CN111445099A - Industrial production data analysis method and system based on association rule - Google Patents

Industrial production data analysis method and system based on association rule Download PDF

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Publication number
CN111445099A
CN111445099A CN201910044615.7A CN201910044615A CN111445099A CN 111445099 A CN111445099 A CN 111445099A CN 201910044615 A CN201910044615 A CN 201910044615A CN 111445099 A CN111445099 A CN 111445099A
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data
industrial production
association rule
association
production data
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石瑞杰
李闯
尹智信
谷牧
邹萍
刘刚
李琳
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Beijing Aerospace Intelligent Technology Development Co ltd
State Grid Corp of China SGCC
State Grid Tianjin Electric Power Co Ltd
State Grid E Commerce Co Ltd
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Beijing Aerospace Intelligent Technology Development Co ltd
State Grid Corp of China SGCC
State Grid Tianjin Electric Power Co Ltd
State Grid E Commerce Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis

Abstract

The invention discloses an industrial production data analysis method based on association rules, which comprises the following steps: acquiring industrial production data, wherein the industrial production data comprises application system related data, equipment operation data and/or control system related data; analyzing the obtained industrial production data to obtain an association rule; and obtaining the association result based on the association rule and carrying out graphical display. According to the method and the system for analyzing the industrial production data based on the association rule, the value of the hidden production data is mined and found by acquiring the industrial production data and analyzing the association rule, so that an enterprise can be assisted to make industrial production improvement measures, the production cost is reduced, and the product quality and the production efficiency are improved.

Description

Industrial production data analysis method and system based on association rule
Technical Field
The invention relates to the technical field of industrial production data management and analysis, in particular to an industrial production data analysis method and system based on association rules.
Background
At present, with the continuous development of scientific technology, the requirements for the intellectualization and automation of industrial production are higher and higher. The following problems exist in the industrial production at present: firstly, data acquisition cannot flexibly define the range of acquired data as required, and original data cannot be uploaded to an upper computer after calculation preprocessing processing is carried out on the original data as required. In the aspect of industrial production, integration level among application systems is not enough, data islands are more, data relation and value cannot be fully mined and analyzed, and cross-system related data analysis capability is not enough.
Disclosure of Invention
In this summary, concepts in a simplified form are introduced that are further described in the detailed description section. This summary of the invention is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.
In view of the above technical problems, the present invention provides an industrial production data analysis method and system based on association rules, which allocates service resources according to priority levels of various factors in service information, optimizes matching between a requested service and a service executor, improves configuration efficiency of the service resources, optimizes allocation results of the service resources, and improves satisfaction of users and service executors.
According to one aspect of the invention, an industrial production data analysis method based on association rules is provided, which comprises the following steps:
acquiring industrial production data, wherein the industrial production data comprises application system related data, equipment operation data and/or control system related data;
analyzing the obtained industrial production data to obtain an association rule;
and obtaining the association result based on the association rule and carrying out graphical display.
In an embodiment of the present invention, the analyzing the acquired industrial production data to obtain the association rule includes:
defining an association rule;
setting a confidence threshold and a support threshold of the association rule;
and finding the association rule in the industrial production data according to the confidence coefficient threshold and the support degree threshold of the association rule.
In one embodiment of the present invention, the acquiring industrial production data comprises:
acquiring data related to industrial production of the application system;
collecting equipment operation data and/or industrial production related data of a control system through an equipment collecting device;
and processing the equipment operation data acquired by the equipment acquisition device and/or the data of the control system related to industrial production.
In an embodiment of the present invention, the finding the association rule in the industrial production data according to the confidence threshold and the support threshold of the association rule includes:
generating a frequent item set based on all item sets meeting the support threshold in the obtained industrial production data;
generating association rules that satisfy the confidence threshold based on the generated frequent item set.
In one embodiment of the invention, if the set of items is
Figure RE-GDA0001992655260000021
And is
Figure RE-GDA0001992655260000022
Then is implied by
Figure RE-GDA0001992655260000023
Referred to as association rules, where X is the antecedent set of rules and Y is the postcedent set of rules.
According to another aspect of the present invention, there is provided an industrial production data analysis system based on association rules, comprising:
the management server is used for acquiring industrial production data, wherein the industrial production data comprises application system related data, equipment operation data and/or control system related data;
and the data analysis platform is used for analyzing the acquired industrial generated data to obtain an association rule, and obtaining an association result based on the association rule and performing graphical display.
In an embodiment of the present invention, when the data analysis platform analyzes the obtained industrial generated data to obtain the association rule, the data analysis platform is specifically configured to:
defining an association rule;
setting a confidence threshold and a support threshold of the association rule;
and finding the association rule in the industrial production data according to the confidence coefficient threshold and the support degree threshold of the association rule.
In one embodiment of the present invention, the method further comprises:
and the equipment data acquisition server is used for processing the equipment operation data acquired by the equipment acquisition device and/or the data of the control system related to industrial production and sending the processed equipment operation data to the management server.
In an embodiment of the present invention, when the data analysis platform finds the association rule in the industrial production data according to the confidence threshold and the support threshold of the association rule, the data analysis platform is specifically configured to:
generating a frequent item set based on all item sets meeting the support threshold in the obtained industrial production data;
generating association rules that satisfy the confidence threshold based on the generated frequent item set.
In one embodiment of the invention, if the set of items is
Figure RE-GDA0001992655260000031
And is
Figure RE-GDA0001992655260000032
Then is implied by
Figure RE-GDA0001992655260000033
Referred to as association rules, where X is the antecedent set of rules and Y is the postcedent set of rules.
According to the method and the system for analyzing the industrial production data based on the association rule, the value of the hidden production data is mined and found by acquiring the industrial production data and analyzing the association rule, so that an enterprise can be assisted to make industrial production improvement measures, the production cost is reduced, and the product quality and the production efficiency are improved.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic block diagram of an exemplary electronic device for implementing an association rule based industrial production data analysis method and system in accordance with embodiments of the present invention;
FIG. 2 is a schematic flow chart diagram of a method for association rule based analysis of industrial production data in accordance with an embodiment of the present invention;
FIG. 3 is a schematic flow chart diagram of an association rule obtaining method according to an embodiment of the present invention;
FIG. 4 is a block diagram of a schematic structure of an association rule based industrial production data analysis system according to an embodiment of the present invention;
FIG. 5 is a diagram of an example architecture of an association rule based industrial production data analysis system, according to an embodiment of the present invention.
Detailed Description
The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. In the following description, numerous specific details are set forth in order to provide a more thorough understanding of the present invention. It will be apparent, however, to one skilled in the art, that embodiments of the invention may be practiced without one or more of these specific details. In other instances, well-known features have not been described in detail so as not to obscure the embodiments of the invention.
The relative arrangement of the components and steps, the numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise. Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description.
Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate. In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.
In order to make the objects, technical solutions and advantages of the present invention more apparent, exemplary embodiments according to the present invention will be described in detail below with reference to the accompanying drawings. It is to be understood that the described embodiments are merely a subset of embodiments of the invention and not all embodiments of the invention, with the understanding that the invention is not limited to the example embodiments described herein. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the invention described herein without inventive step, shall fall within the scope of protection of the invention.
First, an example electronic device 100 for implementing the association rule based industrial production data analysis method and system according to an embodiment of the present invention is described with reference to fig. 1.
As shown in fig. 1, electronic device 100 includes one or more processors 102, one or more memory devices 104, input/output devices 106, and a communication interface 108. It should be noted that the components and structure of the electronic device 100 shown in fig. 1 are only exemplary and not limiting, and the electronic device may have other components and structures, or may not include some of the aforementioned components, for example, may include or may not include a display unit, as needed.
The processor 102 generally represents any type or form of processing unit capable of processing data or interpreting and executing instructions. In general, the processor may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities, and may control other components in the electronic device 100 to perform desired functions. In particular embodiments, processor 102 may receive instructions from a software application or module. These instructions may cause processor 102 to perform the functions of one or more of the example embodiments described and/or illustrated herein.
The storage 104 may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, Random Access Memory (RAM), cache memory (cache), and/or the like. The non-volatile memory may include, for example, Read Only Memory (ROM), hard disk, flash memory, etc. On which one or more computer program instructions may be stored that may be executed by processor 102 to implement client-side functionality (implemented by the processor) and/or other desired functionality in embodiments of the invention described below. Various applications and various data, such as various data used and/or generated by the applications, may also be stored in the computer-readable storage medium.
The input/output device 106 may be a device used by a user to input instructions and output various information to the outside, for example, the input device may include one or more of a keyboard, a mouse, a microphone, a touch screen, and the like. The output devices may include one or more of a display, speakers, and the like.
Communication interface 108 broadly represents any type or form of adapter or communication device capable of facilitating communication between example electronic device 100 and one or more additional devices. For example, the communication interface 108 may facilitate communication between the electronic device 100 and front-end or accessory electronic devices as well as back-end servers or clouds. Examples of communication interface 108 include, but are not limited to, a wired network interface (such as a network interface card), a wireless network interface (such as a wireless network interface card), a modem, and any other suitable interface. In an embodiment, the communication interface 108 provides direct connection to a remote server/remote head end device through direct connection to a network such as the internet. In particular embodiments, communication interface 108 provides direct connection to a remote server/remote head end device through direct connection to a dedicated network, such as a video surveillance network, a skynet system network, or the like. Communication interface 108 may also indirectly provide such connection through any other suitable connection.
For example, the example electronic device for implementing the association rule based industrial production data analysis method and system according to the embodiment of the present invention may be implemented as various computer systems or servers or cloud service systems.
FIG. 2 is a schematic flow chart diagram of a method for analyzing industrial production data based on association rules according to an embodiment of the invention. The method for analyzing industrial production data based on association rules according to the embodiment of the present invention will be described with reference to fig. 2.
As shown in fig. 2, the method for analyzing industrial production data based on association rules disclosed in the embodiment of the present invention includes:
step S201, acquiring industrial production data, wherein the industrial production data includes application system related data, device operation data and/or control system related data.
Illustratively, acquiring industrial production data comprises the steps of:
step A1: data relating to the industrial production of the application system is acquired. The application system comprises a production management system, a quality management system and/or an ERP system and other application systems used in various industrial productions. The application system refers to various systems used for enterprise resource planning, manufacturing execution, quality management, and production management related to industrial production. The system can be realized by corresponding software running on a computer and a server.
Step A2: the device acquisition device acquires device operating data and/or data of the control system related to industrial production. That is, the plant operating data and/or the data of the control system relating to the industrial production are acquired by arranging plant acquisition means on the plant and/or the control system. The device acquisition device can be various sensing and monitoring devices and can also be realized by data acquisition software running on a processor. The equipment refers to various production equipment used in industrial production, and the control system refers to a system for controlling various production equipment in industrial production. Plant operational data refers to parameters of the operation of various production plants in an industrial process. The relevant parameters of the control system refer to parameters of the control system relevant to industrial production.
Step A3: and processing the equipment operation data of the equipment acquired by the equipment acquisition device and/or the related data of the control system.
The processing is, for example, structured processing of data based on logical relationships.
Step S202, analyzing the obtained industrial generated data to obtain an association rule.
Illustratively, as shown in fig. 3, analyzing the obtained industrial production data to obtain the association rule includes the following steps:
step S301, an association rule is defined.
As an example, in the present embodiment, the association rule is defined as: let R ═ { I1, I2 … ….. In } be a production site data set, called an Item (Item), while giving a database D In which each product T is a data set of items, satisfying
Figure RE-GDA0001992655260000081
Each product is provided with a unique identification serial number called Tid. X is a subset of I, if
Figure RE-GDA0001992655260000082
Then T is said to contain X; if the element of X is K, then X is called a K-item set (K-Itemset).
If item set
Figure RE-GDA0001992655260000083
And is
Figure RE-GDA0001992655260000084
Then it acts as
Figure RE-GDA0001992655260000085
Is called an association rule, where X is a set of antecedent terms of the rule and Y is a set of postcedent terms of the rule, indicating that a product T containing X terms will also likely contain Y terms,
rules
Figure RE-GDA0001992655260000086
The confidence expression of (2):
Figure RE-GDA0001992655260000087
rules
Figure RE-GDA0001992655260000088
The support expression of (1):
Figure RE-GDA0001992655260000089
further, since the association rule is defined, in step S201, in the industrial production site, according to the corpus attribute of R, different business data are collected according to the serial number of the product, and the data are stored in the database D.
TABLE 1 data Collection example
Figure RE-GDA00019926552600000810
Figure RE-GDA0001992655260000091
Step S302, a confidence threshold and a support threshold of the association rule are set.
Step S303, finding the association rule in the industrial generated data according to the confidence threshold and the support threshold of the association rule. That is, the association rule in which all the support degree support > min _ support and the confidence > min _ confidence are found.
Illustratively, the finding of the association rule in the obtained industrially generated data according to the confidence threshold and the support threshold of the association rule comprises the following steps:
and generating a frequent item set based on all item sets meeting the support threshold in the acquired industrial production data. That is, a frequent item set is generated, and all item sets satisfying the minimum support degree are found, and the found item sets are called the frequent item set.
Generating association rules that satisfy a confidence threshold based on the generated frequent item set. That is, a rule is generated that satisfies a minimum confidence level based on the generation of a frequent item set
And step S203, obtaining the association result based on the association rule and carrying out graphical display.
Namely, the correlation result obtained through the correlation analysis is graphically displayed in the system, and the user can access the cloud application through the terminal to obtain the analysis result.
Further, the method association rule-based industrial production data analysis of the embodiment further includes the following steps:
the association rule is understood and evaluated, namely the association rule is verified by analyzing the characteristics of the association rule and combining with the actual production situation, and meanwhile, the enterprise decision is assisted, the enterprise management is improved, the efficiency is improved, and the cost is reduced.
According to the industrial production data analysis method based on the association rule, the hidden production data value is mined and found through the acquisition of industrial production data and the analysis of the association rule, enterprises are assisted to make industrial production improvement measures, the production cost is reduced, and the product quality and the production efficiency are improved.
Fig. 4 is a schematic block diagram of an industrial production data analysis system based on association rules according to an embodiment of the present invention. An industrial production data analysis system based on association rules according to an embodiment of the present invention is described below with reference to fig. 4.
As shown in fig. 4, the association rule based industrial production data analysis system 400 according to an embodiment of the present invention includes a device data collection server 410, a management server 420, and a data analysis platform 430.
The device data collecting server 410 is configured to process device operation data and/or control system related data collected by the device data collecting apparatus, and send the processed device operation data to the management server 420. The device data collection server 410 may be implemented by the processor 102 in the electronic device shown in fig. 1 executing the program instructions stored in the storage device 104, and may perform step S201 in the association rule-based industrial production data analysis method according to the embodiment of the present invention.
The management server 420 is configured to obtain industrial production data including application system related data, equipment operating data, and/or control system related data. The management server 420 may be implemented by the processor 102 in the electronic device shown in fig. 1 executing the program instructions stored in the storage device 104, and may perform step S201 in the association rule based industrial production data analysis method according to the embodiment of the present invention.
The data analysis platform 430 is configured to analyze the acquired industrial production data to obtain association rules, and obtain association results according to the association rules and perform graphical display. The data analysis platform 430 may be implemented by the processor 102 in the electronic device shown in fig. 1 executing the program instructions stored in the storage device 104, and may perform steps S202 to S203 and S301 to S303 in the association rule based industrial production data analysis method according to the embodiment of the present invention.
FIG. 5 is a diagram of an example architecture of an association rule based industrial production data analysis system, according to an embodiment of the present invention.
As shown in fig. 5, the related data of the application systems including the enterprise production management system, the quality management system, the ERP system, etc., as well as the device operation data and the automation control system related data are integrated by the management server. The equipment operation data and the related data of the automatic control system are collected through the equipment data collecting device, processed through the equipment data collecting server and transmitted to the management server. The management server collects data from the application system and the equipment data acquisition server according to a logical relation and uploads the data to the cloud platform, and the cloud platform association rule analysis application performs association rule-based data analysis on the acquired industrial production data.
The data analysis process based on the association rule of the cloud platform association rule analysis application on the collected industrial production data is as follows:
(1) defining association rules
Let R ═ { I1, I2 … ….In is a production site data set called Item (Item) given a database D, where each product T is a data set of items satisfying
Figure RE-GDA0001992655260000111
Each product is provided with a unique identification serial number called Tid. X is a subset of I, if
Figure RE-GDA0001992655260000119
Then T is said to contain X; if the element of X is K, then X is called a K-item set (K-Itemset).
If item set
Figure RE-GDA0001992655260000112
And is
Figure RE-GDA0001992655260000113
Then it acts as
Figure RE-GDA0001992655260000114
Is called an association rule, where X is a set of antecedent terms of the rule and Y is a set of postcedent terms of the rule, indicating that a product T containing X terms will also likely contain Y terms,
rules
Figure RE-GDA0001992655260000115
The confidence expression of (2):
Figure RE-GDA0001992655260000116
rules
Figure RE-GDA0001992655260000117
The support expression of (1):
Figure RE-GDA0001992655260000118
(2) data storage
And (3) on the industrial production site, acquiring different service data according to the full set attribute of the R in the step 1 and the serial number of the product, and storing the data in a database D. A data collection example is shown in table 1.
(3) Mining of association rules
Setting support degree and reliability threshold value, and discovering association rule by using data mining algorithm
And finding out association rules of all support degree, min _ support and confidence degree, min _ confidence.
A generating frequent item set
And finding all item sets meeting the minimum support degree, wherein the found item sets are called frequent item sets.
B Generation rules
Generating rules satisfying minimum confidence levels based on generating the frequent item sets.
(4) Data presentation
And the system carries out graphical display through the correlation result obtained by the correlation analysis, and the analysis result can be obtained by accessing the cloud application through the terminal.
(5) Understanding and evaluating association rules
By analyzing the characteristics of the association rule and combining with the actual production situation, the association rule is verified, meanwhile, the enterprise decision is assisted, the enterprise management is improved, the efficiency is improved, and the cost is reduced.
In addition, another industrial production data analysis device based on association rules is provided in an embodiment of the present invention, which includes a memory, a processor, and a computer program stored in the memory and running on the processor, where the processor implements the steps of the foregoing method shown in fig. 2 or fig. 3 when executing the computer program.
Furthermore, according to an embodiment of the present invention, there is also provided a storage medium on which program instructions are stored, which when executed by a computer or a processor are used for executing the corresponding steps of the automatic service resource allocation method according to an embodiment of the present invention, and for implementing the corresponding units or modules of the automatic service resource allocation system according to an embodiment of the present invention. The storage medium may include, for example, a hard disk of a personal computer, a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a portable compact disc read-only memory (CD-ROM), a USB memory, or any combination of the above. The computer-readable storage medium may be any combination of one or more computer-readable storage media.
In one embodiment, the computer program instructions, when executed by a computer, may implement the functional modules of the association rule based industrial production data analysis system according to the embodiment of the present invention and/or may execute the association rule based industrial production data analysis method according to the embodiment of the present invention.
In one embodiment, the computer program instructions, when executed by a computer, perform the steps of: acquiring industrial production data, wherein the industrial production data comprises application system related data, equipment operation data and/or control system related data; analyzing the obtained industrial data to obtain an association rule; and obtaining the association result according to the association rule and carrying out graphical display.
The modules in the association rule-based industrial production data analysis system according to the embodiment of the present invention may be implemented by the electronic device, the server, the processor of the system for implementing the association rule-based industrial production data analysis method according to the embodiment of the present invention running computer program instructions stored in the memory, or may be implemented when computer instructions stored in the computer readable storage medium of the computer program product according to the embodiment of the present invention are executed by the computer.
According to the industrial production data analysis method and system based on the association rule, the value of hidden production data is mined and found by collecting industrial production data and analyzing the association rule, enterprises are assisted to make industrial production improvement measures, the production cost is reduced, and the product quality and the production efficiency are improved.
Although the illustrative embodiments have been described herein with reference to the accompanying drawings, it is to be understood that the foregoing illustrative embodiments are merely exemplary and are not intended to limit the scope of the invention thereto. Various changes and modifications may be effected therein by one of ordinary skill in the pertinent art without departing from the scope or spirit of the present invention. All such changes and modifications are intended to be included within the scope of the present invention as set forth in the appended claims.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described device embodiments are merely illustrative, and for example, the division of the units is only one logical functional division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another device, or some features may be omitted, or not executed.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the invention and aiding in the understanding of one or more of the various inventive aspects. However, the method of the present invention should not be construed to reflect the intent: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
It will be understood by those skilled in the art that all of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where such features are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.
The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It will be appreciated by those skilled in the art that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functionality of some of the modules in an item analysis apparatus according to embodiments of the present invention. The present invention may also be embodied as apparatus programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
The above description is only for the specific embodiment of the present invention or the description thereof, and the protection scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and the changes or substitutions should be covered within the protection scope of the present invention. The protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (10)

1. An industrial production data analysis method based on association rules is characterized by comprising the following steps:
acquiring industrial production data, wherein the industrial production data comprises application system related data, equipment operation data and/or control system related data;
analyzing the obtained industrial production data to obtain an association rule;
and obtaining the association result based on the association rule and carrying out graphical display.
2. The method of claim 1, wherein analyzing the obtained industrial production data for association rules comprises:
defining an association rule;
setting a confidence threshold and a support threshold of the association rule;
and finding the association rule in the industrial production data according to the confidence coefficient threshold and the support degree threshold of the association rule.
3. The method of claim 1, wherein the obtaining industrial production data comprises:
acquiring data related to industrial production of the application system;
collecting equipment operation data and/or industrial production related data of a control system through an equipment collecting device;
and processing the equipment operation data acquired by the equipment acquisition device and/or the data of the control system related to industrial production.
4. The method of claim 2, wherein finding association rules in the industrial production data according to their confidence thresholds and support thresholds comprises:
generating a frequent item set based on all item sets meeting the support threshold in the obtained industrial production data;
generating association rules that satisfy the confidence threshold based on the generated frequent item set.
5. The method of claim 4, wherein if the set of items is present
Figure FDA0001948739440000011
And is
Figure FDA0001948739440000012
Then is implied by
Figure FDA0001948739440000013
Referred to as association rules, where X is the antecedent set of rules and Y is the postcedent set of rules.
6. An association rule based industrial production data analysis system, comprising:
the management server is used for acquiring industrial production data, wherein the industrial production data comprises application system related data, equipment operation data and/or control system related data;
and the data analysis platform is used for analyzing the acquired industrial generated data to obtain an association rule, and obtaining an association result based on the association rule and performing graphical display.
7. The system of claim 6, wherein the data analysis platform, when analyzing the obtained industrially generated data to obtain association rules, is specifically configured to:
defining an association rule;
setting a confidence threshold and a support threshold of the association rule;
and finding the association rule in the industrial production data according to the confidence coefficient threshold and the support degree threshold of the association rule.
8. The system of claim 6, further comprising:
and the equipment data acquisition server is used for processing the equipment operation data acquired by the equipment acquisition device and/or the data of the control system related to industrial production and sending the processed equipment operation data to the management server.
9. The system of claim 7, wherein the data analysis platform, when finding an association rule in the industrial production data based on a confidence threshold and a support threshold of the association rule, is specifically configured to:
generating a frequent item set based on all item sets meeting the support threshold in the obtained industrial production data;
generating association rules that satisfy the confidence threshold based on the generated frequent item set.
10. The system of claim 9, wherein if said set of items is present
Figure FDA0001948739440000021
Figure FDA0001948739440000022
And is
Figure FDA0001948739440000023
Then is implied by
Figure FDA0001948739440000024
Referred to as association rules, where X is the antecedent set of rules and Y is the postcedent set of rules.
CN201910044615.7A 2019-01-17 2019-01-17 Industrial production data analysis method and system based on association rule Pending CN111445099A (en)

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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101576881A (en) * 2008-05-07 2009-11-11 万德洪 Data visualization system and realization method
CN101655857A (en) * 2009-09-18 2010-02-24 西安建筑科技大学 Method for mining data in construction regulation field based on associative regulation mining technology
CN106126637A (en) * 2016-06-23 2016-11-16 东软集团股份有限公司 A kind of vehicles classification recognition methods and device
CN106874491A (en) * 2017-02-22 2017-06-20 北京科技大学 A kind of device fault information method for digging based on dynamic association rules

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101576881A (en) * 2008-05-07 2009-11-11 万德洪 Data visualization system and realization method
CN101655857A (en) * 2009-09-18 2010-02-24 西安建筑科技大学 Method for mining data in construction regulation field based on associative regulation mining technology
CN106126637A (en) * 2016-06-23 2016-11-16 东软集团股份有限公司 A kind of vehicles classification recognition methods and device
CN106874491A (en) * 2017-02-22 2017-06-20 北京科技大学 A kind of device fault information method for digging based on dynamic association rules

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