CN109190892A - A kind of intelligent injection-moulding device detection device detection frequency decision-making technique based on data - Google Patents
A kind of intelligent injection-moulding device detection device detection frequency decision-making technique based on data Download PDFInfo
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Abstract
The present invention relates to testing techniques of equipment fields, relate to a kind of intelligent injection-moulding device detection device detection frequency decision-making technique and device based on data, and storage medium, computer, the present invention is by utilizing neural network model, the operation data of bonding apparatus carries out decision to assembly detection apparatus detection frequency, guarantee collects enough system status informations and carrys out design control law simultaneously, the efficiency and stability and its reliability of the intelligent injection-moulding device of raising, optimize the validity of the execution control rate of equipment to greatest extent, the safety of equipment, product quality, and service life, and then utilize default expertise equipment scrapping index, judge whether equipment is in scrap, it selects and purchase replacement in time for equipment and foundation is provided, it is capable of the detection frequency of Intelligent Optimal injection-moulding device detection device, guarantee to collect enough system modes simultaneously Information carrys out design control law, improves the efficiency and stability and its reliability of intelligent injection-moulding device, has very strong creativeness.
Description
Technical field
The present invention relates to testing techniques of equipment fields, and in particular to a kind of intelligent injection-moulding device based on data detects dress
Set detection frequency decision-making technique and device and storage medium, computer.
Background technique
With the fast development of new and high technology, the automation equipment in the fields such as intelligence manufacture is showed extensive and is complicated
Trend, due to intelligent injection-moulding device be mostly it is distributed, intelligent injection-moulding device can be restricted if there is too many wiring
Production process reduces system flexibility and reduces production efficiency.Simultaneously as wireless network has good flexibility and extension
Property, and wiring cost can be reduced.Therefore, collected system mode letter is transmitted frequently with radio transmission apparatus
Breath.But for it is certain need shut down detection equipment, need to consider simultaneously detect frequency, device security, product quality,
The important informations such as detection loss are shut down, therefore in the case where not considering the bandwidth and energy of wireless network, how to set intelligence
The detection frequency of injection-moulding device detection device, while guaranteeing that collecting enough system status informations carrys out design control law, improves
The efficiency and stability and its reliability of intelligent injection-moulding device are vital problem in science.
Summary of the invention
In view of this, the embodiment of the present invention is designed to provide a kind of intelligent injection-moulding device detection device based on data
Frequency decision-making technique and device and storage medium, computer are detected, for certain equipment for needing to shut down detection, is not being examined
In the case where bandwidth and the energy of considering wireless network, it is capable of the detection frequency of Intelligent Optimal injection-moulding device detection device, protects simultaneously
Card collects enough system status informations and carrys out design control law, improves the efficiency and stability and its can of intelligent injection-moulding device
By property.
It is as follows that the embodiment of the present invention solves technical solution used by above-mentioned technical problem:
A kind of intelligent injection-moulding device detection device detection frequency decision-making technique based on data, comprising the following steps:
1) operation data of intelligent injection-moulding device is obtained；
2) intelligent injection-moulding device detection device of the building based on neural network model detects frequency decision model；
3) frequency decision model is detected using the intelligent injection-moulding device detection device of training in advance, is molded according to the intelligence
The operation data of equipment determines the intelligent injection-moulding device detection device detection frequency result of decision；
4) expertise equipment scrapping index model is established；
5) using default expertise equipment scrapping index, judge whether equipment is in and scrap.
Preferably, include the operating parameter X of intelligent injection-moulding device currently in use in the operation data, shut down detection damage
Consumption index D, times N, product parameters and nominal parameters absolute error E have been detected.
Preferably, the building of the step 2) includes the following contents:
Building first layer is the intelligent injection-moulding device operation data input layer, the second layer is the intelligent injection-moulding device fortune
Row data feature extraction layer, third layer are the three layer depths nerve that intelligent injection-moulding device detection device detects frequency result of decision layer
Network model, wherein the determination of intelligent injection-moulding device detection device detection frequency decision model weight, at the beginning of random initializtion weight
Begin, using the intelligent injection-moulding device operation data and minimum detection device detection frequency f1 as inputoutput data, utilizes
BP back-propagation algorithm training neural network model obtains the weight of intelligent injection-moulding device detection device detection frequency decision model.
Preferably, the step 3) detects frequency decision model using the intelligent injection-moulding device detection device of training in advance,
According to the intelligent injection-moulding device operation data, it is first determined the feature vector of intelligent injection-moulding device operation data, and then determine
The intelligence injection-moulding device detection device detects the frequency result of decision.
Preferably, the step 4) utilizes expert knowledge library data, according to each expert's synthetic reliability, determines intelligence note
Mould the corresponding expectation equipment scrapping index of equipment described eigenvector.
Preferably, the equipment scrapping index includes:
1. minimum frequency index f1 refers to and guarantees that controller acquires enough system status informations and is able to carry out effective control
The minimum frequency acquisition of rate processed has the acquisition of expertise knowledge base；
2. product parameters and nominal parameters maximum absolute error E1, refer to the absolute value of actual product Yu standardized product parameter
Error guarantees the key index of product quality；
3. shutting down detection loss objective D1, refer to that the loss detected every time is detecting cumulative in times N 1, equipment damage
Consumption reaches loss threshold value and selects and purchase replacement in time, ensures the security reliability of equipment；
The synthetic reliability of each expert are as follows:
Assuming that one group of expert A1、A1、…、AnConfidence level be P1、P2、…、Pn, then
Referred to as expertAbout A1、A1、…、AnSynthetic reliability.
Preferably, the step 5) utilizes intelligent injection-moulding device detection device detection frequency result of decision f and aforementioned reality
Product parameters are compared with standardized product parameter error E, shutdown detection loss D and expertise equipment scrapping index, are E
≤ E1, D≤D1, f1≤f has an index to be unsatisfactory for, then carries out scrapping processing.
Preferably, a kind of intelligent injection-moulding device detection device detects frequency decision making device, it is characterised in that: obtains including data
Modulus block, intelligent injection-moulding device detection device detection frequency decision model construct module, decision-making module, expertise equipment scrapping
Index model constructs module and judgment module；
The data acquisition module is used to obtain the operation data of intelligent injection-moulding device；
The intelligence injection-moulding device detection device detection frequency decision model building module is based on neural network for constructing
The intelligent injection-moulding device detection device of model detects frequency decision model；
The decision-making module is used to detect frequency decision model, root using the intelligent injection-moulding device detection device of training in advance
According to the operation data of the intelligent injection-moulding device, the intelligent injection-moulding device detection device detection frequency result of decision is determined；
The expertise equipment scrapping index model building module is for determining operating status described in intelligent injection-moulding device
Corresponding expectation equipment scrapping index；
The judgment module judges whether equipment is in and scraps using default expertise equipment scrapping index.
Preferably, a kind of computer equipment, including memory, processor and storage are on a memory and can be on a processor
The computer program of operation, it is characterised in that: the processor is realized when executing described program as any in claim 1 to 7
The step of intelligence injection-moulding device detection device detection frequency decision-making technique.
Preferably, a kind of computer readable storage medium is stored with computer journey on the computer readable storage medium
Sequence, it is characterised in that: the intelligence note as described in any in claim 1 to 7 is realized when the computer program is executed by processor
The step of moulding assembly detection apparatus detection frequency decision-making technique.
The invention has the benefit that
The present invention by utilizing neural network model, the operation data of bonding apparatus to assembly detection apparatus detect frequency into
Row decision, guarantee collect enough system status informations and carry out design control law simultaneously, improve intelligent injection-moulding device efficiency and
Stability and its reliability, optimize to greatest extent the safety of validity, equipment of the execution control rate of equipment, product quality,
And service life, and then using default expertise equipment scrapping index, judge whether equipment is in and scrap, is that equipment is timely
It selects and purchase replacement and foundation is provided.
Detailed description of the invention
The flow chart of the intelligent injection-moulding device detection device detection frequency decision-making technique of Fig. 1 present invention.
The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.
Specific embodiment
In order to be clearer and more clear technical problems, technical solutions and advantages to be solved, tie below
Drawings and examples are closed, the present invention will be described in further detail.It should be appreciated that specific embodiment described herein is only
To explain the present invention, it is not intended to limit the present invention.
Embodiment one
Referring to FIG. 1, a kind of intelligence injection-moulding device detection device detects frequency decision-making technique, comprising the following steps:
S1. the operation data of intelligent injection-moulding device is obtained；
The operating parameter X of intelligent injection-moulding device currently in use is respectively included in the operation data, shuts down detection loss
Index D, times N, product parameters and nominal parameters absolute error E have been detected；
S2. the intelligent injection-moulding device detection device detection frequency decision model based on neural network model is constructed
Step S1 constructs three layer depth neural network models, and first layer is the intelligent injection-moulding device operation data input
Layer, the second layer are the intelligent injection-moulding device operation data feature extraction layer, third layer is intelligent injection-moulding device detection device inspection
Measured frequency result of decision layer.The determination of intelligent injection-moulding device detection device detection frequency decision model weight, random initializtion power
Weight is initial, using the intelligent injection-moulding device operation data and minimum detection device detection frequency f1 as inputoutput data,
Intelligent injection-moulding device detection device detection frequency decision model is obtained using BP back-propagation algorithm training neural network model
Weight；
Minimum detection device detects frequency f1, refers to and guarantees that controller acquires enough system status informations and is able to carry out
The minimum frequency acquisition of effective control rate has the acquisition of expertise knowledge base.
S3. frequency decision model is detected using the intelligent injection-moulding device detection device of training in advance, is infused according to the intelligence
The operation data for moulding equipment determines the intelligent injection-moulding device detection device detection frequency result of decision；
Frequency decision model is detected using the intelligent injection-moulding device detection device of training in advance, is set according to the intelligence injection molding
Standby operation data, it is first determined the feature vector of intelligent injection-moulding device operation data, and then determine the intelligent injection-moulding device inspection
It surveys device and detects the frequency result of decision；
S4. expertise equipment scrapping index model is established；Including following sub-step:
It is determined using expert knowledge library data according to the synthetic reliability of the scientific and technological level of each expert, that is, expert
The corresponding expectation equipment scrapping index of intelligent injection-moulding device described eigenvector
Equipment scrapping index refers to that minimum frequency index f1 refers to and guarantees that controller acquires enough system status informations
And it is able to carry out the minimum frequency acquisition of effective control rate, there is the acquisition of expertise knowledge base.
Product parameters and nominal parameters maximum absolute error E1 refer to that the absolute value of actual product and standardized product parameter misses
Difference guarantees the key index of product quality.
Detection loss objective D1 is shut down, refers to that the loss detected every time is detecting cumulative in times N 1, equipment loss
Reach loss threshold value and select and purchase replacement in time, ensures the security reliability of equipment.
The synthetic reliability of each expert refers to,
Assuming that one group of expert A1、A1、…、AnConfidence level be P1、P2、…、Pn, then
Referred to as expertAbout A1、A1、…、AnSynthetic reliability
S5. using default expertise equipment scrapping index, judge whether equipment is in and scrap, including following sub-step:
Frequency result of decision f and aforementioned actual product parameter and standardized product are detected using intelligent injection-moulding device detection device
Parameter error E, it shuts down detection loss D and expertise equipment scrapping index compares, is E≤E1, D≤D1, f1≤f,
There is an index to be unsatisfactory for, then carries out scrapping processing.
From the foregoing, it will be observed that the method for the present invention obtains the operation data of intelligent injection-moulding device first, training in advance is then utilized
Intelligent injection-moulding device detection device detects frequency decision model, according to the intelligent injection-moulding device operation data, determines the intelligence
Energy injection-moulding device detection device detects the frequency result of decision, and then using default expertise equipment scrapping index, judges equipment
Whether it is in and scraps.
As a result, by utilizing neural network model, the operation data of bonding apparatus to assembly detection apparatus detect frequency into
Row decision, guarantee collect enough system status informations and carry out design control law simultaneously, improve intelligent injection-moulding device efficiency and
Stability and its reliability, optimize to greatest extent the safety of validity, equipment of the execution control rate of equipment, product quality,
And service life, and then using default expertise equipment scrapping index, judge whether equipment is in and scrap, is that equipment is timely
It selects and purchase replacement and foundation is provided.
Embodiment two
One kind includes data acquisition module, intelligence based on data intelligence injection-moulding device detection device detection frequency decision making device
Injection-moulding device detection device detects frequency decision model and constructs module, decision-making module, expertise equipment scrapping index model structure
Model block and judgment module；
Data acquisition module, for obtaining the operation data of intelligent injection-moulding device；
Intelligent injection-moulding device detection device detection frequency decision model constructs module, is based on neural network model for constructing
Intelligent injection-moulding device detection device detect frequency decision model；
Decision-making module, for detecting frequency decision model using the intelligent injection-moulding device detection device of training in advance, according to
The operation data of the intelligence injection-moulding device determines the intelligent injection-moulding device detection device detection frequency result of decision.
Expertise equipment scrapping index model constructs module, for determining that operating status described in intelligent injection-moulding device is corresponding
Expectation equipment scrapping index
Judgment module judges whether equipment is in and scraps using default expertise equipment scrapping index.
Wherein, detection device detection frequency decision model building module includes following submodule:
Three layer depth neural network models are constructed, first layer is the intelligent injection-moulding device operation data input layer, second
Layer is the intelligent injection-moulding device operation data feature extraction layer, third layer is that intelligent injection-moulding device detection device detection frequency is determined
Plan resultant layer.
The determination of intelligent injection-moulding device detection device detection frequency decision model weight, random initializtion weight is initial, benefit
Use the intelligent injection-moulding device operation data and minimum detection device detection frequency f1 as inputoutput data, it is reversed using BP
Propagation algorithm training neural network model obtains the weight of intelligent injection-moulding device detection device detection frequency decision model；
Minimum detection device detects frequency f1, refers to and guarantees that controller acquires enough system status informations and is able to carry out
The minimum frequency acquisition of effective control rate has the acquisition of expertise knowledge base.
Decision-making module includes following submodule:
Frequency decision model is detected using the intelligent injection-moulding device detection device of training in advance, is set according to the intelligence injection molding
Standby operation data, it is first determined the feature vector of intelligent injection-moulding device operation data, and then determine the intelligent injection-moulding device inspection
It surveys device and detects the frequency result of decision.
Equipment scrapping index refers to,
Minimum frequency index f1 refers to and guarantees that controller acquires enough system status informations and is able to carry out effective control
The minimum frequency acquisition of rate has the acquisition of expertise knowledge base.
Product parameters and nominal parameters maximum absolute error E1 refer to that the absolute value of actual product and standardized product parameter misses
Difference guarantees the key index of product quality.
Detection loss objective D1 is shut down, refers to that the loss detected every time is detecting cumulative in times N 1, equipment loss
Reach loss threshold value and select and purchase replacement in time, ensures the security reliability of equipment.
Further, the synthetic reliability of each expert refers to,
Assuming that one group of expert A1、A1、…、AnConfidence level be P1、P2、…、Pn, then
Referred to as expertAbout A1、A1、…、AnSynthetic reliability.
The judgment module includes following submodule
Frequency result of decision f and aforementioned actual product parameter and standardized product are detected using intelligent injection-moulding device detection device
Parameter error E, it shuts down detection loss D and expertise equipment scrapping index compares, is E≤E1, D≤D1, f1≤f,
There is an index to be unsatisfactory for, then carries out scrapping processing.
Embodiment three
A kind of computer equipment can be run on a memory and on a processor including memory, processor and storage
Computer program, the processor realize that the intelligent injection-moulding device detection device of the present invention detects frequency decision when executing described program
The step of method.
A kind of computer readable storage medium is stored with computer program on the computer readable storage medium, described
The step of intelligent injection-moulding device detection device of the present invention detects frequency decision-making technique is realized when computer program is executed by processor.
Computer can be the calculating such as mobile terminal, desktop PC, notebook, palm PC and cloud server and set
It is standby.The computer may include, but be not limited only to, processor, memory.The processor can be central processing unit
(Central Processing Unit, CPU), can also be other general processors, digital signal processor (Digital
Signal Processor, DSP), specific integrated circuit (Application Specific Integrated Circuit,
ASIC), ready-made programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic
Device, discrete gate or transistor logic, discrete hardware components etc..General processor can be microprocessor or this at
Reason device is also possible to any conventional processor etc..
Memory can be the internal storage unit of the computer, such as the hard disk or memory of computer.The storage
Device is also possible to the plug-in type hard disk being equipped on the External memory equipment of the computer, such as the computer, intelligent storage
Block (Smart Media Card, SMC), secure digital (Secure Digital, SD) card, flash card (Flash Card) etc..
Further, the memory can also both including the computer internal storage unit and also including External memory equipment.Institute
Memory is stated for other programs and data needed for storing the computer program and the computer.The memory is also
It can be used for temporarily storing the data that has exported or will export.
Preferred embodiments of the present invention have been described above with reference to the accompanying drawings, not thereby limiting the scope of the invention.This
Field technical staff without departing from the scope and spirit of the invention in made by any modifications, equivalent replacements, and improvements, should all this
Within the interest field of invention.
Claims (10)
1. a kind of intelligent injection-moulding device detection device based on data detects frequency decision-making technique, it is characterised in that: including following
Step:
1) operation data of intelligent injection-moulding device is obtained；
2) intelligent injection-moulding device detection device of the building based on neural network model detects frequency decision model；
3) frequency decision model is detected using the intelligent injection-moulding device detection device of training in advance, according to the intelligent injection-moulding device
Operation data, determine the intelligent injection-moulding device detection device detection frequency result of decision；
4) expertise equipment scrapping index model is established；
5) using default expertise equipment scrapping index, judge whether equipment is in and scrap.
2. intelligent injection-moulding device detection device detects frequency decision-making technique according to claim 1, it is characterised in that: the fortune
Include in row data the operating parameter X of intelligent injection-moulding device currently in use, shut down detection loss objective D, detected times N,
Product parameters and nominal parameters absolute error E.
3. intelligent injection-moulding device detection device detects frequency decision-making technique according to claim 1, it is characterised in that: the step
Rapid building 2) includes the following contents:
Building first layer is the intelligent injection-moulding device operation data input layer, the second layer is the intelligent injection-moulding device operation number
It is the three layer depth neural networks that intelligent injection-moulding device detection device detects frequency result of decision layer according to feature extraction layer, third layer
Model, wherein the determination of intelligent injection-moulding device detection device detection frequency decision model weight, random initializtion weight is initial, benefit
Use the intelligent injection-moulding device operation data and minimum detection device detection frequency f1 as inputoutput data, it is reversed using BP
Propagation algorithm training neural network model obtains the weight of intelligent injection-moulding device detection device detection frequency decision model.
4. intelligent injection-moulding device detection device detects frequency decision-making technique according to claim 1, it is characterised in that: the step
It is rapid 3) to detect frequency decision model using the intelligent injection-moulding device detection device of training in advance, it is transported according to the intelligent injection-moulding device
Row data, it is first determined the feature vector of intelligent injection-moulding device operation data, and then determine the intelligent injection-moulding device detection dress
Set the detection frequency result of decision.
5. intelligent injection-moulding device detection device detects frequency decision-making technique according to claim 1, it is characterised in that: the step
It is rapid 4) to utilize expert knowledge library data, according to each expert's synthetic reliability, determine intelligence injection-moulding device described eigenvector pair
The expectation equipment scrapping index answered.
6. intelligent injection-moulding device detection device detects frequency decision-making technique according to claim 5, it is characterised in that: described to set
Include: for scrap indicator
1. minimum frequency index f1 refers to and guarantees that controller acquires enough system status informations and is able to carry out effective control rate
Minimum frequency acquisition, have expertise knowledge base acquisition；
2. product parameters and nominal parameters maximum absolute error E1 refer to that the absolute value of actual product and standardized product parameter misses
Difference guarantees the key index of product quality；
3. shutting down detection loss objective D1, refer to that the loss detected every time is detecting adding up in times N 1, equipment loss reaches
Replacement is selected and purchased in time to loss threshold value, ensures the security reliability of equipment；
The synthetic reliability of each expert are as follows:
Assuming that one group of expert A1、A1、…、AnConfidence level be P1、P2、…、Pn, then
Referred to as expertAbout A1、A1、…、AnSynthetic reliability.
7. intelligent injection-moulding device detection device detects frequency decision-making technique according to claim 1, it is characterised in that: the step
It is rapid 5) to utilize intelligent injection-moulding device detection device detection frequency result of decision f and aforementioned actual product parameter and standardized product parameter
Error E, shutdown detection loss D and expertise equipment scrapping index compare, and are E≤E1, D≤D1, f1≤f, there is one
Item index is unsatisfactory for, then carries out scrapping processing.
8. a kind of intelligence injection-moulding device detection device detects frequency decision making device, it is characterised in that: including data acquisition module, intelligence
It can injection-moulding device detection device detection frequency decision model building module, decision-making module, expertise equipment scrapping index model
Construct module and judgment module；
The data acquisition module is used to obtain the operation data of intelligent injection-moulding device；
The intelligence injection-moulding device detection device detection frequency decision model building module is based on neural network model for constructing
Intelligent injection-moulding device detection device detect frequency decision model；
The decision-making module is used to detect frequency decision model using the intelligent injection-moulding device detection device of training in advance, according to institute
The operation data for stating intelligent injection-moulding device determines the intelligent injection-moulding device detection device detection frequency result of decision；
The expertise equipment scrapping index model building module is for determining that operating status described in intelligent injection-moulding device is corresponding
Expectation equipment scrapping index；
The judgment module judges whether equipment is in and scraps using default expertise equipment scrapping index.
9. a kind of computer equipment including memory, processor and stores the meter that can be run on a memory and on a processor
Calculation machine program, it is characterised in that: the processor realizes the intelligence as described in any in claim 1 to 7 when executing described program
Injection-moulding device detection device detects the step of frequency decision-making technique.
10. a kind of computer readable storage medium, computer program, feature are stored on the computer readable storage medium
It is: realizes the intelligent injection-moulding device detection as described in any in claim 1 to 7 when the computer program is executed by processor
Device detects the step of frequency decision-making technique.
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| CN201810847313.9A CN109190892B (en) | 2018-07-27 | 2018-07-27 | Data-based intelligent injection molding equipment detection device detection frequency decision method |
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| CN201810847313.9A CN109190892B (en) | 2018-07-27 | 2018-07-27 | Data-based intelligent injection molding equipment detection device detection frequency decision method |
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