CN106325154B - A kind of tealeaves rolling heating stirring machine control method based on pattern-recognition - Google Patents
A kind of tealeaves rolling heating stirring machine control method based on pattern-recognition Download PDFInfo
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- CN106325154B CN106325154B CN201610716271.6A CN201610716271A CN106325154B CN 106325154 B CN106325154 B CN 106325154B CN 201610716271 A CN201610716271 A CN 201610716271A CN 106325154 B CN106325154 B CN 106325154B
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- 238000005096 rolling process Methods 0.000 title claims abstract description 38
- 238000010438 heat treatment Methods 0.000 title claims abstract description 25
- 238000003756 stirring Methods 0.000 title claims abstract description 25
- 238000000034 method Methods 0.000 title claims abstract description 18
- 238000003909 pattern recognition Methods 0.000 title claims abstract description 18
- 238000005457 optimization Methods 0.000 claims abstract description 5
- 238000013499 data model Methods 0.000 claims description 17
- 238000013528 artificial neural network Methods 0.000 claims description 3
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 239000002994 raw material Substances 0.000 description 1
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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
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
- G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
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- G06F30/20—Design optimisation, verification or simulation
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- G—PHYSICS
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Abstract
The tealeaves rolling heating stirring machine control method based on pattern-recognition that the present invention provides a kind of, includes the following steps: that a. establishes model；B. data are obtained；C. optimal possible outcome is compared；D. optimization control parameter is obtained；E. control parameter is compared；F. control parameter is adjusted.The present invention passes through real-time pattern-recognition and adjusts control parameter, can effectively be adjusted to tealeaves rolling stir-fry process, and the control parameter of tealeaves rolling heating stirring machine is adjusted to most suitable as a result, to greatly promote quality of finished in time.
Description
Technical field
The tealeaves rolling heating stirring machine control method based on pattern-recognition that the present invention relates to a kind of.
Background technique
In the prior art, the control of tealeaves rolling heating stirring machine is artificial setting control parameter mostly, and this mode needs largely
It attempts, and rule of thumb judge to adjust, on the one hand adjustment is not in time easy to cause defect rate high to this mode, on the other hand
It is easy to process the good raw material of quality as more secondary material.
Summary of the invention
In order to solve the above technical problems, the present invention provides a kind of tealeaves rolling heating stirring machine control method based on pattern-recognition,
The tealeaves rolling heating stirring machine control method based on pattern-recognition passes through real-time pattern-recognition and adjusts control parameter, can be effective right
Tealeaves rolling stir-fry process is adjusted, and the control parameter of tealeaves rolling heating stirring machine is adjusted to most suitable as a result, to greatly in time
Promote quality of finished.
The present invention is achieved by the following technical programs.
A kind of tealeaves rolling heating stirring machine control method based on pattern-recognition provided by the invention, includes the following steps:
A. it establishes model: by historical data, establishing odour component → quality grading and control parameter → quality results
Data model, and quality grading database is established to possible odour component under each quality grading；
B. data are obtained: obtaining current tealeaves smell number from the multiple groups gas sensor being arranged in tealeaves rolling heating stirring machine
According to, and attached current control parameter；
C. it compares optimal possible outcome: current tealeaves odor data is carried out with odour component → quality grading data model
Pattern-recognition, and will identify that the quality comparison quality grading database come, judge the highest quality grading most possibly reached；
D. obtain optimization control parameter: according to control parameter → quality results model, inverse operation obtains corresponding to above-mentioned possibility
The control parameter of the highest quality grading reached, control parameter include that speed is fried in the rolling of tealeaves rolling heating stirring machine, temperature is fried in rolling and rolling is fried
Time；
E. it compares control parameter: the current control parameter in control parameter obtained in step d, with step b is carried out pair
Than；
F. it adjusts control parameter: control adjustment being carried out to tealeaves rolling heating stirring machine according to comparing result, and enters step b again,
Until end is turned off manually.
Odour component → quality grading and control parameter → quality results data model are established in the step a, be
It is carried out on computer, and the step of single-chip microcontroller is with after completing is written into established data model.
The data model of the odour component → quality grading is by the BP neural network algorithm of three hidden layers by 5 instructions
Practice and establishes.
The control parameter → quality results model is polynary once linear equation.
The beneficial effects of the present invention are: pass through real-time pattern-recognition and adjusts control parameter, it can be effectively to tealeaves
Rolling stir-fry process is adjusted, and the control parameter of tealeaves rolling heating stirring machine is adjusted to most suitable as a result, to greatly be promoted in time
Quality of finished.
Detailed description of the invention
Fig. 1 is flow diagram of the invention.
Specific embodiment
Be described further below technical solution of the present invention, but claimed range be not limited to it is described.
A kind of tealeaves rolling heating stirring machine control method based on pattern-recognition as shown in Figure 1, includes the following steps:
A. it establishes model: by historical data, establishing odour component → quality grading and control parameter → quality results
Data model, and quality grading database is established to possible odour component under each quality grading；
B. data are obtained: obtaining current tealeaves smell number from the multiple groups gas sensor being arranged in tealeaves rolling heating stirring machine
According to, and attached current control parameter；
C. it compares optimal possible outcome: current tealeaves odor data is carried out with odour component → quality grading data model
Pattern-recognition, and will identify that the quality comparison quality grading database come, judge the highest quality grading most possibly reached；
D. obtain optimization control parameter: according to control parameter → quality results model, inverse operation obtains corresponding to above-mentioned possibility
The control parameter of the highest quality grading reached, control parameter include that speed is fried in the rolling of tealeaves rolling heating stirring machine, temperature is fried in rolling and rolling is fried
Time；
E. it compares control parameter: the current control parameter in control parameter obtained in step d, with step b is carried out pair
Than；
F. it adjusts control parameter: control adjustment being carried out to tealeaves rolling heating stirring machine according to comparing result, and enters step b again,
Until end is turned off manually.
As a result, by the pattern-recognition of gas data, and recognition result is compared, to be carried out timely to control
Optimization finally can quickly and effectively be adjusted tealeaves rolling stir-fry process.
Odour component → quality grading and control parameter → quality results data model are established in the step a, be
It is carried out on computer, and the step of single-chip microcontroller is with after completing is written into established data model.
The data model of the odour component → quality grading is by the BP neural network algorithm of three hidden layers by 5 instructions
Practice and establishes.
The control parameter → quality results model is polynary once linear equation.
Claims (4)
1. a kind of tealeaves rolling heating stirring machine control method based on pattern-recognition, characterized by the following steps:
A. it establishes model: by historical data, establishing odour component → quality grading control parameter → quality results data
Model, and quality grading database is established to possible odour component under each quality grading；
B. data are obtained: obtaining current tealeaves odor data from the multiple groups gas sensor being arranged in tealeaves rolling heating stirring machine, and
Attached current control parameter；
C. it compares optimal possible outcome: mode is carried out with odour component → quality grading data model to current tealeaves odor data
Identification, and will identify that the quality comparison quality grading database come, judge the highest quality grading most possibly reached；
D. obtain optimization control parameter: according to control parameter → quality results data model of quality grading, inverse operation is obtained
The control parameter of the corresponding above-mentioned highest quality grading being likely to be breached, control parameter include that speed, rolling are fried in the rolling of tealeaves rolling heating stirring machine
It fries temperature and the time is fried in rolling；
E. it compares control parameter: the current control parameter in control parameter obtained in step d, with step b is compared；
F. it adjusts control parameter: control adjustment being carried out to tealeaves rolling heating stirring machine according to comparing result, and enters step b again, until
End is turned off manually.
2. the tealeaves rolling heating stirring machine control method based on pattern-recognition as described in claim 1, it is characterised in that: the step a
It is middle to establish odour component → quality grading control parameter → quality results data model, it is to carry out on computers, and will build
The step of data model write-in single-chip microcontroller stood is with after completing.
3. the tealeaves rolling heating stirring machine control method based on pattern-recognition as described in claim 1, it is characterised in that: the smell at
Point → data model of quality grading established by the BP neural network algorithm of three hidden layers by 5 training.
4. the tealeaves rolling heating stirring machine control method based on pattern-recognition as described in claim 1, it is characterised in that: the quality point
Control parameter → quality results data model of grade is polynary once linear equation.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201610716271.6A CN106325154B (en) | 2016-08-24 | 2016-08-24 | A kind of tealeaves rolling heating stirring machine control method based on pattern-recognition |
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| CN201610716271.6A CN106325154B (en) | 2016-08-24 | 2016-08-24 | A kind of tealeaves rolling heating stirring machine control method based on pattern-recognition |
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| CN106325154A CN106325154A (en) | 2017-01-11 |
| CN106325154B true CN106325154B (en) | 2018-12-11 |
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| CN110609523B (en) * | 2019-07-18 | 2021-01-05 | 浙江工业大学 | Cooperative control method for units in primary tea leaf making process |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101419166A (en) * | 2008-11-18 | 2009-04-29 | 江苏大学 | Tea quality nondestructive detecting method and device based on near-infrared spectrum and machine vision technology |
| CN102722201A (en) * | 2012-06-29 | 2012-10-10 | 重庆大学 | Automatic baking monitoring system and method |
| CN202956625U (en) * | 2012-11-27 | 2013-05-29 | 王思远 | Automatic control system of tea frying machine |
| CN103487558A (en) * | 2013-07-30 | 2014-01-01 | 中国标准化研究院 | Detection method for abnormal samples in mode identification and analysis of tea quality through intelligent sensory signals |
| CN204305975U (en) * | 2014-09-24 | 2015-05-06 | 新昌县博驰电子有限公司 | Automatic tea frying machine control system |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001327249A (en) * | 2000-05-19 | 2001-11-27 | Kagoshima Prefecture | Method for evaluating tea leaf and system therefor |
-
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- 2016-08-24 CN CN201610716271.6A patent/CN106325154B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101419166A (en) * | 2008-11-18 | 2009-04-29 | 江苏大学 | Tea quality nondestructive detecting method and device based on near-infrared spectrum and machine vision technology |
| CN102722201A (en) * | 2012-06-29 | 2012-10-10 | 重庆大学 | Automatic baking monitoring system and method |
| CN202956625U (en) * | 2012-11-27 | 2013-05-29 | 王思远 | Automatic control system of tea frying machine |
| CN103487558A (en) * | 2013-07-30 | 2014-01-01 | 中国标准化研究院 | Detection method for abnormal samples in mode identification and analysis of tea quality through intelligent sensory signals |
| CN204305975U (en) * | 2014-09-24 | 2015-05-06 | 新昌县博驰电子有限公司 | Automatic tea frying machine control system |
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