CN109287687A - A kind of intelligent apparatus for baking and method based on deep learning - Google Patents
A kind of intelligent apparatus for baking and method based on deep learning Download PDFInfo
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- CN109287687A CN109287687A CN201811146213.XA CN201811146213A CN109287687A CN 109287687 A CN109287687 A CN 109287687A CN 201811146213 A CN201811146213 A CN 201811146213A CN 109287687 A CN109287687 A CN 109287687A
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- A—HUMAN NECESSITIES
- A21—BAKING; EDIBLE DOUGHS
- A21B—BAKERS' OVENS; MACHINES OR EQUIPMENT FOR BAKING
- A21B1/00—Bakers' ovens
- A21B1/02—Bakers' ovens characterised by the heating arrangements
- A21B1/24—Ovens heated by media flowing therethrough
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- A—HUMAN NECESSITIES
- A21—BAKING; EDIBLE DOUGHS
- A21B—BAKERS' OVENS; MACHINES OR EQUIPMENT FOR BAKING
- A21B3/00—Parts or accessories of ovens
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- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Food Science & Technology (AREA)
- Baking, Grill, Roasting (AREA)
Abstract
The invention discloses intelligent baking method and device based on deep learning, the intelligent baking method includes by the information analysis of feedback module feedback, learns, and generates baking curve, and then according to baking curve, control mechanical movement module is toasted；Intelligent apparatus for baking includes central processing module, deep learning module, mechanical movement module, feedback module, deep learning module generates baking curve according to the information that feedback module is fed back, and central processing module is then toasted according to baking curve controlled mechanical movement module；Different baking curves is obtained according to different baking food materials, is toasted according to baking curve, to make a kind of baking system that the baked food to various food production various tastes can be completed.
Description
Technical field
The present invention relates to food materials production field, especially a kind of intelligent apparatus for baking and method based on deep learning.
Background technique
Currently, roasting plant in the market, only merely provides the temperature of baking, food is baked, to obtain beauty
The baked food of taste then needs veteran cook's manpower overturning food materials to be baked.There are also smart baking devices
According to the program that central processing unit is set, intelligent rotating food materials adjust the operation of roasting plant, save manpower, but can only be simple
The baked food of single taste and style is made, the requirement of multifarious food materials production and multiple tastes cannot be reached.
Summary of the invention
To solve the above problems, the purpose of the present invention is to provide intelligent baking methods and dress based on deep learning
It sets, completes the baking of various food and the requirement of baked food multiple tastes.
Technical solution used by the present invention solves the problems, such as it is:
According to the first aspect of the invention, a kind of intelligent apparatus for baking based on deep learning, including central processing module,
Deep learning module, mechanical movement module and feedback module, the deep learning module, mechanical movement module and feedback module point
It is not connect with central processing module；The deep learning module, information analysis, deep learning for feeding back feedback module,
And generate baking curve；The central processing module, the baking curve for being obtained according to deep learning module control mechanical fortune
Dynamic model block is toasted.
Further, the mechanical movement module includes turning mechanical arm module, bright eruption module, oxygen and Fuel equalization tune
Save module, the turning mechanical arm module, bright eruption module and oxygen and Fuel equalization adjustment module respectively with central processing mould
Block connection；The turning mechanical arm module, for according to baking curve adjustment baking position and direction；The bright eruption module is used
Food materials are toasted in spraying bluster according to baking curve；The oxygen and Fuel equalization adjustment module, for dynamic according to baking curve
State is adjusted into oxygen pressure and fuel allotment speed.
In addition, a kind of intelligent apparatus for baking based on deep learning further includes data assistance module, the data
Assistance module is connect with central processing module, for store the data of feedback module and generate data packet in real time with central processing mould
Block swaps.
Further, a kind of intelligent apparatus for baking based on deep learning further include servo power supply module, electric leakage it is short
Road protective module and fume purifying module；Servo power supply module is connect with central processing module, leak electricity short-circuit protective module with watch
Power module connection is taken, fume purifying module is connect with central processing module.
According to the second aspect of the invention, a kind of intelligent baking method based on deep learning, includes the following steps, will be anti-
Information analysis, the deep learning of module feedback are presented, and generates baking curve；According to baking curve, control mechanical movement module into
Row baking.
Further, a kind of intelligent baking method based on deep learning further includes being dried according to baking curve adjustment
Roasting position and direction；Speed is deployed into oxygen pressure and fuel according to baking curve dynamic regulation.
In addition, a kind of intelligent baking method based on deep learning is further comprising the steps of, feedback module is stored
Data and generate data packet and swapped in real time with central processing module.
The beneficial effects of the present invention are: the intelligent baking method and device provided by the invention based on deep learning, root
Different baking curves is obtained according to different baking food materials, then according to baking curve controlled device operational mode, to obtain
The various tastes of different baked foods make a kind of baking system that the baking food to various food production various tastes can be completed
Product；Baking can be automatically completed simultaneously, save human cost.
Detailed description of the invention
The invention will be further described with example with reference to the accompanying drawing.
Fig. 1 is a kind of flow chart of the first embodiment of the intelligent baking method based on deep learning of the present invention；
Fig. 2 is a kind of flow chart of the second embodiment of the intelligent baking method based on deep learning of the present invention；
Fig. 3 is a kind of structure chart of the intelligent apparatus for baking based on deep learning of the present invention.
Specific embodiment
Referring to Figures 1 and 2, one embodiment of the present of invention, in step a1, primary data is obtained: be first obtain it is a large amount of
About baking food data, the time of roasting food, angle, firepower are recorded according to mechanical movement module 3, will be dried
Roasting obtained food gives customer's test-meal, allows customer to score, assigns to 1 point from 0, and score is higher, and the mouthfeel taste that represents is better, thus
To data form.Then according to data form, the two of them amount of time, angle, firepower is quantified, another amount work becomes
Amount, does abscissa with variable, does ordinate with score, obtain a series of initial baking curve.
Model optimization: in deep learning module 2, input layer is arranged: output layer: 3 roasting mode of mechanical movement module is commented
Divide score；By 3 roasting mode of mechanical movement module (i.e. by feedback module 4 feed back obtain baking time, angle, firepower these
Data) it is used as input layer, according to initial baking curve, according to deepness belief network (DBNs) algorithm, (specific algorithm can refer to ginseng
Examine the method in document: Hinton, G.E., Osindero, S.and Teh, Y.W.A fast learning algorithm
For deep belief nets.Neural Computation, vol18, pp.1527-1554,2006), it exports as scoring
Score carries out largely training to initial baking curve and optimizes, and optimizes to intermediate weighting parameters and perfect (such as right
The hidden layer for forming N number of limited Boltzmann machine of entire depth belief network chooses sigmoid activation primitive, is dissipated by comparing
Degree algorithm and gibbs sampler update model parameter to every layer of hidden layer successive ignition pre-training, and then obtain parameter preferably
Deepness belief network model, and add one layer of softmax to return again on the deepness belief network model after pre-training, to entire net
Network is reversely finely tuned) it obtains finally toasting curve；The processing of period, data are completed by central processing module 1, while data are assisted
It helps module 5 to store the data of feedback module 4 and generate data packet and pass through central processing module 1 in real time to swap, shares center
The pressure of the processing data of processing module 1.According to the different available different baking curves of food materials.
In step a2, baking production: the final baking curve that central processing module 1 is obtained according to deep learning module 2, control
Mechanical movement module 3 processed toasts food；Regulate and control turning mechanical arm module 31 according to the baking comprehensive adjustment of curve closed loop
Position and direction are toasted, regulation bright eruption module 32 toasts food materials according to baking curve, and effective thermal energy is crucial used in food materials
Property part, regulate and control oxygen and Fuel equalization adjustment module 33 according to baking curve dynamic regulation and deploy speed into oxygen pressure and fuel
Degree regulates and controls baking time, angle, firepower with this respectively.It can be completed according to different baking curves and various food carried out
The baking of diversified flavor.
Referring to Fig. 3, another embodiment, a kind of intelligent apparatus for baking based on deep learning, including central processing module
1, deep learning module 2, mechanical movement module 3, feedback module 4, deep learning module 2, mechanical movement module 3, feedback module 4
It is connect respectively with central processing module 1；Deep learning module 2, information analysis, deep learning for feeding back feedback module 4,
And generate baking curve；Central processing module 1, the baking curve for being obtained according to deep learning module 2 control mechanical movement
Module 3 is toasted.
Further, the mechanical movement module 3 includes turning mechanical arm module 31, bright eruption module 32, oxygen and fuel
Well-balanced adjustment module 33；Turning mechanical arm module 31, for toasting position and direction according to the comprehensive adjustment of baking curve closed loop；
Effective thermal energy for toasting food materials according to baking curve, and is used in the key position of food materials by bright eruption module 32；Oxygen and combustion
Well-balanced adjustment module 33 is expected, for deploying speed into oxygen pressure and fuel according to baking curve dynamic regulation.
In addition, the intelligent apparatus for baking based on deep learning further includes data assistance module 5, data assistance module
5 connect with central processing module 1, for store the data of feedback module 4 and generate data packet in real time with central processing module 1 into
Row exchange.
Further, the intelligent apparatus for baking based on deep learning further includes servo power supply module 6, leak electricity short-circuit guarantor
Protect module 7 and fume purifying module 8；Servo power supply module 6 is connect with central processing module 1, leak electricity short-circuit protective module 7 with watch
The connection of power module 6 is taken, fume purifying module 8 is connect with central processing module 1.Round-the-clock servo power supply, according to system firepower
Demand real-time dynamicly adjust output power of power supply.When considering Operation at full power, if overload or electric leakage occurs, leak electricity short
Road protective module 7 can be with automatic cutting in emergency power supply.Fume purifying module 8 uses novel environment friendly self-circulation purifying scheme, baking
The oil smoke generated in the process is then exhausted from outside equipment after equipment internal compression and purification, reduces air pollution.
The above, only presently preferred embodiments of the present invention, the invention is not limited to above embodiment, as long as
It reaches technical effect of the invention with identical means, all should belong to protection scope of the present invention.
Claims (8)
1. a kind of intelligent apparatus for baking based on deep learning, it is characterised in that: including central processing module (1), deep learning
Module (2), mechanical movement module (3) and feedback module (4), the deep learning module (2), mechanical movement module (3) and anti-
Feedback module (4) is connect with central processing module (1) respectively；
The deep learning module (2), information analysis, deep learning for feeding back feedback module (4), and it is bent to generate baking
Line；
The central processing module (1), the baking curve for being obtained according to deep learning module (2), controls mechanical movement mould
Block (3) is toasted.
2. the intelligent apparatus for baking according to claim 1 based on deep learning, which is characterized in that the mechanical movement
Module (3) includes turning mechanical arm module (31), bright eruption module (32), oxygen and Fuel equalization adjustment module (33), described to turn over
Turn mechanical arm module (31), bright eruption module (32) and oxygen and Fuel equalization adjustment module (33) respectively with central processing module
(1) it connects；
The turning mechanical arm module (31), for according to baking curve adjustment baking position and direction；
The bright eruption module (32) toasts food materials for spraying bluster according to baking curve；
The oxygen and Fuel equalization adjustment module (33), for being deployed according to baking curve dynamic regulation into oxygen pressure and fuel
Speed.
3. according to claim 1 or 2 described in any item intelligent apparatus for baking based on deep learning, which is characterized in that also wrap
It includes data assistance module (5), the data assistance module (5) connect with central processing module (1), for storing feedback module
(4) data simultaneously generate data packet and swap in real time with central processing module (1).
4. the intelligent apparatus for baking according to claim 3 based on deep learning, which is characterized in that further include servo power supply
Module (6) and leak electricity short-circuit protective module (7)；The servo power supply module (6) connect with central processing module (1), the leakage
Electric short circuit protective module (7) is connect with servo power supply module (6).
5. the intelligent apparatus for baking according to claim 3 based on deep learning, which is characterized in that further include fume purifying
Module (8), the fume purifying module (8) connect with central processing module (1).
6. a kind of intelligent baking method based on deep learning, which comprises the following steps:
By the information analysis of feedback module (4) feedback, deep learning, and generate baking curve；
According to baking curve, control mechanical movement module (3) is toasted.
7. the intelligent baking method according to claim 6 based on deep learning, which is characterized in that further include following step
It is rapid:
According to baking curve adjustment baking position and direction；
Speed is deployed into oxygen pressure and fuel according to baking curve dynamic regulation.
8. the described in any item intelligent baking methods based on deep learning of according to claim 6 or 7, which is characterized in that also wrap
Include following steps:
It stores the data of feedback module (4) and generates data packet and swapped in real time with central processing module (1).
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| CN201811146213.XA CN109287687B (en) | 2018-09-29 | 2018-09-29 | Intelligent baking device and method based on deep learning |
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| CN201811146213.XA CN109287687B (en) | 2018-09-29 | 2018-09-29 | Intelligent baking device and method based on deep learning |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112835299A (en) * | 2020-12-31 | 2021-05-25 | 重庆电子工程职业学院 | Intelligent baking control system based on deep learning |
| CN113780112A (en) * | 2021-08-25 | 2021-12-10 | 横店集团东磁有限公司 | Feedback system and method for monitoring baking state of oven food in real time |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4162381A (en) * | 1977-08-30 | 1979-07-24 | Litton Systems, Inc. | Microwave oven sensing system |
| US5681496A (en) * | 1994-09-07 | 1997-10-28 | Sharp Kabushiki Kaisha | Apparatus for and method of controlling a microwave oven and a microwave oven controlled thereby |
| CN1494853A (en) * | 2002-05-31 | 2004-05-12 | 刘小勇 | Automatic cooking machine and its control system |
| CN102058012A (en) * | 2010-11-03 | 2011-05-18 | 广东海洋大学 | Oyster sapidity peptide controllable enzymolysis process based on optimization of nerve network system |
| CN102539326A (en) * | 2012-01-13 | 2012-07-04 | 江苏大学 | Method for carrying out quantitative evaluation on soup hue quality of tea |
| CN105573114A (en) * | 2015-12-30 | 2016-05-11 | 北京小焙科技有限公司 | Electric oven and double-end intelligent control method thereof |
| CN106304453A (en) * | 2016-08-01 | 2017-01-04 | 广东美的厨房电器制造有限公司 | Heat foods control method, equipment and comprise the cooking apparatus of this equipment |
| CN106579532A (en) * | 2017-01-17 | 2017-04-26 | 重庆电子工程职业学院 | Method for online generating tobacco leaf curing process curve for bulk curing barn |
| CN108006721A (en) * | 2017-11-29 | 2018-05-08 | 广东美的厨房电器制造有限公司 | Control the method and cooking apparatus of cooking apparatus |
| CN108490784A (en) * | 2018-04-19 | 2018-09-04 | 云南佳叶现代农业发展有限公司 | Tobacco flue-curing curve based on intensified learning recommends method |
| CN108509601A (en) * | 2018-04-02 | 2018-09-07 | 中山大学 | A kind of flavour of food products assessment method based on big data analysis |
-
2018
- 2018-09-29 CN CN201811146213.XA patent/CN109287687B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4162381A (en) * | 1977-08-30 | 1979-07-24 | Litton Systems, Inc. | Microwave oven sensing system |
| US5681496A (en) * | 1994-09-07 | 1997-10-28 | Sharp Kabushiki Kaisha | Apparatus for and method of controlling a microwave oven and a microwave oven controlled thereby |
| CN1494853A (en) * | 2002-05-31 | 2004-05-12 | 刘小勇 | Automatic cooking machine and its control system |
| CN102058012A (en) * | 2010-11-03 | 2011-05-18 | 广东海洋大学 | Oyster sapidity peptide controllable enzymolysis process based on optimization of nerve network system |
| CN102539326A (en) * | 2012-01-13 | 2012-07-04 | 江苏大学 | Method for carrying out quantitative evaluation on soup hue quality of tea |
| CN105573114A (en) * | 2015-12-30 | 2016-05-11 | 北京小焙科技有限公司 | Electric oven and double-end intelligent control method thereof |
| CN106304453A (en) * | 2016-08-01 | 2017-01-04 | 广东美的厨房电器制造有限公司 | Heat foods control method, equipment and comprise the cooking apparatus of this equipment |
| CN106579532A (en) * | 2017-01-17 | 2017-04-26 | 重庆电子工程职业学院 | Method for online generating tobacco leaf curing process curve for bulk curing barn |
| CN108006721A (en) * | 2017-11-29 | 2018-05-08 | 广东美的厨房电器制造有限公司 | Control the method and cooking apparatus of cooking apparatus |
| CN108509601A (en) * | 2018-04-02 | 2018-09-07 | 中山大学 | A kind of flavour of food products assessment method based on big data analysis |
| CN108490784A (en) * | 2018-04-19 | 2018-09-04 | 云南佳叶现代农业发展有限公司 | Tobacco flue-curing curve based on intensified learning recommends method |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112835299A (en) * | 2020-12-31 | 2021-05-25 | 重庆电子工程职业学院 | Intelligent baking control system based on deep learning |
| CN112835299B (en) * | 2020-12-31 | 2022-11-08 | 重庆电子工程职业学院 | Intelligent baking control system based on deep learning |
| CN113780112A (en) * | 2021-08-25 | 2021-12-10 | 横店集团东磁有限公司 | Feedback system and method for monitoring baking state of oven food in real time |
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|---|---|
| CN109287687B (en) | 2021-04-13 |
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Effective date of registration: 20210629 Address after: 528400 No.3, building 2, 191 Boai 7th Road, Torch Development Zone, Zhongshan City, Guangdong Province Patentee after: Guangdong Titan Intelligent Power Co.,Ltd. Address before: On the south side of Zhuhai Avenue in Guangdong city of Zhuhai province Jinwan District 519090 Patentee before: GUANGDONG INSTITUTE OF SCIENCE & TECHNOLOGY |
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