AU2020100379A4 - Intelligent Food Liquid Fermentation Parameter Control Method - Google Patents

Intelligent Food Liquid Fermentation Parameter Control Method Download PDF

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AU2020100379A4
AU2020100379A4 AU2020100379A AU2020100379A AU2020100379A4 AU 2020100379 A4 AU2020100379 A4 AU 2020100379A4 AU 2020100379 A AU2020100379 A AU 2020100379A AU 2020100379 A AU2020100379 A AU 2020100379A AU 2020100379 A4 AU2020100379 A4 AU 2020100379A4
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temperature
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Quansheng Chen
Zhiming GUO
Tianhui JIAO
Huanhuan LI
Hao Lin
Qin Ouyang
Ancheng WANG
Bing Wang
Yi Xu
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Jiangsu University
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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
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
    • G05B13/0275—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using fuzzy logic only
    • A—HUMAN NECESSITIES
    • A23—FOODS OR FOODSTUFFS; TREATMENT THEREOF, NOT COVERED BY OTHER CLASSES
    • A23F—COFFEE; TEA; THEIR SUBSTITUTES; MANUFACTURE, PREPARATION, OR INFUSION THEREOF
    • A23F3/00—Tea; Tea substitutes; Preparations thereof
    • A23F3/16—Tea extraction; Tea extracts; Treating tea extract; Making instant tea
    • A23F3/166—Addition of, or treatment with, enzymes or microorganisms
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q3/00—Condition responsive control processes
    • 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
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
    • 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
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/048—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators using a predictor
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D27/00—Simultaneous control of variables covered by two or more of main groups G05D1/00 - G05D25/00
    • G05D27/02—Simultaneous control of variables covered by two or more of main groups G05D1/00 - G05D25/00 characterised by the use of electric means
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D21/00—Control of chemical or physico-chemical variables, e.g. pH value
    • G05D21/02—Control of chemical or physico-chemical variables, e.g. pH value characterised by the use of electric means
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D23/00—Control of temperature
    • G05D23/19—Control of temperature characterised by the use of electric means

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Abstract

Abstract The present invention is to provide a multivariable fermentation control method and system based on fuzzy control, which may replace the fermentation parameter control method in the current food liquid fermentation production, and realize the liquid food fermentation control based on a fuzzy theory, thus solving the failure of accurate control to the objects to be controlled caused by the non-linear, strong coupling, time varying, lagging and other characteristics in the fermentation control process of food currently. Drawings Improved fuzzy control system Polyphenol content Parameter probability Fuzzy computing Markov approach System output ColorEuclideandistance coupling and reasoning decoupling S Summer/Autumn tea Temperature, Ph, DO, Actuator fermentation liquor dissolved oxven Fig.1 55, color -, 0 1 4 duofe. Fig.2

Description

Description
Intelligent Food Liquid Fermentation Parameter Control Method
Technical Field
The present invention relates to the field of fermentation control, and in particular to a method and a system for controlling various input/output parameters during fermentation process.
Background Art
The fermentation technology is applied in the fields of food, medicine, chemical industry and the like, and particularly in the food industry. The fermented food has a very large consumption group, promoting the development of a huge fermented food industry; food itself is a complex system, therefore, during the production of the fermented food, the control of the various production conditions of the complex system is always a challenge recognized within and beyond the industry.
Fuzzy Control, derived from Fuzzy Theory, is a kind of a computer numerical control technology based on fuzzy set theory, fuzzy reasoning, and fuzzy variable, and belongs to a category of intelligent bionic control, and it is essentially a non-linear control. Fuzzy Control has extensive application foundation in common control systems, and has many advantages, such as wide adaptability, independent of a specific model, fast parameter feedback speed, accurate control. However, in actual use, single-variable input/output fuzzy control is mainly adopted, which can not meet the demand of complex parameter control in food industry.
Summary of the Invention
The fermentation system includes a fermentation tank, a control executor, a control system and a sensor system; the fermentation tank is combined with a sensor, and the sensor system includes a temperature sensor, a pH sensor and a visible/near infrared spectrum (NIR) sensor; the control executor includes a stirring motor, a temperature control module and an acid-base pump; the control system includes a master control computer and a PLC;
the sensor is connected with the PLC, and the PLC acquires data of the sensor; the PLC is connected with the master control computer, the master control computer sends an instruction to
2020100379 12 Mar 2020 the PLC, and the PLC is connected with the control executor to achieve the action control of the control executor directly; the master control computer receives the data of the sensor, then processes the data via a fuzzy control system to obtain control parameters, and then transmits the control parameters to the PLC; the executor is directly connected with the fermentation tank, thus controlling the production conditions in the fermentation tank.
Furthermore, a construction method of the fuzzy control system includes the following steps of:
acquiring two or more key status values of the fermentation liquor, and taking the values as an input value Xk of the fuzzy control system; obtaining key production control parameters in the fermentation process according to production experience and experiments, and taking the key production control parameters as an output value Yk of the fuzzy control system;
formulating a Fuzzy Control Table, fuzzifying the input value Xk of the fuzzy control system, and then deblurring the Xk through a fuzzy membership function to obtain an accurate output value Yk for production adjustment;
the present invention designs a fuzzy control model for food liquid fermentation, including:
a parameter input section, used for receiving key fermentation state parameters measured by a detection device, including content, color, viscosity, turbidity and the like of some key components, substituting the above input variables into Fuzzy Control Table and mapping into an input domain to obtain fuzzy values of the input parameters;
a parameter processing section, used for performing fuzzy reasoning and decision on the fuzzy values of the input variables to obtain fuzzy quantity corresponding to output values;
a parameter output section, used for deblurring the fuzzy quantity of control parameters obtained by the parameter processing section to obtain a control output quantity, presenting the control output quantity to an executing and operating mechanism for actual control, and it mainly includes
2020100379 12 Mar 2020 temperature control of the fermentation tank, stirring speed control, ventilatory capacity control and pH control;
based upon the above technical solution, the present invention designs an improved fuzzy control method; a plurality of fermentation states serve as input quantity and a plurality of control parameters serve as output quantity for defuzzification fuzzy and decoupling through fuzzification and Markov approach, thus achieving the accurate control of fermentation parameters and quality; and a closed-loop multivariable fuzzy control method and system is further disclosed in the present invention, thereby achieving energy conservation and emission reduction as well as 10 improvement of product quality.
The invention has the following beneficial effects:
(1) an improved multivariable input/output control system based on fuzzy control is combined 15 with Markov model for deblurring and decoupling output parameters, which may real-timely and accurately control the simultaneous control of multiple fermentation variables under complex food liquid fermentation conditions, thus achieving energy conservation and emission reduction;
(2) reasonable multivariable fuzzy control rules are constructed in combination with fermentation 20 control data provided by an experienced operator, thus achieving more accurate control of fermentation variables;
Brief Description of the Drawings
FIG. 1 shows a control flow chart of a fermentation fuzzy system of a tea extract liquor.
FIG.2 shows a surface of fuzzy control rule on fermentation temperature parameters of the tea extract liquor.
FIG.3 shows a flow chart of the intelligent food liquid fermentation control system.
Detailed Description of the Invention
2020100379 12 Mar 2020
The fermentation system includes a fermentation tank, a control executor, a control system and a sensor system; the fermentation tank is combined with a sensor, and the sensor system includes a temperature sensor, a pH sensor and a visible/near infrared spectrum (NIR) sensor; the control executor includes a stirring motor, a temperature control module and an acid-base pump; the 5 control system includes a master control computer and a PLC;
In the embodiment, a fermentation fuzzy control system of a tea extract liquor based on fuzzy control is designed, mainly including the following steps of:, the main steps include:
step 1, acquiring polyphenol content and color information of fermentation liquor in the oxidative fermentation process of summer/autumn tea;
step 2, taking the polyphenol content and color information as input factors of fuzzy reasoning, and taking the oxidative fermentation temperature of summer/autumn tea, PH of the fermentation liquor, dissolved oxygen DO of the fermentation liquor and stirring speed of the fermentation liquor as output factors of the fuzzy reasoning; constructing a fuzzy control system;
step 3, determining a variable universe of the input/output factor of the fuzzy control system;
step 4, formulating a fuzzy division and membership function of the input/output factor;
step 5, formulating an input/output parameter probability coupling rule and a fuzzy control table;
step 6, fuzzy reasoning and decoupling by a Markov approach;
step 7, taking four output factors in the oxidative fermentation process of the summer/autumn tea as control parameters, inputting the control parameters into an actuator, and respectively adjusting a heating device, an acid-base pump for changing the pH value of the fermentation liquor, an air pump for changing the dissolved oxygen of the fermentation liquor and a stirring motor for 30 changing the stirring speed of the fermentation liquor in the actuator. Further description: in FIG. 1,
2020100379 12 Mar 2020 denotes two key parameters, polyphenol content and color values of the tea extract liquor received by the system; 2 denotes the fuzzy control system and the system construction process; 3 denotes coupling steps of the parameter probability of an improved fuzzy control system; 4 denotes fuzzy calculation reasoning; 5 denotes decoupling steps of output parameters by Markov approach; 6 denotes output control parameters for the system; 7 denotes an extract liquor of the control object-summer/autumn tea; 8 denotes an actuator of fermentation parameters (temperature, pH, dissolved oxygen, rotating speed); 9 denotes control parameter-temperature, pH, dissolved oxygen and rotating speed of actual output of the improved fuzzy control system;
major steps of establishing the improved fuzzy control system are as follows:
step 1: determining a variable universe of the input/output factor;
step II: formulating a fuzzy division and membership function of the input/output factor;
step III: formulating a parameter probability coupling rule and a fuzzy control table;
step IV: fuzzy reasoning and decoupling by a Markov approach.
The specific steps are as follows:
step I: determining a variable universe of the input/output factor;
the fuzzy reasoning system detects the polyphenol content and color of the fermentation liquor during the oxidative fermentation process of the summer/autumn tea for once every 2 min; and it can be seen from the accumulated experimental data that the polyphenol content varies from 1.4 to 2.1 and, Euclidean distance of the color ranges from 0 to 15.6. The system includes four output factors, and the range of the output factors are as follows: temperature: 25-70°C; pH: 6.0-8.0; DO: 0-100; rotating speed: 20-300.
2020100379 12 Mar 2020
Variable universe of input/output variables
hiput/Out put factor Input factor Output factor
Polyphenol Euclidean distance of color Temperature rc PH DO/% Rotating speed/r· min-1
Minimum 1.4 0 25 6.0 0 20
Maximum 2.1 15.6 70 8.0 100 300
step II: formulating a fuzzy division and membership function of the input/output factor;
The selection of membership function has a great influence on the performance of the fuzzy reasoning system. A triangle membership function is selected in the system, and the fuzzy division table of the input/output factor is as follows
Fuzzy set division of polyphenol
Left endpoint Top end Right endpoint
Very low (VL) 1.4 1.4 1.5
Low (LOW) 1.5 1.6 1.7
Rather low (RL) 1.6 1.7 1.8
Medium (MED) 1.7 1.8 1.9
Rather high (RH) 1.8 1.9 2.0
High (H) 1.9 2.0 2.1
Very high (VH) 2.0 2.1 2.1
Fuzzy set table of the input parameter-color Euclidean distance is as follows:
Fuzzy set division of the color Euclidean distance
Left endpoint Top end Right
endpoint
Medium (MED) 0 2 2
Relatively medium (RM) 0 2 4
A little high (LH) 2 4 6
Rather high (RH) 4 6 8
High (H) 6 8 10
Very high (VH) 8 12 15
Fuzzy set table of the output parameter-temperature:
Fuzzy set table of temperature
Left endpoint Top end Right endpoint
Minimum temperature 25 25 34
(MINT)
Lower temperature (LT) 25 34 43
Medium temperature 34 43 52
(MT)
Higher temperature (PT) 43 52 61
Maximum temperature 52 61 70
(MAXT)
Fuzzy set division rule of the output parameter pH is as follows:
Fuzzy set division of pH
Left endpoint Top end Right endpoint
Minimum pH (MINpH) 6.0 6.0 6.5
Low pH(LpH) 6.0 6.5 7.0
Medium pH(MpH) 6.5 7.0. 7,5
A little alkali (PpH) 7.0 7.5 8.0
Maximum pH(MAXpH) 7.5 8.0 8.0
Fuzzy set division rule of the output value DO is as follows:
Fuzzy set division of the DO value
Left endpoint Top end Right endpoint
Minimum DO(MINDO) 0 0 25
Lower DO(LDO) 0 25 50
Medium DO(MDO) 25 50 70
Higher DO(PDO) 50 75 100
Maximum DO(MAXDO) 75 100 100
Fuzzy set division rule of the output value-rotating speed is as follows:
Fuzzy set division of the rotating speed
Left endpoint Top end Right endpoint
Minimum speed(MINS) 20 20 67
Low speed(LS) 20 67 114
Lower speed(RS) 67 114 161
Medium speed (MS) 114 161 208
Higher speed (PS) 161 208 255
High speed(HS) 208 255 300
Maximum Speed (MAXS) 255 300 300
step III: formulating a parameter probability coupling rule and a fuzzy control table;
The fuzzy decision-making system designed in the system is a double-input and four-output fuzzy reasoning system, which is divided into a fuzzy reasoning system with four double-input and single-output, respectively corresponding to four output factors, namely, temperature, pH, DO and rotating speed. The polyphenol content is divided into 7 linguistic variables, the color is divided into 6 linguistic variables, and the output factor is divided into 5 and 7 linguistic variables. Under the guidance of experienced production experts and combined with long-term production experience, fuzzy control rules are formulated reasonably.
Fuzzy strategy control table of temperature:
Fuzzy strategy control table of temperature
Polyphe nol Color
MED RM LH RH H VH
VL MINT MINT LT MT PT PT
LOW MINT MINT LT MT PT PT
RL MINT MINT LT MT PT PT
MED MINT MINT LT MT PT PT
RH MT MT MT MT PT MAXT
HIGH PT PT MT PT MAXT MAXT
VH PT PT PT MAXT MAXT MAXT
Fuzzy strategy table of pH
Fuzzy strategy table of pH
Color
Polyphenol MED RM LH RH H VH
VL MAXpH MAXpH MAXpH MAXpH MAXpH MAXpH
LOW MAXpH MAXpH MAXpH MAXpH MAXpH MAXpH
2020100379 12 Mar 2020
RL MAXpH MAXpH LpH MpH PpH PpH
MED MAXpH MAXpH LpH MpH PpH PpH
RH MpH MpH MpH MpH PpH MINpH
HIGH PpH PpH MpH PpH MINpH MINpH
VH PpH PpH PpH MINpH MINpH MINpH
Fuzzy strategy table of DO
Fuzzy strategy table of DO
Polyphenol Color
MED RM LH RH H VH
VL MINDO MINDO LDO MDO PDO PDO
LOW MINDO MINDO LDO MDO PDO PDO
RL MINDO MINDO LDO MDO PDO PDO
MED MINDO MINDO LDO MDO PDO PDO
RH MDO MDO MDO MDO PDO MAXDO
HIGH PDO PDO MDO PDO MAXDO MAXDO
VH PDO PDO PDO MAXDO MAXDO MAXDO
Fuzzy strategy table of rotating speed
Fuzzy strategy table of rotating speed
Color
Polyphenol MED RM LH RH H VH
VL MINS MINS LS MS PS PS
LOW MINS MINS LS MS PS PS
RL MINS MINS LS MS PS PS
MED MINS MINS LS MS PS PS
RH MS MS MS MS PS MAXS
HfGH PS PS MS PS MAXS MAXS
VH PS PS PS MAXS MAXS MAXS
step IV: fuzzy reasoning and decoupling by a Markov approach.
The fuzzy reasoning and Markov approach decoupling model is constituted below:
the weight of each parameter combination model is calculated for the acquired polyphenol content and color information of the fermentation liquor, as well as the fermentation temperature, pH value, the dissolved oxygen DO and the stirring speed of the fermentation liquor to be output to a control mechanism, and multiple models are taken as an observation sequence; and a forward factor at(i) is used and initialized, al(i)=7tibi(Yl), where 1 < i < N, Y1 denotes the probability of timing sequence at an initial moment; the weight is continuously calculated by a recursion method for gradual recursion from the forward and back at+1(j)=Eat(i)aij]bj(Yt+1), where l<t<T-l, l<j<N, and at is the probability of the observation sequence at time t. bj is the probability of the observation sequence in a given Markov model; and finally a fuzzy control surface is formed, as shown in the F1G.2: surface of fuzzy control rule on fermentation temperature parameters of the tea extract liquor.
The fuzzy controher of the embodiment processes the detection 2 input variables input by a detector into fuzzy control quantity by a fuzzy control method according to a fuzzy theory, and controls the object to be controlled according to four control output quantity after deblurred, which overcomes the problems of zero unified mathematical model and inaccurate control caused by nonlinear, strong coupling, time varying and lagging characteristics in the existing control process, thus making the control process more accurate and achieving a better control effect.

Claims (11)

  1. Claims
    1. An intelligent food liquid fermentation parameter control method, characterized by comprising the following steps of:
    step 1, acquiring polyphenol content and color information of fermentation liquor in the oxidative fermentation process of summer/autumn tea;
    step 2, taking the polyphenol content and color information as input factors of fuzzy reasoning, and taking the oxidative fermentation temperature of summer/autumn tea, PH of the fermentation liquor, dissolved oxygen DO of the fermentation liquor and rotating speed of the fermentation liquor as output factors of the fuzzy reasoning; constructing a fuzzy control system;
    step 3, determining a variable universe of the input/output factor of the fuzzy control system;
    step 4, formulating a fuzzy division and membership function of the input/output factor;
    step 5, formulating an input/output parameter probability coupling rule and a fuzzy control table;
    step 6, fuzzy reasoning and decoupling by a Markov approach;
    step 7, taking four output factors in the oxidative fermentation process of the summer/autumn tea as control parameters, inputting the control parameters into an actuator, and respectively adjusting a heating device, an acid-base pump for changing the pH value of the fermentation liquor, an air pump for changing the dissolved oxygen of the fermentation liquor and a stirring motor for changing the stirring speed of the fermentation liquor in the actuator.
  2. 2. The intelligent food liquid fermentation parameter control method according to claim 1,
    2020100379 12 Mar 2020 characterized in that the fuzzy control system is an improved two-input and four-output fuzzy control system.
  3. 3. The intelligent food liquid fermentation parameter control method according to claim 1, 5 characterized in that in step 3, the variable universe of the input/output factor is: the polyphenol content varies from 1.
  4. 4 to 2.1, the color Euclidean distance ranges from 0 to 15.6, and the temperature ranges from 25°C to 70°C; pH: 6.0-8.0; DO: 0-100; the rotating speed of stirring: 20 -300.
    10 4. The intelligent food liquid fermentation parameter control method according to claim 1, characterized in that the membership function is selected as: a triangle segmentation membership function.
  5. 5. The intelligent food liquid fermentation parameter control method according to claim 1, 15 characterized in that fuzzy set division rule of the polyphenol content is as follows, respectively:
    very low VLe(1.4,1.5); low LOWE(1.5,1.
  6. 6)U(1.6,1.
  7. 7); rather low RLe (1.6,1.7) U (1.7,1.
  8. 8); medium MEDe(1.7,1.8)U(1.8,1.
  9. 9); rather high RHE(1.8,1.9)U(1.9,2.0); high He(1.9,2.0)U (2.0,2.1); very high VH e (2.0,2.1);
    20 fuzzy set division rule of the fermentation liquor's color value is as follows, respectively medium MEDE(0,2); relatively medium RMe(0,2)U(2,4); slightly higher LHG(2,4)U(4,6); rather high RHE (4,6) U (6,8); high He (6,8) U (8,10); very high VHE (8,12) U (12,15);
    25 temperature fuzzy sets are divided as the following rules, respectively:
    minimum temperature MINT e (25,34); lower temperature LT e (25,34) U (34,43); medium temperature MT e (34,43) U (43,52); higher temperature PT e (43,52) U (52,61); maximum temperature MAXT e (52,61) U (61,70);
    2020100379 12 Mar 2020 fuzzy set division rule of the fermentation liquor pH is as follows, respectively:
    minimum pH MINpHe (6.0,6.5): low pH LpHG (6.0,6.5) U (6.5,7.0): medium pH MpHG (6.5,7.0)
    U (7.0,7.5): a little alkali PpH G (7.0,7.5) U (7.5,8.0): maximum pH MAXpH G (7.5,8.0):
    fuzzy set division rule of the dissolved oxygen DO of the fermentation liquor is as follows, respectively:
    minimum DO MINDO G (0,25); lower DO LDOG (0,25) U (25,50); medium DO MDOG (25,50)
  10. 10 U (50,70); higher DO PDOG (50,75) U (75,100); maximum DO MAXDO G (75,100);
    fuzzy set division rule of the stirring speed of the fermentation liquor is as follows, respectively:
    minimum speed MINS G (20,67); low speed LSG (20,67) U (67,114); lower speed RS G (67,114) U
  11. 15 (114,161); medium speed MSG(114,161)U(161,208); relatively higher speed PSG(161,208)U (208,255); high speed HS G (208,255) U (255,300); maximum speed MAXS G (355,300);
AU2020100379A 2020-03-12 2020-03-12 Intelligent Food Liquid Fermentation Parameter Control Method Ceased AU2020100379A4 (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116520919A (en) * 2023-05-08 2023-08-01 安徽农业大学 Temperature and humidity decoupling control method of yellow tea processing equipment
CN117441843A (en) * 2023-12-26 2024-01-26 山东农圣恒昌农业科技有限公司 Preparation method of pulp type composite vegetable fermented beverage

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116520919A (en) * 2023-05-08 2023-08-01 安徽农业大学 Temperature and humidity decoupling control method of yellow tea processing equipment
CN116520919B (en) * 2023-05-08 2024-05-14 安徽农业大学 Temperature and humidity decoupling control method of yellow tea processing equipment
CN117441843A (en) * 2023-12-26 2024-01-26 山东农圣恒昌农业科技有限公司 Preparation method of pulp type composite vegetable fermented beverage
CN117441843B (en) * 2023-12-26 2024-03-19 山东农圣恒昌农业科技有限公司 Preparation method of pulp type composite vegetable fermented beverage

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