CN110597329A - Big data-based environment monitoring system for tea substitute beverage processing workshop - Google Patents
Big data-based environment monitoring system for tea substitute beverage processing workshop Download PDFInfo
- Publication number
- CN110597329A CN110597329A CN201910918346.2A CN201910918346A CN110597329A CN 110597329 A CN110597329 A CN 110597329A CN 201910918346 A CN201910918346 A CN 201910918346A CN 110597329 A CN110597329 A CN 110597329A
- Authority
- CN
- China
- Prior art keywords
- data
- equipment
- temperature
- workshop
- tea substitute
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- 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
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Tea And Coffee (AREA)
Abstract
The invention discloses an environment monitoring system of a tea substitute beverage processing workshop based on big data, which comprises a monitoring module, a processor, an analysis module, a judgment module, a database, an alarm unit and intelligent equipment, wherein the monitoring module is used for monitoring the spatial information of the processing workshop, the quality data of the tea substitute beverage, the processing time data of the tea substitute beverage and the environment safety information, the spatial information comprises the temperature data in the workshop and the humidity data in the workshop, the invention analyzes the temperature, the humidity and the air flow data in different workshops through the arrangement of the analysis module, judges the influence of the temperature, the humidity and the air flow data on the processing time of the tea substitute beverage, obtains a calculation formula, further obtains the regulation standards of the temperature, the humidity and the air flow data in the workshop at different times, and increases the time grasp of the tea substitute beverage, the observation time of the staff is saved, and the working efficiency is improved.
Description
Technical Field
The invention relates to the technical field of tea substitute beverage processing, in particular to an environment monitoring system for a tea substitute beverage processing workshop based on big data.
Background
The chrysanthemum tea is a herbal tea prepared from chrysanthemum. The chrysanthemum tea is prepared by the procedures of fresh flower picking, shade drying, sun drying, steaming and sun drying, baking and the like. According to ancient books, chrysanthemum is sweet and bitter in taste, cold-resistant in nature, and has the effects of dispelling wind and clearing heat, clearing liver and improving vision, detoxifying and diminishing inflammation and the like. The chrysanthemum tea originates from the Tang dynasty and the Zhiqing dynasty and is widely applied to the life of people.
The processing technology of the American ginseng black tea drink, which is disclosed in the prior patent application publication No. CN107397009A, can enhance the functions of a central nervous system, protect a cardiovascular system, improve immunity, promote blood activity, treat diabetes, tonify lung, reduce pathogenic fire, nourish stomach and promote fluid production, but the processing technology of the American ginseng black tea drink cannot accurately control the processing time of tea substitute drinks under different temperatures, humidity and flow speed control during processing, and has the problem of inconvenient processing of processing equipment under the condition of unstable electric power.
Disclosure of Invention
The invention aims to provide a tea substitute beverage based on big data, which is characterized in that an analysis module is used for analyzing temperature data in a workshop, humidity data in the workshop, air flow data and tea substitute beverage quality data in the workshop, tea substitute beverage processing time data, equipment current data, equipment voltage data and equipment temperature data, the time for grasping the tea substitute beverage is increased, so that the production quality of the tea substitute beverage is ensured, and a judgment module is used for judging the relation among the actual processing time Jx of the tea substitute beverage, the equipment current data Bi, the equipment voltage data Di and the equipment temperature data Pi, so that the deviation of the fixed processing time in the workshop is prevented, and the production quality is improved.
The technical problem to be solved by the invention is as follows:
(1) how to analyze temperature, humidity and air flow data in different workshops through the arrangement of an analysis module, judge the influence of the temperature, humidity and air flow data on the processing time of the tea substitute beverage, and obtain a calculation formula, so as to obtain the regulation standard of the temperature, humidity and air flow data in the workshops under different time conditions, and solve the problem that the processing time of the tea substitute beverage is difficult to accurately control under different temperatures, humidities and flow control speeds in the prior art;
(2) how to carry out safety judgment on current and voltage data in a workshop through the setting of a judgment module so as to calculate a power influence coefficient F, calculate the processing time Jx of actual tea substitute beverages under different powers and solve the problem of inconvenient processing under the condition of unstable electric power in the prior art.
The purpose of the invention can be realized by the following technical scheme: a big data-based environment monitoring system for a tea substitute beverage processing workshop is characterized by comprising a monitoring module, a processor, an analysis module, a judgment module, a database, an alarm unit and intelligent equipment;
the monitoring module is used for monitoring space information of a processing workshop, quality data of tea substitute beverages, processing time data of the tea substitute beverages and environment safety information, wherein the space information comprises temperature data in the workshop, humidity data in the workshop and air flow data in the workshop, the environment safety information comprises equipment current data, equipment voltage data and temperature data of equipment, and the monitoring module transmits the monitored temperature data in the workshop, the humidity data in the workshop, the air flow data in the workshop, the quality data of the tea substitute beverages, the processing time data of the tea substitute beverages, the equipment current data, the equipment voltage data and the temperature data of the equipment to the analysis module through the processor;
the analysis module is used for analyzing and operating temperature data in the workshop, humidity data in the workshop, air flow data in the workshop, tea substitute beverage quality data, tea substitute beverage processing time data, equipment current data, equipment voltage data and equipment temperature data to obtain actual processing time Jx ═ j + [ O (Wi-W0) + K × (Si-S0) + M (Li-L0) ] of tea substitute beverages and actual tea substitute beverage quality data Ci ═ c-V ═ Jx-j, and transmitting the actual processing time Jx ═ j + [ O (Wi-W0) + K ═ Si-S0) + M (Li-L0) to the intelligent equipment;
the analysis module transmits equipment current data, equipment voltage data, equipment temperature data and actual processing time of the tea substitute beverage to the judgment module, the database stores equipment standard current range data, equipment standard voltage range data and equipment standard temperature range data, the judgment module obtains the equipment standard current data, the equipment standard voltage data and the equipment standard temperature range data in the database, and the judgment module is used for judging the relationship among the actual processing time of the tea substitute beverage, the equipment current data, the equipment voltage data and the equipment temperature data to obtain a current abnormal signal, a voltage abnormal signal and an equipment temperature abnormal signal and transmitting the current abnormal signal, the voltage abnormal signal and the equipment temperature abnormal signal to the alarm unit;
the alarm unit is used for transmitting the current abnormal signal, the voltage abnormal signal and the equipment temperature abnormal signal to the alarm unit to be converted into a current abnormal alarm, a voltage abnormal alarm and an equipment temperature abnormal alarm, giving an alarm and transmitting the alarm signal to the intelligent equipment.
As a further improvement scheme of the invention, the specific operation process of the analysis operation comprises the following steps:
the method comprises the following steps: acquiring temperature data in a workshop, humidity data in the workshop, air flow data in the workshop, quality data of tea substitute beverages, processing time data of the tea substitute beverages, equipment current data, equipment voltage data and temperature data of equipment, and sequentially marking the temperature data as Wi, Si, Li, Ci, Ji, Bi, Di and Pi, wherein i is 1, 2, 3.
Step two: under the condition that other conditions are not changed, acquiring different workshop temperature data W1 and W2, acquiring corresponding tea substitute beverage processing time data J1 and J2, comparing different workshop temperature data W1 and W2, comparing tea substitute beverage processing time data J1 and J2, and judging according to the comparison result, wherein the method specifically comprises the following steps:
s1: when W1> W2 and J1> J2, the processing time of the tea substitute beverage is judged to be shortened along with the reduction of the temperature; s2: when W1 is W2 and J1 is more than J2, the processing time of the tea substitute beverage is judged not to be changed by the change of the temperature; s3: when W1> W2 and J1< J2, the processing time of the tea substitute beverage is judged to increase along with the reduction of the temperature; s4: when W1< W2, J1> J2, the processing time of the tea substitute beverage is judged to be shortened along with the rise of the temperature; s5: when W1< W2 and J1< J2, the processing time of the tea substitute beverage is judged to increase along with the increase of the temperature;
step three: and obtaining the relation between the humidity data in the workshop and the air flow data in the workshop and the processing time of the tea substitute beverage according to the comparison mode in the second step, wherein the influence relation is divided into five types: replacing the temperature in the second step with the humidity and the air flow to obtain a judgment result;
step four: setting influence coefficients O, K and M corresponding to the temperature data, humidity data and air flow data in the workshop according to the judgment results of the second step and the third step, respectively establishing influence calculation formulas J2-J1 ═ O (W2-W1), J2-J1 ═ K (S2-S1) and J2-J1 ═ M (L2-L1), and calculating the processing time Jx ═ J + [ O (Wi-W0) + K ═ (Si-S0) + M (Li-L0) ] of the actual tea substitute beverage according to the established influence calculation formulas, wherein J is the processing time of the basic tea substitute beverage, W0 is the temperature in the workshop, S0 is the humidity in the workshop, and L0 is the flow value of the basic air;
step five: the method comprises the following steps of obtaining quality data Ci of the substituted tea drinks, setting a preset high-quality value c, and comparing the preset high-quality value c with the actual quality data Ci of the substituted tea drinks, wherein the specific steps are as follows:
b1: when Ci is less than c, judging that the quality of the tea substitute beverage is poor; b2: when Ci is equal to c, judging that the quality of the tea substitute beverage is general; b3: when Ci is greater than c, judging that the quality of the tea substitute beverage is good;
step six: obtaining a calculation formula c-Ci ═ V × (Jx-j) according to the determination result in the B1-B3 and the processing time Jx of the actual tea substitute beverage corresponding to the determination result, wherein V is an influence coefficient;
step seven: and (3) calculating actual Ci-c-V (Jx-j) according to a calculation formula Jx ═ j + [ O (Wi-W0) + K (Si-S0) + M (Li-L0) ] and c-Ci ═ V (Jx-j) obtained in the fourth step and the sixth step, inputting the quality of the produced tea substitute beverage and the required processing time into the calculation formula, calculating and obtaining relevant data such as required temperature, humidity, air flow and the like, and transmitting the data to intelligent equipment.
As a further improvement scheme of the invention, the specific operation process of the judgment operation comprises the following steps:
g1: acquiring standard current range data, standard voltage range data and standard temperature range data of equipment, and sequentially marking the standard current range data, the standard voltage range data and the standard temperature range data as b, d and p;
g2: and sequentially comparing the equipment current data Bi, the equipment voltage data Di, the equipment temperature data Pi with the equipment standard current range data, the equipment standard voltage range data and the equipment standard temperature range data to obtain two conditions: t1: the device current data Bi, the device voltage data Di and the device temperature data Pi all belong to device standard current range data, device standard voltage range data and device standard temperature range data; t2: when the device current data does not belong to the range of the device standard current range data, generating a current abnormal signal, when the device voltage data does not belong to the range of the device standard voltage range data, generating a voltage abnormal signal, when the temperature of the device does not belong to the range of the standard temperature range data, generating a device temperature abnormal signal, and transmitting the current abnormal signal, the voltage abnormal signal and the device temperature abnormal signal to the alarm unit;
g3: obtaining device current data Bi and device voltage data Di to calculate electric power Q to Bi Di, and judging according to the difference value of two different electric powers Q1 and Q2 and the change of the processing time Jx of the actual tea substitute beverage under two times of electric powers, specifically:
when the processing time Jx of the actual tea substitute beverage is not changed under the condition that Q1 and Q2 are different, the processing time Jx of the actual tea substitute beverage is judged not to be influenced by electric power, when the processing time Jx of the actual tea substitute beverage is changed under the condition that Q1 and Q2 are different, the processing time Jx of the actual tea substitute beverage is judged to be influenced by electric power, when the judgment result is influenced, a power influence coefficient F is obtained according to a calculation formula Delta Q F Jx, and the processing time Jx of the actual tea substitute beverage under different power is calculated according to the power influence coefficient F, wherein the Delta Q is the difference value of Q1 and Q2.
The invention has the beneficial effects that:
(1) the monitoring module transmits the monitored temperature data in the workshop, humidity data in the workshop, air flow data in the workshop and quality data of tea-substituted drinks, processing time data of the tea-substituted drinks, equipment current data, equipment voltage data and temperature data of equipment to the analysis module through the processor, the analysis module is used for analyzing the temperature data in the workshop, the humidity data in the workshop, the air flow data in the workshop and quality data of the tea-substituted drinks, processing time data of the tea-substituted drinks, equipment current data, equipment voltage data and temperature data of the equipment, the analysis module is used for analyzing the temperature, humidity and air flow data in different workshops to judge the influence of the temperature, humidity and air flow data on the processing time of the tea-substituted drinks and obtain a calculation formula, so that the temperature, air flow data in the workshop and the quality data of the tea-substituted drinks in different time conditions are required to be processed, The adjustment standards of the humidity and the air flow data increase the time for holding the tea substitute beverage, thereby ensuring the production quality of the tea substitute beverage, reducing deviation, saving the observation time of staff and improving the working efficiency.
(2) The analysis module transmits the device current data Bi, the device voltage data Di, the device temperature data Pi and the actual processing time Jx of the tea substitute beverage to the judgment module, the judgment module acquires the device standard current data, the device standard voltage data and the device standard temperature range data in the database, the judgment module is used for judging the relationship among the actual processing time Jx of the tea substitute beverage, the device current data Bi, the device voltage data Di and the device temperature data Pi, the current and voltage data in the workshop are judged safely through the setting of the judgment module, the production safety of the tea substitute beverage and the workshop safety are guaranteed, the power influence coefficient F is obtained by comparing the time change of the current and the voltage with the processing time of the tea substitute beverage, and the processing time Jx of the actual tea substitute beverage under different powers is calculated by utilizing the power influence coefficient F, the deviation of fixed processing time in a workshop is prevented, so that the quality of the tea substitute beverage is influenced, and the production quality of the tea substitute beverage is improved.
Drawings
The invention will be further described with reference to the accompanying drawings.
FIG. 1 is a system block diagram of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the invention relates to a big data-based environment monitoring system for a tea substitute beverage processing workshop, which comprises a monitoring module, a processor, an analysis module, a judgment module, a database, an alarm unit and intelligent equipment, wherein the monitoring module is used for monitoring the environment of the tea substitute beverage processing workshop;
the monitoring module is used for monitoring spatial information of a processing workshop, quality data of tea-substituted drinks, processing time data of the tea-substituted drinks and environmental safety information, wherein the spatial information comprises temperature data in the workshop, humidity data in the workshop and air flow data in the workshop, the temperature data in the workshop refers to temperature change in the processing workshop, the humidity data in the workshop refers to water vapor contained in air in the processing workshop, the air flow data refers to the movement rate of the air in the processing workshop to a certain fixed place in the processing workshop, namely the air speed, the tea-substituted drink quality data refers to the quality grade of a finished product of the tea-substituted drink, the environmental safety information comprises equipment current data, equipment voltage data and equipment temperature data, and the monitoring module monitors the temperature data in the workshop, the humidity data in the workshop, the air flow data in the workshop and the tea-substituted drink quality data, The processing time data, the equipment current data, the equipment voltage data and the equipment temperature data of the tea substitute beverage are transmitted to the analysis module through the processor;
the analysis module is used for carrying out analysis operation to temperature data in the workshop, humidity data in the workshop, air flow data in the workshop and tea substitute beverage quality data, tea substitute beverage processing time data, equipment current data, equipment voltage data and the temperature data of equipment, specifically do:
the method comprises the following steps: acquiring temperature data in a workshop, humidity data in the workshop, air flow data in the workshop, quality data of tea substitute beverages, processing time data of the tea substitute beverages, equipment current data, equipment voltage data and temperature data of equipment, and sequentially marking the temperature data as Wi, Si, Li, Ci, Ji, Bi, Di and Pi, wherein i is 1, 2, 3.
Step two: under the condition that other conditions are not changed, acquiring different workshop temperature data W1 and W2, acquiring corresponding tea substitute beverage processing time data J1 and J2, comparing different workshop temperature data W1 and W2, comparing tea substitute beverage processing time data J1 and J2, and judging according to the comparison result, wherein the method specifically comprises the following steps:
s1: when W1> W2 and J1> J2, the processing time of the tea substitute beverage is judged to be shortened along with the reduction of the temperature; s2: when W1 is W2 and J1 is more than J2, the processing time of the tea substitute beverage is judged not to be changed by the change of the temperature; s3: when W1> W2 and J1< J2, the processing time of the tea substitute beverage is judged to increase along with the reduction of the temperature; s4: when W1< W2, J1> J2, the processing time of the tea substitute beverage is judged to be shortened along with the rise of the temperature; s5: when W1< W2 and J1< J2, the processing time of the tea substitute beverage is judged to increase along with the increase of the temperature;
step three: and obtaining the relation between the humidity data in the workshop and the air flow data in the workshop and the processing time of the tea substitute beverage according to the comparison mode in the second step, wherein the influence relation is divided into five types: replacing the temperature in the second step with the humidity and the air flow to obtain a judgment result;
step four: setting influence coefficients O, K and M corresponding to the temperature data, humidity data and air flow data in the workshop according to the judgment results of the second step and the third step, respectively establishing influence calculation formulas J2-J1 ═ O (W2-W1), J2-J1 ═ K (S2-S1) and J2-J1 ═ M (L2-L1), and calculating the processing time Jx ═ J + [ O (Wi-W0) + K ═ (Si-S0) + M (Li-L0) ] of the actual tea substitute beverage according to the established influence calculation formulas, wherein J is the processing time of the basic tea substitute beverage, W0 is the temperature in the workshop, S0 is the humidity in the workshop, and L0 is the flow value of the basic air;
step five: the method comprises the following steps of obtaining quality data Ci of the substituted tea drinks, setting a preset high-quality value c, and comparing the preset high-quality value c with the actual quality data Ci of the substituted tea drinks, wherein the specific steps are as follows:
b1: when Ci is less than c, judging that the quality of the tea substitute beverage is poor; b2: when Ci is equal to c, judging that the quality of the tea substitute beverage is general; b3: when Ci is greater than c, judging that the quality of the tea substitute beverage is good;
step six: obtaining a calculation formula c-Ci ═ V × (Jx-j) according to the determination result in the B1-B3 and the processing time Jx of the actual tea substitute beverage corresponding to the determination result, wherein V is an influence coefficient;
step seven: calculating actual Ci-c-V (Jx-j) according to a calculation formula Jx ═ j + [ O (Wi-W0) + K (Si-S0) + M (Li-L0) ] and c-Ci ═ V (Jx-j) obtained in the fourth step and the sixth step, inputting the quality of the produced tea substitute beverage and the required processing time into the calculation formula, calculating and obtaining relevant required data such as temperature, humidity, air flow and the like, and transmitting the data to intelligent equipment;
the analysis module transmits device current data Bi, device voltage data Di, device temperature data Pi and actual processing time Jx of the tea substitute beverage to the judgment module, device standard current range data, device standard voltage range data and device standard temperature range data are stored in the database, the judgment module obtains the device standard current data, the device standard voltage data and the device standard temperature range data in the database, and the judgment module is used for judging the relationship among the actual processing time Jx of the tea substitute beverage, the device current data Bi, the device voltage data Di and the device temperature data Pi and specifically comprises the following steps:
g1: acquiring standard current range data, standard voltage range data and standard temperature range data of equipment, and sequentially marking the standard current range data, the standard voltage range data and the standard temperature range data as b, d and p;
g2: and sequentially comparing the equipment current data Bi, the equipment voltage data Di, the equipment temperature data Pi with the equipment standard current range data, the equipment standard voltage range data and the equipment standard temperature range data to obtain two conditions: t1: the device current data Bi, the device voltage data Di and the device temperature data Pi all belong to device standard current range data, device standard voltage range data and device standard temperature range data; t2: when the device current data does not belong to the range of the device standard current range data, generating a current abnormal signal, when the device voltage data does not belong to the range of the device standard voltage range data, generating a voltage abnormal signal, when the temperature of the device does not belong to the range of the standard temperature range data, generating a device temperature abnormal signal, and transmitting the current abnormal signal, the voltage abnormal signal and the device temperature abnormal signal to the alarm unit;
g3: obtaining device current data Bi and device voltage data Di to calculate electric power Q to Bi Di, and judging according to the difference value of two different electric powers Q1 and Q2 and the change of the processing time Jx of the actual tea substitute beverage under two times of electric powers, specifically:
when the processing time Jx of the actual tea substitute beverage is not changed under the condition that Q1 and Q2 are different, the processing time Jx of the actual tea substitute beverage is judged not to be influenced by electric power, when the processing time Jx of the actual tea substitute beverage is changed under the condition that Q1 and Q2 are different, the processing time Jx of the actual tea substitute beverage is judged to be influenced by electric power, when the judgment result is influenced, a power influence coefficient F is obtained according to a calculation formula Delta Q F Jx, and the processing time Jx of the actual tea substitute beverage under different power is calculated according to the power influence coefficient F, wherein the Delta Q is the difference value of Q1 and Q2;
the alarm unit is used for transmitting the current abnormal signal, the voltage abnormal signal and the equipment temperature abnormal signal to the alarm unit to be converted into a current abnormal alarm, a voltage abnormal alarm and an equipment temperature abnormal alarm, giving an alarm and transmitting the alarm signal to the intelligent equipment.
When the tea substitute beverage processing system works, the monitoring module is used for monitoring spatial information of a processing workshop, quality data of tea substitute beverages, processing time data of the tea substitute beverages and environmental safety information, the spatial information comprises temperature data in the workshop, humidity data in the workshop and air flow data in the workshop, the environmental safety information comprises equipment current data, equipment voltage data and temperature data of equipment, the monitoring module is used for transmitting the monitored temperature data in the workshop, humidity data in the workshop, air flow data in the workshop and tea substitute beverage quality data, tea substitute beverage processing time data, equipment current data, equipment voltage data and equipment temperature data to the analysis module through the processor, and the analysis module is used for transmitting the temperature data in the workshop, the humidity data in the workshop, the air flow data in the workshop and the tea substitute beverage quality data, the tea substitute beverage processing time data, The device current data, the device voltage data and the device temperature data are analyzed, the analysis module transmits the device current data Bi, the device voltage data Di, the device temperature data Pi and the processing time Jx of the actual tea substitute beverage to the judgment module, the standard device current range data, the standard device voltage range data and the standard device temperature range data are stored in the database, the judgment module acquires the standard device current data, the standard device voltage data and the standard device temperature range data in the database, the judgment module is used for judging the relation among the processing time Jx of the actual tea substitute beverage, the device current data Bi, the device voltage data Di and the device temperature data Pi, the alarm unit is used for transmitting the current abnormal signal, the voltage abnormal signal and the device temperature abnormal signal to the alarm unit to be converted into a current abnormal alarm, The voltage anomaly alarm and the device temperature anomaly alarm are transmitted to the intelligent device.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (3)
1. A big data-based environment monitoring system for a tea substitute beverage processing workshop is characterized by comprising a monitoring module, a processor, an analysis module, a judgment module, a database, an alarm unit and intelligent equipment;
the monitoring module is used for monitoring space information of a processing workshop, quality data of tea substitute beverages, processing time data of the tea substitute beverages and environment safety information, wherein the space information comprises temperature data in the workshop, humidity data in the workshop and air flow data in the workshop, the environment safety information comprises equipment current data, equipment voltage data and temperature data of equipment, and the monitoring module transmits the monitored temperature data in the workshop, the humidity data in the workshop, the air flow data in the workshop, the quality data of the tea substitute beverages, the processing time data of the tea substitute beverages, the equipment current data, the equipment voltage data and the temperature data of the equipment to the analysis module through the processor;
the analysis module is used for analyzing and operating temperature data in the workshop, humidity data in the workshop, air flow data in the workshop, tea substitute beverage quality data, tea substitute beverage processing time data, equipment current data, equipment voltage data and equipment temperature data to obtain actual processing time Jx ═ j + [ O (Wi-W0) + K × (Si-S0) + M (Li-L0) ] of tea substitute beverages and actual tea substitute beverage quality data Ci ═ c-V ═ Jx-j, and transmitting the actual processing time Jx ═ j + [ O (Wi-W0) + K ═ Si-S0) + M (Li-L0) to the intelligent equipment;
the analysis module transmits equipment current data, equipment voltage data, equipment temperature data and actual processing time of the tea substitute beverage to the judgment module, the database stores equipment standard current range data, equipment standard voltage range data and equipment standard temperature range data, the judgment module obtains the equipment standard current data, the equipment standard voltage data and the equipment standard temperature range data in the database, and the judgment module is used for judging the relationship among the actual processing time of the tea substitute beverage, the equipment current data, the equipment voltage data and the equipment temperature data to obtain a current abnormal signal, a voltage abnormal signal and an equipment temperature abnormal signal and transmitting the current abnormal signal, the voltage abnormal signal and the equipment temperature abnormal signal to the alarm unit;
the alarm unit is used for transmitting the current abnormal signal, the voltage abnormal signal and the equipment temperature abnormal signal to the alarm unit to be converted into a current abnormal alarm, a voltage abnormal alarm and an equipment temperature abnormal alarm, giving an alarm and transmitting the alarm signal to the intelligent equipment.
2. The big data based environment monitoring system for tea substitute beverage processing plant according to claim 1, wherein the specific operation process of the analysis operation is as follows:
the method comprises the following steps: acquiring temperature data in a workshop, humidity data in the workshop, air flow data in the workshop, quality data of tea substitute beverages, processing time data of the tea substitute beverages, equipment current data, equipment voltage data and temperature data of equipment, and sequentially marking the temperature data as Wi, Si, Li, Ci, Ji, Bi, Di and Pi, wherein i is 1, 2, 3.
Step two: under the condition that other conditions are not changed, acquiring different workshop temperature data W1 and W2, acquiring corresponding tea substitute beverage processing time data J1 and J2, comparing different workshop temperature data W1 and W2, comparing tea substitute beverage processing time data J1 and J2, and judging according to the comparison result, wherein the method specifically comprises the following steps:
s1: when W1> W2 and J1> J2, the processing time of the tea substitute beverage is judged to be shortened along with the reduction of the temperature; s2: when W1 is W2 and J1 is more than J2, the processing time of the tea substitute beverage is judged not to be changed by the change of the temperature; s3: when W1> W2 and J1< J2, the processing time of the tea substitute beverage is judged to increase along with the reduction of the temperature; s4: when W1< W2, J1> J2, the processing time of the tea substitute beverage is judged to be shortened along with the rise of the temperature; s5: when W1< W2 and J1< J2, the processing time of the tea substitute beverage is judged to increase along with the increase of the temperature;
step three: and obtaining the relation between the humidity data in the workshop and the air flow data in the workshop and the processing time of the tea substitute beverage according to the comparison mode in the second step, wherein the influence relation is divided into five types: replacing the temperature in the second step with the humidity and the air flow to obtain a judgment result;
step four: setting influence coefficients O, K and M corresponding to the temperature data, humidity data and air flow data in the workshop according to the judgment results of the second step and the third step, respectively establishing influence calculation formulas J2-J1 ═ O (W2-W1), J2-J1 ═ K (S2-S1) and J2-J1 ═ M (L2-L1), and calculating the processing time Jx ═ J + [ O (Wi-W0) + K ═ (Si-S0) + M (Li-L0) ] of the actual tea substitute beverage according to the established influence calculation formulas, wherein J is the processing time of the basic tea substitute beverage, W0 is the temperature in the workshop, S0 is the humidity in the workshop, and L0 is the flow value of the basic air;
step five: the method comprises the following steps of obtaining quality data Ci of the substituted tea drinks, setting a preset high-quality value c, and comparing the preset high-quality value c with the actual quality data Ci of the substituted tea drinks, wherein the specific steps are as follows:
b1: when Ci is less than c, judging that the quality of the tea substitute beverage is poor; b2: when Ci is equal to c, judging that the quality of the tea substitute beverage is general; b3: when Ci is greater than c, judging that the quality of the tea substitute beverage is good;
step six: obtaining a calculation formula c-Ci ═ V × (Jx-j) according to the determination result in the B1-B3 and the processing time Jx of the actual tea substitute beverage corresponding to the determination result, wherein V is an influence coefficient;
step seven: and (3) calculating actual Ci-c-V (Jx-j) according to a calculation formula Jx ═ j + [ O (Wi-W0) + K (Si-S0) + M (Li-L0) ] and c-Ci ═ V (Jx-j) obtained in the fourth step and the sixth step, inputting the quality of the produced tea substitute beverage and the required processing time into the calculation formula, calculating and obtaining relevant data such as required temperature, humidity, air flow and the like, and transmitting the data to intelligent equipment.
3. The system for monitoring the environment of the tea substitute beverage processing workshop based on the big data according to claim 1, wherein the specific operation process of the judgment operation is as follows:
g1: acquiring standard current range data, standard voltage range data and standard temperature range data of equipment, and sequentially marking the standard current range data, the standard voltage range data and the standard temperature range data as b, d and p;
g2: and sequentially comparing the equipment current data Bi, the equipment voltage data Di, the equipment temperature data Pi with the equipment standard current range data, the equipment standard voltage range data and the equipment standard temperature range data to obtain two conditions: t1: the device current data Bi, the device voltage data Di and the device temperature data Pi all belong to device standard current range data, device standard voltage range data and device standard temperature range data; t2: when the device current data does not belong to the range of the device standard current range data, generating a current abnormal signal, when the device voltage data does not belong to the range of the device standard voltage range data, generating a voltage abnormal signal, when the temperature of the device does not belong to the range of the standard temperature range data, generating a device temperature abnormal signal, and transmitting the current abnormal signal, the voltage abnormal signal and the device temperature abnormal signal to the alarm unit;
g3: obtaining device current data Bi and device voltage data Di to calculate electric power Q to Bi Di, and judging according to the difference value of two different electric powers Q1 and Q2 and the change of the processing time Jx of the actual tea substitute beverage under two times of electric powers, specifically:
when the processing time Jx of the actual tea substitute beverage is not changed under the condition that Q1 and Q2 are different, the processing time Jx of the actual tea substitute beverage is judged not to be influenced by electric power, when the processing time Jx of the actual tea substitute beverage is changed under the condition that Q1 and Q2 are different, the processing time Jx of the actual tea substitute beverage is judged to be influenced by electric power, when the judgment result is influenced, a power influence coefficient F is obtained according to a calculation formula Delta Q F Jx, and the processing time Jx of the actual tea substitute beverage under different power is calculated according to the power influence coefficient F, wherein the Delta Q is the difference value of Q1 and Q2.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910918346.2A CN110597329B (en) | 2019-09-26 | 2019-09-26 | Big data-based environment monitoring system for tea substitute beverage processing workshop |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910918346.2A CN110597329B (en) | 2019-09-26 | 2019-09-26 | Big data-based environment monitoring system for tea substitute beverage processing workshop |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110597329A true CN110597329A (en) | 2019-12-20 |
| CN110597329B CN110597329B (en) | 2021-10-08 |
Family
ID=68863998
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910918346.2A Active CN110597329B (en) | 2019-09-26 | 2019-09-26 | Big data-based environment monitoring system for tea substitute beverage processing workshop |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110597329B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117148764A (en) * | 2023-09-09 | 2023-12-01 | 广州临广电气机械有限公司 | Intelligent Internet of things type vehicle-mounted control system and method based on man-machine interaction |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104714532A (en) * | 2015-03-10 | 2015-06-17 | 杭州掌企科技有限公司 | Quality control method and device |
| CN105759764A (en) * | 2016-04-08 | 2016-07-13 | 浙江中烟工业有限责任公司 | Cigarette production technological parameter control system and control method therefor |
| WO2017185156A1 (en) * | 2016-04-26 | 2017-11-02 | Palacios Barrasús José Ignácio | Automated system for pasteurising food and eliminating pathogens, and automated assembly to provide dry saturated steam during pelletisation |
| CN108147647A (en) * | 2017-11-22 | 2018-06-12 | 彩虹显示器件股份有限公司 | A kind of method for heating and controlling for glass-melting furnace |
| KR20190014628A (en) * | 2017-08-03 | 2019-02-13 | 동국대학교 산학협력단 | Bigdata based temperature management assessment method and system |
-
2019
- 2019-09-26 CN CN201910918346.2A patent/CN110597329B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104714532A (en) * | 2015-03-10 | 2015-06-17 | 杭州掌企科技有限公司 | Quality control method and device |
| CN105759764A (en) * | 2016-04-08 | 2016-07-13 | 浙江中烟工业有限责任公司 | Cigarette production technological parameter control system and control method therefor |
| WO2017185156A1 (en) * | 2016-04-26 | 2017-11-02 | Palacios Barrasús José Ignácio | Automated system for pasteurising food and eliminating pathogens, and automated assembly to provide dry saturated steam during pelletisation |
| KR20190014628A (en) * | 2017-08-03 | 2019-02-13 | 동국대학교 산학협력단 | Bigdata based temperature management assessment method and system |
| CN108147647A (en) * | 2017-11-22 | 2018-06-12 | 彩虹显示器件股份有限公司 | A kind of method for heating and controlling for glass-melting furnace |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117148764A (en) * | 2023-09-09 | 2023-12-01 | 广州临广电气机械有限公司 | Intelligent Internet of things type vehicle-mounted control system and method based on man-machine interaction |
| CN117148764B (en) * | 2023-09-09 | 2024-03-15 | 广州临广电气机械有限公司 | Intelligent Internet of things type vehicle-mounted control system and method based on man-machine interaction |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110597329B (en) | 2021-10-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110597329B (en) | Big data-based environment monitoring system for tea substitute beverage processing workshop | |
| CN116258431A (en) | Cold chain transportation safety remote monitoring system based on internet | |
| CN107893173A (en) | Special-shaped copper alloy wire processing technology | |
| CN114135477B (en) | Dynamic threshold early warning method for monitoring state of machine pump equipment | |
| CN110421408A (en) | A kind of monitoring method of cutting-tool wear state | |
| CN117223807B (en) | Preparation method of tomato fruit and vegetable beverage rich in lycopene | |
| CN117668734B (en) | Intelligent cutting head temperature monitoring method | |
| CN106483847A (en) | A kind of handpiece Water Chilling Units fault detection method based on self adaptation ICA | |
| CN113534727B (en) | Early warning control system of refrigeration equipment for fishing boat based on artificial intelligence platform | |
| CN117441843B (en) | Preparation method of pulp type composite vegetable fermented beverage | |
| Umme et al. | Characteristics of soursop natural puree and determination of optimum conditions for pasteurization | |
| CN108445854B (en) | A kind of workshop autonomous learning method in the intelligent workshop based on big data | |
| KR102140625B1 (en) | Vegan cheese by saccharification of germination sorghum and yeast fermentation and method thereof | |
| CN104814413A (en) | Method for producing black garlic | |
| CN112307415A (en) | Online detection method for abnormal data values of digital education recording and broadcasting system | |
| CN109021123A (en) | A kind of preparation method of banana starch | |
| CN110814080A (en) | PF line heat preservation device and method for improving scale peeling performance | |
| CN103330162A (en) | Preparation method of sweet and sour asparagus can | |
| CN113568383B (en) | Non-invasive identification method suitable for machining center | |
| KR20090025396A (en) | Method for manufacturing concentrated solution of sweet drink made from fermented rice | |
| CN113554854B (en) | Enameled equipment stall alarm system | |
| CN102960429A (en) | Steam precooking production method of canned food | |
| CN116777178B (en) | Quality control method for fruit and vegetable juice production | |
| CN101878939B (en) | Process for producing concentrated strawberry clear juice | |
| CN116009501A (en) | Primary pulp production machine management and control system based on data analysis |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |