CN114265458A - Method for realizing accurate control of air pipe temperature and humidity and room temperature and humidity - Google Patents
Method for realizing accurate control of air pipe temperature and humidity and room temperature and humidity Download PDFInfo
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Abstract
The invention discloses a method for accurately controlling the temperature and humidity of an air pipe and the temperature and humidity in a room; the method comprises the steps that a high-precision temperature and humidity sensor is arranged in a controlled object and a controlled environment, the sensor avoids signal transmission interference, 4-20 mA signals are adopted, a shielding cable is used for transmitting signals, a PLC analog input and output module is configured through a PLC controller, the temperature and humidity of the environment of the controlled object are monitored, and the monitored temperature and humidity are used as hardware facilities for data acquisition; configuring a computer for data storage and a data analysis unit, installing an upper computer software system in the computer, reading data acquired in the PLC through the upper computer software system, and storing the data to be collected in an SQL database through industrial configuration software such as Siemens winc, ifix and the like; in computers responsible for storing and analyzing data, the data stored in SQL is analyzed using python scripts.
Description
Technical Field
The invention relates to the field of high-precision temperature and humidity automatic control of factory clean room environment, in particular to a method for realizing accurate control of air pipe temperature and humidity and room temperature and humidity by utilizing an artificial intelligent neural network learning algorithm.
Background
At present, the environment condition of high-precision equipment is strict, the high-precision equipment is very dependent on the environment temperature and humidity, part of the equipment is required to be constant temperature and humidity, the environment temperature precision is required to be less than +/-0.1 ℃ or even 0.05 ℃, the humidity is +/-1 percent, and the equipment is particularly laboratory equipment. If the traditional FMCS is used, PID (proportional integral derivative) control is generally adopted, the stability of a controlled object is very dependent on the setting of PID parameters, the setting of the PID parameters is closely related to the characteristics of an actuator actuating mechanism, and the control parameter cannot be widely used in every environment, so that the fixed control parameter which can adapt to the temperature of the changing environment does not exist. And once the control balance is damaged, a long time is needed for recovering stability due to disturbance caused by external environment fluctuation, so that the control precision cannot realize higher-precision control.
Disclosure of Invention
Therefore, in order to solve the above disadvantages, the present invention provides a method for accurately controlling the temperature and humidity of an air duct and the temperature and humidity in a room by using an artificial intelligent neural network learning algorithm; the high-precision temperature and humidity automatic control system is applied to the factory clean room environment.
The invention is realized in such a way that a method for realizing accurate control of the temperature and humidity of the air pipe and the temperature and humidity in the room is constructed, and the method is characterized in that; the method comprises the steps that a high-precision temperature and humidity sensor is arranged in a controlled object and a controlled environment, the sensor avoids signal transmission interference, 4-20 mA signals are adopted, a shielding cable is used for transmitting signals, a PLC analog input and output module is configured through a PLC controller, the temperature and humidity of the environment of the controlled object are monitored, and the monitored temperature and humidity are used as hardware facilities for data acquisition; configuring a computer for data storage and a data analysis unit, installing an upper computer software system in the computer, reading data acquired in the PLC through the upper computer software system, and storing the data to be collected in an SQL database through industrial configuration software such as Siemens winc, ifix and the like; analyzing the data stored in SQL by using python script in a computer responsible for storing and analyzing the data, calculating the output parameter of the actuator by using the functional relation obtained by machine learning, storing the parameter into SQL, returning the obtained result to PLC by using industrial configuration software, and enabling the PLC to execute the instruction; the specific operation is as follows:
(1) data transmission: transmitting the real-time measured value of each sensor and the real-time opening value of the actuating mechanism to a PLC module through a 4-20 mA signal;
(2) data acquisition: firstly, determining field data to be collected, and considering the influence of each data on the whole system loop; at present, the data collected by a field sensor are considered as the temperature and humidity \ moisture content, dew point and enthalpy of the outdoor environment, the temperature and humidity, moisture content, dew point and enthalpy of an air supply section of an air conditioning unit, the temperature and humidity, moisture content, dew point and enthalpy of each level of coil pipes of an air conditioner, the temperature and humidity, the dew point and enthalpy of the rear humidifier, the temperature and humidity in a controlled room, and the dew point, enthalpy and moisture content;
(3) data storage: writing each data into an SQL database in a matrix form through a storage interface of each configuration software according to a standard table, wherein the data to be stored is a data ID, a data name, a data value and data acquisition time;
(4) data reading: reading an SQL database through an open function in python, or connecting a connect in a pandas resource library with a current computer database, reading data in the database by using a read _ SQL function, and sorting the data in the database into a matrix, wherein a first column of the matrix is time, and other column names are values of the data mentioned in the second step which are arranged according to the time;
(5) analyzing data;
(6) and (3) parameter storage: storing the conclusion in the data analysis into an SQL database through a python function;
(7) reading parameters: calling a database in real time through configuration software, and transmitting parameters stored in SQL into an industrial configuration software channel;
(8) parameter feedback: transmitting the SQL parameter values read by the configuration software to a PLC controller through the real-time communication between the configuration software and the PLC;
(9) performing parameters: and issuing the parameter information acquired from the PLC to each execution mechanism through a 4-20 mA control signal, and executing the command through the execution mechanisms.
The method for accurately controlling the temperature and the humidity of the air pipe and the temperature and the humidity in the room is characterized by comprising the following steps of (1) accurately controlling the temperature and the humidity of the air pipe and the temperature and the humidity in the room; in the step (3), the data is stored once in a time period of 10S or 5S.
The method for accurately controlling the temperature and the humidity of the air pipe and the temperature and the humidity in the room is characterized by comprising the following steps of (1) accurately controlling the temperature and the humidity of the air pipe and the temperature and the humidity in the room; the specific operation of the data analysis in the step (5) is as follows:
firstly, adding the following actuator values (adding five columns) in five periods in a matrix on the basis of data reading;
index column 1: whether the current temperature is within the deviation range allowed by the system is 1 within the deviation range and 0 is not within the deviation range;
index column 2: whether the current humidity is within the deviation range allowed by the system is 1 within the deviation range and 0 is not within the deviation range;
in the second step, all the parameter lists are normalized, i.e. the value of the data is the current value of the data/(the maximum value of all the values of the data-the minimum value of all the values) to ensure that all the data values are in the range of 0-1
Thirdly, performing single-row linear regression fitting processing on uncontrolled variables such as environment change parameters (outdoor environment temperature and humidity) to obtain a fitting function, calculating a value of the next period through the fitting function, continuously correcting the function equation through machine learning, and reducing comprehensive errors;
fourthly, obtaining a layer convolutional layer which enables the temperature and the humidity to meet the system requirements, namely the temperature and the humidity to be in a fluctuation range by using a neural network algorithm through a neural network tree;
and fifthly, substituting the environmental variables calculated in the third step and other parameter variables acquired in a real-time period into the convolutional layer to obtain the control parameters of each actuating mechanism at the moment.
The invention has the following advantages: the invention provides a method for realizing accurate control of air pipe temperature and humidity and room temperature and humidity by using an artificial intelligent neural network learning algorithm; the high-precision temperature and humidity automatic control system is applied to the factory clean room environment. The integrated circuit and the liquid crystal panel display which have high precision requirements on environmental variables are realized through a novel algorithm, and industrial production factory systems such as electronic, biopharmaceutical, food, medical apparatus and the like, process cooling water systems, data centers, civil building air conditioners and heating systems are realized. The existing automatic control system usually adopts the traditional PID algorithm for regulation, and has the phenomena of untimely regulation, large fluctuation range of regulated variables and generally low regulation precision for serious environment variables with lag. By introducing an AI learning algorithm, big data analysis is carried out on historical data to obtain an environment variable model, the seasonal variation trend of the environment is learned to obtain the control logic of a predictive execution mechanism, the prediction and compensation of the environment temperature and humidity are realized by using an advanced adjusting mode, and finally, the control with higher precision is realized. Through early algorithm development, unmanned management is achieved, and the method can be widely applied to high-precision control of multiple projects through a machine learning mode.
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FIG. 1 is a schematic representation of an embodiment of the present invention;
FIG. 2 is a schematic flow chart of the present invention.
Detailed Description
The present invention will be described in detail with reference to fig. 1-2, and the technical solutions in the embodiments of the present invention will be clearly and completely described, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all 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.
The invention provides a method for realizing accurate control of air pipe temperature and humidity and room temperature and humidity by improving an artificial intelligent neural network learning algorithm, which is applied to a factory clean room environment high-accuracy temperature and humidity automatic control system.
The invention is realized in such a way that a method for realizing accurate control of the temperature and humidity of the air pipe and the temperature and humidity in the room is constructed, and the method is characterized in that; the method comprises the steps that a high-precision temperature and humidity sensor is arranged in a controlled object and a controlled environment, the sensor avoids signal transmission interference, 4-20 mA signals are adopted, a shielding cable is used for transmitting signals, a PLC analog input and output module is configured through a PLC controller, the temperature and humidity of the environment of the controlled object are monitored, and the monitored temperature and humidity are used as hardware facilities for data acquisition; configuring a computer for data storage and a data analysis unit, installing an upper computer software system in the computer, reading data acquired in the PLC through the upper computer software system, and storing the data to be collected in an SQL database through industrial configuration software such as Siemens winc, ifix and the like; analyzing the data stored in SQL by using python script in a computer responsible for storing and analyzing the data, calculating the output parameter of the actuator by using the functional relation obtained by machine learning, storing the parameter into SQL, returning the obtained result to PLC by using industrial configuration software, and enabling the PLC to execute the instruction; the specific operation is as follows:
(1) data transmission: transmitting the real-time measured value of each sensor and the real-time opening value of the actuating mechanism to a PLC module through a 4-20 mA signal;
(2) data acquisition: firstly, determining field data to be collected, and considering the influence of each data on the whole system loop; at present, the data collected by a field sensor are considered as the temperature and humidity \ moisture content, dew point and enthalpy of the outdoor environment, the temperature and humidity, moisture content, dew point and enthalpy of an air supply section of an air conditioning unit, the temperature and humidity, moisture content, dew point and enthalpy of each level of coil pipes of an air conditioner, the temperature and humidity, the dew point and enthalpy of the rear humidifier, the temperature and humidity in a controlled room, and the dew point, enthalpy and moisture content;
(3) data storage: writing each data into an SQL database in a matrix form through a storage interface of each configuration software according to a standard table, wherein the data to be stored is a data ID, a data name, a data value and data acquisition time; the data storage time period is 10S or 5S;
(4) data reading: reading an SQL database through an open function in python, or connecting a connect in a pandas resource library with a current computer database, reading data in the database by using a read _ SQL function, and sorting the data in the database into a matrix, wherein a first column of the matrix is time, and other column names are values of the data mentioned in the second step which are arranged according to the time;
(5) analyzing data; the specific operation is as follows:
firstly, adding the following actuator values (adding five columns) in five periods in a matrix on the basis of data reading;
index column 1: whether the current temperature is within the deviation range allowed by the system is 1 within the deviation range and 0 is not within the deviation range;
index column 2: whether the current humidity is within the deviation range allowed by the system is 1 within the deviation range and 0 is not within the deviation range;
in the second step, all the parameter lists are normalized, i.e. the value of the data is the current value of the data/(the maximum value of all the values of the data-the minimum value of all the values) to ensure that all the data values are in the range of 0-1
Thirdly, performing single-row linear regression fitting processing on uncontrolled variables such as environment change parameters (outdoor environment temperature and humidity) to obtain a fitting function, calculating a value of the next period through the fitting function, continuously correcting the function equation through machine learning, and reducing comprehensive errors;
fourthly, obtaining a layer convolutional layer which enables the temperature and the humidity to meet the system requirements, namely the temperature and the humidity to be in a fluctuation range by using a neural network algorithm through a neural network tree;
fifthly, substituting the environmental variables calculated in the third step and other parameter variables acquired in a real-time period into the convolutional layer to obtain control parameters of each actuating mechanism at the moment;
(6) and (3) parameter storage: storing the conclusion in the data analysis into an SQL database through a python function;
(7) reading parameters: calling a database in real time through configuration software, and transmitting parameters stored in SQL into an industrial configuration software channel;
(8) parameter feedback: transmitting the SQL parameter values read by the configuration software to a PLC controller through the real-time communication between the configuration software and the PLC;
(9) performing parameters: and issuing the parameter information acquired from the PLC to each execution mechanism through a 4-20 mA control signal, and executing the command through the execution mechanisms.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (3)
1. A method for realizing accurate control of the temperature and humidity of an air duct and the temperature and humidity in a room is characterized in that;
the method comprises the steps that a high-precision temperature and humidity sensor is arranged in a controlled object and a controlled environment, the sensor avoids signal transmission interference, 4-20 mA signals are adopted, a shielding cable is used for transmitting signals, a PLC analog input and output module is configured through a PLC controller, the temperature and humidity of the environment of the controlled object are monitored, and the monitored temperature and humidity are used as hardware facilities for data acquisition; configuring a computer for data storage and a data analysis unit, installing an upper computer software system in the computer, reading data acquired in the PLC through the upper computer software system, and storing the data to be collected in an SQL database through industrial configuration software such as Siemens winc, ifix and the like; analyzing the data stored in SQL by using python script in a computer responsible for storing and analyzing the data, calculating the output parameter of the actuator by using the functional relation obtained by machine learning, storing the parameter into SQL, returning the obtained result to PLC by using industrial configuration software, and enabling the PLC to execute the instruction; the specific operation is as follows:
(1) data transmission: transmitting the real-time measured value of each sensor and the real-time opening value of the actuating mechanism to a PLC module through a 4-20 mA signal;
(2) data acquisition: firstly, determining field data to be collected, and considering the influence of each data on the whole system loop; at present, the data collected by a field sensor are considered as the temperature and humidity \ moisture content, dew point and enthalpy of the outdoor environment, the temperature and humidity, moisture content, dew point and enthalpy of an air supply section of an air conditioning unit, the temperature and humidity, moisture content, dew point and enthalpy of each level of coil pipes of an air conditioner, the temperature and humidity, the dew point and enthalpy of the rear humidifier, the temperature and humidity in a controlled room, and the dew point, enthalpy and moisture content;
(3) data storage: writing each data into an SQL database in a matrix form through a storage interface of each configuration software according to a standard table, wherein the data to be stored is a data ID, a data name, a data value and data acquisition time;
(4) data reading: reading an SQL database through an open function in python, or connecting a connect in a pandas resource library with a current computer database, reading data in the database by using a read _ SQL function, and sorting the data in the database into a matrix, wherein a first column of the matrix is time, and other column names are values of the data mentioned in the second step which are arranged according to the time;
(5) analyzing data;
(6) and (3) parameter storage: storing the conclusion in the data analysis into an SQL database through a python function;
(7) reading parameters: calling a database in real time through configuration software, and transmitting parameters stored in SQL into an industrial configuration software channel;
(8) parameter feedback: transmitting the SQL parameter values read by the configuration software to a PLC controller through the real-time communication between the configuration software and the PLC;
(9) performing parameters: and issuing the parameter information acquired from the PLC to each execution mechanism through a 4-20 mA control signal, and executing the command through the execution mechanisms.
2. The method for realizing accurate control of the temperature and humidity of the air duct and the temperature and humidity of the room according to claim 1, wherein the method comprises the following steps of (1); in the step (3), the data is stored once in a time period of 10S or 5S.
3. The method for realizing accurate control of the temperature and humidity of the air duct and the temperature and humidity of the room according to claim 1, wherein the method comprises the following steps of (1); the specific operation of the data analysis in the step (5) is as follows:
firstly, adding the following actuator values (adding five columns) in five periods in a matrix on the basis of data reading;
index column 1: whether the current temperature is within the deviation range allowed by the system is 1 within the deviation range and 0 is not within the deviation range;
index column 2: whether the current humidity is within the deviation range allowed by the system is 1 within the deviation range and 0 is not within the deviation range;
in the second step, all the parameter lists are normalized, i.e. the value of the data is the current value of the data/(the maximum value of all the values of the data-the minimum value of all the values) to ensure that all the data values are in the range of 0-1
Thirdly, performing single-row linear regression fitting processing on uncontrolled variables such as environment change parameters (outdoor environment temperature and humidity) to obtain a fitting function, calculating a value of the next period through the fitting function, continuously correcting the function equation through machine learning, and reducing comprehensive errors;
fourthly, obtaining a layer convolutional layer which enables the temperature and the humidity to meet the system requirements, namely the temperature and the humidity to be in a fluctuation range by using a neural network algorithm through a neural network tree;
and fifthly, substituting the environmental variables calculated in the third step and other parameter variables acquired in a real-time period into the convolutional layer to obtain the control parameters of each actuating mechanism at the moment.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115185191A (en) * | 2022-09-13 | 2022-10-14 | 钛科优控(江苏)工业科技有限公司 | Self-learning control system and method for thickness of copper foil of foil forming machine |
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| CN201377875Y (en) * | 2009-04-27 | 2010-01-06 | 西安工程大学 | Visual monitoring system for evaporative cooling air conditioner |
| CN104374053A (en) * | 2014-11-25 | 2015-02-25 | 珠海格力电器股份有限公司 | Intelligent control method, device and system |
| CN111272216A (en) * | 2020-01-16 | 2020-06-12 | 杭州麦乐克科技股份有限公司 | Temperature and humidity compensation method and device based on BP neural network |
| CN112378056A (en) * | 2020-11-18 | 2021-02-19 | 珠海格力电器股份有限公司 | Intelligent air conditioner control method and device, computer equipment and storage medium |
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201377875Y (en) * | 2009-04-27 | 2010-01-06 | 西安工程大学 | Visual monitoring system for evaporative cooling air conditioner |
| CN104374053A (en) * | 2014-11-25 | 2015-02-25 | 珠海格力电器股份有限公司 | Intelligent control method, device and system |
| CN111272216A (en) * | 2020-01-16 | 2020-06-12 | 杭州麦乐克科技股份有限公司 | Temperature and humidity compensation method and device based on BP neural network |
| CN112378056A (en) * | 2020-11-18 | 2021-02-19 | 珠海格力电器股份有限公司 | Intelligent air conditioner control method and device, computer equipment and storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115185191A (en) * | 2022-09-13 | 2022-10-14 | 钛科优控(江苏)工业科技有限公司 | Self-learning control system and method for thickness of copper foil of foil forming machine |
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