A visual automatic control system for yellow phosphorus production

Abstract

The present invention relates to the technical field of yellow phosphorus production control, and in particular, to a visual automatic control system for yellow phosphorus production. The system comprises: a data acquisition unit for real-time monitoring of electric furnace temperature deviation, furnace pressure, yellow phosphorus gas concentration deviation, and coke and phosphate consumption; a hierarchical control unit for regulating and controlling electric furnace temperature deviation, electric furnace pressure deviation, coke delivery, and phosphate delivery using a yellow phosphorus electric furnace intelligent hierarchical control algorithm combined with a hierarchical control strategy; a safety protection unit for monitoring temperature indicators, pressure indicators, and abnormal raw material delivery during yellow phosphorus production; and a visual monitoring unit for real-time display of the monitoring results of the data acquisition unit, the hierarchical control unit, and the safety protection unit. The visual automatic control system for yellow phosphorus production realizes visual automatic control of yellow phosphorus production through a yellow phosphorus electric furnace intelligent hierarchical control algorithm combined with visual monitoring and a real-time feedback mechanism.

Description

Technical Field

[0001] The invention relates to the technical field of yellow phosphorus production control, in particular to a visual automatic control system for yellow phosphorus production. Background Art

[0002] A visual automated control system for yellow phosphorus production aims to achieve precise control of the production process and improve production efficiency. Through intelligent hierarchical control algorithms and real-time visual monitoring methods, the temperature of the electric furnace, the pressure inside the furnace, and the amount of coke and phosphate added are controlled to achieve stable, safe and visual automated control of the yellow phosphorus production process.

[0003] The existing yellow phosphorus production control system is usually difficult to cope with complex nonlinear production variables and real-time monitoring of safety hazards. In addition, since the temperature and pressure in the yellow phosphorus production process are difficult to monitor, and the accuracy of the amount of coke and phosphate is difficult to control, it will lead to frequent fluctuations in yellow phosphorus production, serious waste of phosphate and coke resources, and the reaction in the electric furnace cannot be detected in time. Therefore, a visual automatic control system for yellow phosphorus production is designed. Summary of the invention

[0004] The object of the present invention is to provide a visual automatic control system for yellow phosphorus production, so as to solve the problems raised in the above background technology that the temperature and pressure in the yellow phosphorus production process are difficult to monitor, and the accuracy of the amount of coke and phosphate added is difficult to control, which will lead to frequent fluctuations in yellow phosphorus production, serious waste of phosphate and coke resources, and the reaction in the electric furnace cannot be detected in time.

[0005] To achieve the above object, the present invention aims to provide a visual automatic control system for yellow phosphorus production, comprising: a data acquisition unit, wherein the data acquisition unit uses a temperature sensor, a pressure sensor, a gas concentration sensor and a raw material consumption sensor to monitor the temperature deviation of the electric furnace, the pressure in the furnace, the deviation of the yellow phosphorus gas concentration and the consumption of coke and phosphate in real time;

[0006] It also includes a hierarchical control unit, which uses a yellow phosphorus electric furnace intelligent hierarchical control algorithm combined with a hierarchical control strategy to dynamically adjust and control the electric furnace temperature deviation, the electric furnace pressure deviation, the coke input amount, and the phosphate input amount;

[0007] It also includes a safety protection unit, which is used to monitor temperature indicators, pressure indicators and abnormal conditions of raw material delivery during the yellow phosphorus production process;

[0008] It also includes a visual monitoring unit, which displays the monitoring results of the data acquisition unit, the hierarchical control unit and the safety protection unit in real time.

[0009] As a further improvement of the technical solution, the data acquisition unit includes a sensor installation module and a data acquisition module;

[0010] The sensor installation module is used to install each sensor at a specified position. The specific method is as follows:

[0011] S1.1.1. The temperature sensor is used to monitor the high temperature environment inside the electric furnace and is installed inside the electric furnace;

[0012] S1.1.2, the pressure sensor is used to monitor the changes in the gas pressure in the furnace and is installed in a closed position inside the electric furnace;

[0013] S1.1.3, Gas concentration sensor is used to monitor the deviation of yellow phosphorus gas concentration and is installed in the gas discharge channel;

[0014] S1.1.4, Mass flow meter is used to monitor the consumption of coke and phosphate, installed on the raw material conveyor belt;

[0015] The data acquisition module acquires the data of electric furnace temperature deviation, electric furnace pressure deviation, yellow phosphorus gas concentration deviation, coke feeding amount and phosphate feeding amount from various sensors in real time, and transmits the data to the hierarchical control unit and the visual monitoring unit in real time.

[0016] As a further improvement of the technical solution, the yellow phosphorus electric furnace intelligent hierarchical control algorithm is implemented based on LQR control technology and sliding mode control technology. Through the hierarchical control strategy, the electric furnace temperature deviation, electric furnace pressure deviation, coke input and phosphate consumption in the yellow phosphorus production process are dynamically adjusted and optimized, and the yellow phosphorus production process is automatically controlled in combination with a visual monitoring unit.

[0017] Among them, the hierarchical control strategy divides the yellow phosphorus production automation control into two levels: LQR control layer and sliding mode control layer.

[0018] As a further improvement of the technical solution, the hierarchical control unit uses the yellow phosphorus electric furnace intelligent hierarchical control algorithm to dynamically adjust and control the electric furnace temperature deviation, electric furnace pressure deviation, coke feeding amount and phosphate feeding amount. The specific method is as follows:

[0019] S2.1, LQR control layer controls the temperature deviation, pressure deviation and coke input of electric furnace in yellow phosphorus production based on the system state feedback by minimizing the state deviation and the cost of control input;

[0020] S2.2, the sliding mode control layer constructs the phosphate delivery optimization surface, and introduces the molar ratio constraint of phosphate to coke according to the chemical formula of the electric furnace method for yellow phosphorus production, and automatically adjusts the phosphate delivery amount.

[0021] As a further improvement of the technical solution, in S2.1, the LQR control layer controls the temperature deviation, pressure deviation and coke input amount of the electric furnace in yellow phosphorus production by minimizing the state deviation and the cost of the control input based on the state feedback of the system. The specific steps are as follows:

[0022] S2.1.1. Obtaining data from the acquisition module time , Electric furnace pressure deviation and yellow phosphorus gas concentration deviation The state deviation data of Coke supply data at each moment ;

[0023] S2.1.2. Pass time , Electric furnace pressure deviation and yellow phosphorus gas concentration deviation The state deviation data is used to construct the state vector and control input , and construct a state space model;

[0024] S2.1.3 Definitions The matrix is ​​the state vector The weight of The matrix is ​​the control input The weights of the control optimization function are constructed ;

[0025] S2.1.4. Solve the Riccati equation to obtain the Riccati matrix , and calculate the control gain matrix ;

[0026] S2.1.5, according to the control gain matrix Calculate control input , i.e. the amount of coke put into .

[0027] As a further improvement of this technical solution, in S2.1.2, by time , Electric furnace pressure deviation and yellow phosphorus gas concentration deviation The state deviation data is used to construct the state vector and control input , and construct the state space model. The specific method is as follows:

[0028] ;

[0029] ;

[0030] State-space model:

[0031] ;

[0032] in, It is a 3*3 state matrix; is a 3*1 input matrix; Represents the state vector and control input About Time The rate of change of

[0033] In S2.1.3, it is defined The matrix is ​​the state vector The weight of The matrix is ​​the control input The weights of the control optimization function are constructed , the specific method is as follows:

[0034] ;

[0035] ;

[0036] ;

[0037] in, is the state vector The weight matrix of is the weight of the temperature deviation of the electric furnace; is the weight of the yellow phosphorus gas concentration deviation; is the weight of the electric furnace pressure deviation; Coke input The weight of For control input The weight matrix of is the target coke delivery amount;

[0038] In S2.1.4, the Riccati matrix is ​​obtained by solving the Riccati equation , and calculate the control gain matrix , the specific method is as follows:

[0039] Riccati equation:

[0040] ;

[0041] in, yes The transpose of yes The transpose of yes The inverse matrix of

[0042] Control Gain Matrix :

[0043] ;

[0044] in, is the Riccati matrix;

[0045] In S2.1.5, according to the control gain matrix Calculate control input , i.e. the amount of coke put into , the specific method is as follows:

[0046] ;

[0047] in, is the amount of coke put into the system.

[0048] As a further improvement of the technical solution, in S2.2, the sliding mode control layer constructs a phosphate delivery optimization surface, and introduces a molar ratio constraint of phosphate to coke according to the chemical formula of the electric furnace method for yellow phosphorus production, and automatically adjusts the phosphate delivery amount. The specific steps are as follows:

[0049] S2.2.1. According to the state vector , build an optimization surface for phosphate placement , and calculate the optimal area for phosphate placement The derivative of ;

[0050] S2.2.2. According to the chemical formula of yellow phosphorus production by electric furnace method, the molar ratio constraint of phosphate to coke is introduced to calculate the ideal amount of phosphate;

[0051] S2.2.3. According to the state vector Calculate the optimal area for phosphate placement ;

[0052] S2.2.4. Optimize the area according to phosphate placement , derivative And the ideal amount of phosphate , combined with the control law to calculate the actual amount of phosphate;

[0053] S2.2.5, through the control law, the sliding mode control layer optimizes the surface according to the phosphate placement Automatically adjust the actual phosphate dosage .

[0054] As a further improvement of the technical solution, in S2.2.1, according to the state vector , build an optimization surface for phosphate placement , and calculate the optimal area for phosphate placement The derivative of , the specific method is as follows:

[0055] ;

[0056] ;

[0057] in, is the weight coefficient of the temperature deviation of the electric furnace; is the weight coefficient of yellow phosphorus gas concentration deviation; is the weight coefficient of the electric furnace pressure deviation; is the time derivative of the temperature deviation of the electric furnace; is the time derivative of the yellow phosphorus gas concentration deviation; is the time derivative of the electric furnace pressure deviation;

[0058] In S2.2.2, according to the chemical formula of the electric furnace method for yellow phosphorus production, the molar ratio constraint of phosphate to coke is introduced to calculate the ideal amount of phosphate. The specific method is as follows:

[0059] ;

[0060] Phosphate to coke molar ratio constraints: ;

[0061] ;

[0062] In S2.2.4, according to the optimization of phosphate placement , derivative And the ideal amount of phosphate , combined with the control law to calculate the actual amount of phosphate, the specific method is as follows:

[0063] Control law:

[0064] ;

[0065] In S2.2.5, the sliding mode control layer optimizes the surface according to the phosphate placement through the control law. Automatically adjust the actual phosphate dosage , the specific method is as follows:

[0066] ;

[0067] in, is the control gain coefficient; is a symbolic function.

[0068] As a further improvement of the technical solution, the safety protection unit is used to monitor the temperature index, pressure index and abnormal conditions of raw material delivery during the yellow phosphorus production process. The specific method is as follows:

[0069] S3.1. Set the upper and lower temperature thresholds. When the temperature of the electric furnace exceeds the set upper and lower temperature thresholds, the alarm mechanism is automatically triggered; the reaction intensity is reduced by controlling the coke feeding rate; and the cooling device is started to reduce the temperature;

[0070] S3.2. Set the upper and lower pressure thresholds. When the pressure of the electric furnace exceeds the set upper and lower pressure thresholds, release part of the pressure through the automatic valve and reduce the amount of coke added;

[0071] S3.3. The normal range of raw material delivery is set. The coke delivery rate is 50kg / h and the phosphate delivery rate is 10kg / h. When the system detects abnormal raw material delivery, it may immediately suspend the delivery of raw materials and issue an alarm.

[0072] As a further improvement of the technical solution, the visual monitoring unit includes a real-time data panel, an alarm information window and a control status display;

[0073] The real-time data panel displays the data of the electric furnace temperature, electric furnace pressure, yellow phosphorus gas concentration, and the amount of coke and phosphate in the data acquisition unit in real time;

[0074] The control status display is used to show the control input results of the hierarchical control unit LQR control layer and the control input results of the sliding mode control layer;

[0075] The alarm information window displays the alarm information of the safety protection unit in real time, including excessive temperature, abnormal pressure and abnormal raw material delivery.

[0076] Compared with the prior art, the present invention has the following beneficial effects:

[0077] 1. In the visual automatic control system of yellow phosphorus production, based on the intelligent hierarchical control algorithm of yellow phosphorus electric furnace, it can realize the dynamic adjustment of electric furnace temperature, furnace pressure, coke and phosphate input, and accurately control the linear and nonlinear variables in the production process.

[0078] 2. In the visual automation control system for yellow phosphorus production, real-time data collection and visual monitoring are integrated to achieve real-time monitoring and feedback of key production parameters, and combined with automated alarm and protection mechanisms to ensure safe visual monitoring of the production process. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 It is the overall flow chart of the present invention;

[0080] The meaning of each number in the figure is:

[0081] 1. Data acquisition unit; 2. Hierarchical control unit; 3. Safety protection unit; 4. Visual monitoring unit. DETAILED DESCRIPTION

[0082] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0083] Example

[0084] See also Figure 1 As shown, a visual automatic control system for yellow phosphorus production is provided, including a data acquisition unit 1, wherein the data acquisition unit 1 uses a temperature sensor, a pressure sensor, a gas concentration sensor, and a raw material consumption sensor to monitor the temperature deviation of the electric furnace, the pressure in the furnace, the deviation of the yellow phosphorus gas concentration, and the consumption of coke and phosphate in real time;

[0085] In the data acquisition unit 1 of this embodiment, it includes a sensor installation module and a data acquisition module;

[0086] The sensor installation module is used to install each sensor at a specified position. The specific method is as follows:

[0087] S1.1.1. The temperature sensor is used to monitor the high temperature environment inside the electric furnace and is installed inside the electric furnace;

[0088] S1.1.2, the pressure sensor is used to monitor the changes in the gas pressure in the furnace and is installed in a closed position inside the electric furnace;

[0089] S1.1.3, Gas concentration sensor is used to monitor the deviation of yellow phosphorus gas concentration and is installed in the gas discharge channel;

[0090] S1.1.4, Mass flow meter is used to monitor the consumption of coke and phosphate, installed on the raw material conveyor belt;

[0091] In this embodiment, the data acquisition module obtains the electric furnace temperature deviation, electric furnace pressure deviation, yellow phosphorus gas concentration deviation, coke input and phosphate input data from each sensor in real time, and transmits the data to the hierarchical control unit 2 and the visual monitoring unit 4 in real time.

[0092] It also includes a hierarchical control unit 2, which uses a yellow phosphorus electric furnace intelligent hierarchical control algorithm combined with a hierarchical control strategy to dynamically adjust and control the electric furnace temperature deviation, the electric furnace pressure deviation, the coke input amount, and the phosphate input amount;

[0093] In this embodiment, the intelligent hierarchical control algorithm of the yellow phosphorus electric furnace is realized based on the LQR control technology and the sliding mode control technology. Through the hierarchical control strategy, the electric furnace temperature deviation, the electric furnace pressure deviation, the coke input amount and the phosphate consumption in the yellow phosphorus production process are dynamically adjusted and optimized, and the yellow phosphorus production process is automatically controlled in combination with the visual monitoring unit 4;

[0094] In this embodiment, the hierarchical control strategy divides the yellow phosphorus production automation control into two levels: the LQR control layer and the sliding mode control layer.

[0095] In the hierarchical control unit 2 of this embodiment, the yellow phosphorus electric furnace intelligent hierarchical control algorithm is used to dynamically adjust and control the electric furnace temperature deviation, electric furnace pressure deviation, coke feeding amount and phosphate feeding amount. The specific method is as follows:

[0096] S2.1, LQR control layer controls the temperature deviation, pressure deviation and coke input of electric furnace in yellow phosphorus production based on the system state feedback by minimizing the state deviation and the cost of control input;

[0097] S2.2, the sliding mode control layer constructs the phosphate delivery optimization surface, and introduces the molar ratio constraint of phosphate to coke according to the chemical formula of the electric furnace method for yellow phosphorus production, and automatically adjusts the phosphate delivery amount.

[0098] In this embodiment S2.1, the LQR control layer controls the temperature deviation of the electric furnace, the pressure deviation of the electric furnace, and the amount of coke put in during yellow phosphorus production by minimizing the cost of the state deviation and the control input based on the state feedback of the system. The specific steps are as follows:

[0099] S2.1.1. Obtaining data from the acquisition module time , Electric furnace pressure deviation and yellow phosphorus gas concentration deviation The state deviation data of Coke supply data at each moment ;

[0100] S2.1.2. Pass time , Electric furnace pressure deviation and yellow phosphorus gas concentration deviation The state deviation data is used to construct the state vector and control input , and construct a state space model;

[0101] S2.1.3 Definitions The matrix is ​​the state vector The weight of The matrix is ​​the control input The weights of the control optimization function are constructed ;

[0102] S2.1.4. Solve the Riccati equation to obtain the Riccati matrix , and calculate the control gain matrix ;

[0103] S2.1.5, according to the control gain matrix Calculate control input , i.e. the amount of coke put into .

[0104] In this embodiment S2.1.2, by time , Electric furnace pressure deviation and yellow phosphorus gas concentration deviation The state deviation data is used to construct the state vector and control input , and construct the state space model. The specific method is as follows:

[0105] ;

[0106] ;

[0107] State-space model:

[0108] ;

[0109] in, It is a 3*3 state matrix; is a 3*1 input matrix; Represents the state vector and control input About Time The rate of change of

[0110] The state matrix describes the internal dynamic behavior of the system, that is, the mutual influence relationship between state variables such as temperature, yellow phosphorus concentration and pressure, in the following form:

[0111] ;

[0112] Input matrix, describing the control input How to affect the system state determines the direct effect of coke input on temperature, gas concentration and pressure in the following form:

[0113] ;

[0114] Calculate the state vector based on the actual state deviation , this state vector It is used for state feedback regulation in LQR control;

[0115] State Space Model , describes how the system state is affected by the current state and control input, and controls the system temperature, yellow phosphorus concentration and pressure by dynamically adjusting the amount of coke added.

[0116] In this embodiment S2.1.3, it is defined The matrix is ​​the state vector The weight of The matrix is ​​the control input The weights of the control optimization function are constructed , the specific method is as follows:

[0117] ;

[0118] ;

[0119] ;

[0120] in, is the state vector The weight matrix of is the weight of the temperature deviation of the electric furnace; is the weight of the yellow phosphorus gas concentration deviation; is the weight of the electric furnace pressure deviation; Coke input The weight of For control input The weight matrix of is the target coke delivery amount;

[0121] , and The value of is usually determined according to system performance requirements or through experiments and simulation tuning. The specific value depends on the relative importance of temperature, gas concentration and pressure in the yellow phosphorus production process;

[0122] Reflects the optimization tendency of the control system for coke consumption, The larger the value, the control system will tend to reduce the consumption of coke and avoid unnecessary waste of resources; The smaller the value, the more flexibly the system will adjust the coke delivery to maintain the balance of the system; The value is determined based on resource availability and production goals.

[0123] In this embodiment S2.1.4, the Riccati equation is solved to obtain the Riccati matrix , and calculate the control gain matrix , the specific method is as follows:

[0124] Riccati equation:

[0125] ;

[0126] in, yes The transpose of yes The transpose of yes The inverse matrix of

[0127] Control Gain Matrix :

[0128] ;

[0129] in, is the Riccati matrix;

[0130] The Riccati matrix obtained by solving the Riccati equation , used for weighted state feedback;

[0131] Control Gain Matrix The size of reflects how the control input is adjusted according to the system state:

[0132] if A larger value indicates that the system is more sensitive to state deviations and will make large control adjustments;

[0133] if A smaller value indicates that the system is more moderate in adjusting the state deviation;

[0134] In S2.1.5, according to the control gain matrix Calculate control input , i.e. the amount of coke put into , the specific method is as follows:

[0135] ;

[0136] in, is the amount of coke put into the system.

[0137] Indicates the amount of coke required for the system under ideal conditions. If the system state (temperature, yellow phosphorus gas concentration, pressure) has no deviation, then Will be close , that is, there will be no significant adjustment in the amount of coke supplied;

[0138] Indicates that the system adjusts the delivery amount according to the deviation of the current state. Matrix-to-state feedback Perform weighted calculation and give the adjustment value. Specifically:

[0139] If there are large deviations in temperature, gas concentration or pressure, the control system will calculate , adjust the amount of coke added;

[0140] If the deviation is positive, the system will reduce the amount of coke added to slow down the reaction; if the deviation is negative, the system will increase the amount of coke added.

[0141] In this embodiment S2.2, the sliding mode control layer constructs a phosphate delivery optimization surface, and introduces a phosphate to coke molar ratio constraint based on the chemical formula of yellow phosphorus production electric furnace method, and automatically adjusts the phosphate delivery amount. The specific steps are as follows:

[0142] S2.2.1. According to the state vector , build an optimization surface for phosphate placement , and calculate the optimal area for phosphate placement The derivative of ;

[0143] S2.2.2. According to the chemical formula of yellow phosphorus production by electric furnace method, the molar ratio constraint of phosphate to coke is introduced to calculate the ideal amount of phosphate;

[0144] S2.2.3. According to the state vector Calculate the optimal area for phosphate placement ;

[0145] S2.2.4. Optimize the area according to phosphate placement , derivative And the ideal amount of phosphate , combined with the control law to calculate the actual amount of phosphate;

[0146] S2.2.5, through the control law, the sliding mode control layer optimizes the surface according to the phosphate placement Automatically adjust the actual phosphate dosage .

[0147] In this embodiment S2.2.1, according to the state vector , build an optimization surface for phosphate placement , and calculate the optimal area for phosphate placement The derivative of , the specific method is as follows:

[0148] ;

[0149] ;

[0150] in, is the weight coefficient of the temperature deviation of the electric furnace; is the weight coefficient of yellow phosphorus gas concentration deviation; is the weight coefficient of the electric furnace pressure deviation; is the time derivative of the temperature deviation of the electric furnace; is the time derivative of the yellow phosphorus gas concentration deviation; is the time derivative of the electric furnace pressure deviation;

[0151] In this embodiment S2.2.2, according to the chemical formula of the electric furnace method for yellow phosphorus production, the molar ratio constraint of phosphate to coke is introduced to calculate the ideal amount of phosphate added. The specific method is as follows:

[0152] ;

[0153] Phosphate to coke molar ratio constraints: ;

[0154] ;

[0155] In this embodiment S2.2.4, according to the phosphate placement optimization area , derivative And the ideal amount of phosphate , combined with the control law to calculate the actual amount of phosphate, the specific method is as follows:

[0156] Control law:

[0157] ;

[0158] In this embodiment S2.2.5, the sliding mode control layer optimizes the surface according to the phosphate placement through the control law. Automatically adjust the actual phosphate dosage , the specific method is as follows:

[0159] ;

[0160] in, is the control gain coefficient; is a symbolic function.

[0161] is the control gain factor, which is used to adjust the optimization surface according to the phosphate placement. Adjustments to phosphate levels:

[0162] when When the value is large, the system The system is more sensitive to deviations and has a larger adjustment range. At this time, the system responds faster to the amount of phosphate added and is suitable for adjusting to rapidly changing conditions.

[0163] when When the value is small, the system adjustment range is small, which is suitable for fine adjustment of stable or slowly changing systems;

[0164] is a symbolic function used to determine the optimal surface for phosphate placement Symbols:

[0165] , indicating that the system state has deviated from the optimal surface of phosphate delivery, and the amount of phosphate delivery should be increased to return the system state to the optimal surface of phosphate delivery;

[0166] , indicating that the system state deviates from the optimal surface of phosphate delivery, and the phosphate delivery amount should be reduced to adjust the system state;

[0167] , indicating that the system status is just at the optimization surface of phosphate delivery. At this time, no additional adjustment is required, and the phosphate delivery amount remains at the ideal delivery value.

[0168] It also includes a safety protection unit 3, which is used to monitor temperature indicators, pressure indicators and abnormal conditions of raw material delivery during the yellow phosphorus production process;

[0169] In the present embodiment, the safety protection unit 3 is used to monitor the temperature index, pressure index and abnormal conditions of raw material delivery during the yellow phosphorus production process. The specific method is as follows:

[0170] S3.1. Set the upper and lower temperature thresholds. When the temperature of the electric furnace exceeds the set upper and lower temperature thresholds, the alarm mechanism is automatically triggered; the reaction intensity is reduced by controlling the coke feeding rate; and the cooling device is started to reduce the temperature;

[0171] S3.2. Set the upper and lower pressure thresholds. When the pressure of the electric furnace exceeds the set upper and lower pressure thresholds, release part of the pressure through the automatic valve and reduce the amount of coke added;

[0172] S3.3. The normal range of raw material delivery is set. The coke delivery rate is 50kg / h and the phosphate delivery rate is 10kg / h. When the system detects abnormal raw material delivery, it may immediately suspend the delivery of raw materials and issue an alarm.

[0173] It also includes a visual monitoring unit 4, which displays the monitoring results of the data acquisition unit 1, the hierarchical control unit 2 and the security protection unit 3 in real time.

[0174] In the present embodiment, the visual monitoring unit 4 includes a real-time data panel, an alarm information window and a control status display;

[0175] The real-time data panel displays the data of the electric furnace temperature, electric furnace pressure, yellow phosphorus gas concentration, and the amount of coke and phosphate in the data acquisition unit 1 in real time;

[0176] The control status display is used to show the control input results of the hierarchical control unit 2LQR control layer and the control input results of the sliding mode control layer;

[0177] The alarm information window displays the alarm information of the safety protection unit 3 in real time, including temperature exceeding the limit, pressure abnormality and abnormal raw material delivery.

[0178] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments, and the above embodiments and descriptions are only preferred examples of the present invention, and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.

Claims

1. A visual automatic control system for yellow phosphorus production, characterized in that: include: A data acquisition unit (1), wherein the data acquisition unit (1) uses a temperature sensor, a pressure sensor, a gas concentration sensor and a raw material consumption sensor to monitor in real time the temperature deviation of the electric furnace, the pressure in the furnace, the yellow phosphorus gas concentration deviation and the consumption of coke and phosphate; A hierarchical control unit (2), wherein the hierarchical control unit (2) utilizes a yellow phosphorus electric furnace intelligent hierarchical control algorithm combined with a hierarchical control strategy to dynamically adjust and control the electric furnace temperature deviation, the electric furnace pressure deviation, the coke feed amount, and the phosphate feed amount; A safety protection unit (3), the safety protection unit (3) being used to monitor temperature indicators, pressure indicators and abnormal conditions of raw material delivery during the yellow phosphorus production process; A visual monitoring unit (4), wherein the visual monitoring unit (4) displays monitoring results of the data acquisition unit (1), the hierarchical control unit (2) and the safety protection unit (3) in real time; The hierarchical control unit (2) uses the yellow phosphorus electric furnace intelligent hierarchical control algorithm to dynamically adjust and control the electric furnace temperature deviation, electric furnace pressure deviation, coke feed amount and phosphate feed amount. The specific method is as follows: S2.1, LQR control layer controls the temperature deviation, pressure deviation and coke input of electric furnace in yellow phosphorus production based on the system state feedback by minimizing the state deviation and the cost of control input; S2.2, the sliding mode control layer constructs the phosphate delivery optimization surface, and introduces the molar ratio constraint of phosphate to coke according to the chemical formula of the electric furnace method for yellow phosphorus production, and automatically adjusts the phosphate delivery amount; In S2.1, the LQR control layer controls the temperature deviation, pressure deviation and coke input amount of the electric furnace in yellow phosphorus production based on the system state feedback by minimizing the state deviation and the cost of control input. The specific steps are as follows: S2.1.

1. Obtaining data from the acquisition module Temperature deviation of electric furnace at all times , Electric furnace pressure deviation and yellow phosphorus gas concentration deviation The state deviation data of Coke supply data at each moment ; S2.1.

2. Pass Temperature deviation of electric furnace at all times , Electric furnace pressure deviation and yellow phosphorus gas concentration deviation The state deviation data is used to construct the state vector and control input , and construct a state space model; S2.1.3 Definitions The matrix is ​​the state vector The weight of The matrix is ​​the control input The weights of the control optimization function are constructed ; S2.1.

4. Solve the Riccati equation to obtain the Riccati matrix , and calculate the control gain matrix ; S2.1.5, according to the control gain matrix Calculate control input , i.e. the amount of coke put into ; In S2.1.2, by Temperature deviation of electric furnace at all times , Electric furnace pressure deviation and yellow phosphorus gas concentration deviation The state deviation data is used to construct the state vector and control input , and construct the state space model. The specific method is as follows: ； ； State-space model: ； in, It is a 3*3 state matrix; is a 3*1 input matrix; Represents the state vector and control input About Time The rate of change of In S2.1.3, it is defined The matrix is ​​the state vector The weight of The matrix is ​​the control input The weights of the control optimization function are constructed , the specific method is as follows: ； ； ； in, is the state vector The weight matrix of is the weight of the temperature deviation of the electric furnace; is the weight of the yellow phosphorus gas concentration deviation; is the weight of the electric furnace pressure deviation; Coke input The weight of For control input The weight matrix of is the target coke delivery amount; In S2.1.4, the Riccati matrix is ​​obtained by solving the Riccati equation , and calculate the control gain matrix , the specific method is as follows: Riccati equation: ； in, yes The transpose of yes The transpose of yes The inverse matrix of Control Gain Matrix : ； in, is the Riccati matrix; In S2.1.5, according to the control gain matrix Calculate control input , i.e. the amount of coke put into , the specific method is as follows: ； in, is the amount of coke put into the system.

2. The visual automatic control system for yellow phosphorus production according to claim 1, characterized in that: The data acquisition unit (1) comprises a sensor installation module and a data acquisition module; The sensor installation module is used to install each sensor at a specified position. The specific method is as follows: S1.1.

1. The temperature sensor is used to monitor the high temperature environment inside the electric furnace and is installed inside the electric furnace; S1.1.2, the pressure sensor is used to monitor the changes in the gas pressure in the furnace and is installed in a closed position inside the electric furnace; S1.1.3, Gas concentration sensor is used to monitor the deviation of yellow phosphorus gas concentration and is installed in the gas discharge channel; S1.1.4, Mass flow meter is used to monitor the consumption of coke and phosphate, installed on the raw material conveyor belt; The data acquisition module acquires data on electric furnace temperature deviation, electric furnace pressure deviation, yellow phosphorus gas concentration deviation, coke feed amount and phosphate feed amount from various sensors in real time, and transmits the data to the hierarchical control unit (2) and the visual monitoring unit (4) in real time.

3. The visual automatic control system for yellow phosphorus production according to claim 1, characterized in that: The yellow phosphorus electric furnace intelligent hierarchical control algorithm is implemented based on LQR control technology and sliding mode control technology. Through the hierarchical control strategy, the electric furnace temperature deviation, electric furnace pressure deviation, coke input and phosphate consumption in the yellow phosphorus production process are dynamically adjusted and optimized, and the yellow phosphorus production process is automatically controlled in combination with the visual monitoring unit (4); Among them, the hierarchical control strategy divides the yellow phosphorus production automation control into two levels: LQR control layer and sliding mode control layer.

4. The visual automatic control system for yellow phosphorus production according to claim 1, characterized in that: In S2.2, the sliding mode control layer constructs the phosphate delivery optimization surface, and introduces the molar ratio constraint of phosphate to coke according to the chemical formula of the electric furnace method for yellow phosphorus production, and automatically adjusts the phosphate delivery amount. The specific steps are as follows: S2.2.

1. According to the state vector , build an optimization surface for phosphate placement , and calculate the optimal area for phosphate placement The derivative of ; S2.2.

2. According to the chemical formula of yellow phosphorus production by electric furnace method, the molar ratio constraint of phosphate to coke is introduced to calculate the ideal amount of phosphate; S2.2.

3. According to the state vector Calculate the optimal area for phosphate placement ; S2.2.

4. Optimize the area according to phosphate placement , derivative And the ideal amount of phosphate , combined with the control law to calculate the actual amount of phosphate; S2.2.5, through the control law, the sliding mode control layer optimizes the surface according to the phosphate placement Automatically adjust the actual phosphate dosage .

5. The visual automatic control system for yellow phosphorus production according to claim 4, characterized in that: In S2.2.1, according to the state vector , build an optimization surface for phosphate placement , and calculate the optimal area for phosphate placement The derivative of , the specific method is as follows: ； ； in, is the weight coefficient of the temperature deviation of the electric furnace; is the weight coefficient of yellow phosphorus gas concentration deviation; is the weight coefficient of the electric furnace pressure deviation; is the time derivative of the temperature deviation of the electric furnace; is the time derivative of the yellow phosphorus gas concentration deviation; is the time derivative of the electric furnace pressure deviation; In S2.2.2, according to the chemical formula of the electric furnace method for yellow phosphorus production, the molar ratio constraint of phosphate to coke is introduced to calculate the ideal amount of phosphate. The specific method is as follows: ； Phosphate to coke molar ratio constraints: ; ； In S2.2.4, according to the optimization of phosphate placement , derivative And the ideal amount of phosphate , combined with the control law to calculate the actual amount of phosphate, the specific method is as follows: Control law: ； In S2.2.5, the sliding mode control layer optimizes the surface according to the phosphate placement through the control law. Automatically adjust the actual phosphate dosage , the specific method is as follows: ； in, is the control gain coefficient; is a symbolic function.

6. The visual automatic control system for yellow phosphorus production according to claim 1, characterized in that: The safety protection unit (3) is used to monitor the temperature index, pressure index and abnormal conditions of raw material delivery during the yellow phosphorus production process. The specific method is as follows: S3.

1. Set the upper and lower temperature thresholds. When the temperature of the electric furnace exceeds the set upper and lower temperature thresholds, the alarm mechanism is automatically triggered; the reaction intensity is reduced by controlling the coke feeding rate; and the cooling device is started to reduce the temperature; S3.

2. Set the upper and lower pressure thresholds. When the pressure of the electric furnace exceeds the set upper and lower pressure thresholds, release part of the pressure through the automatic valve and reduce the amount of coke added; S3.

3. The normal range of raw material delivery is set. The coke delivery rate is 50kg / h and the phosphate delivery rate is 10kg / h. When the system detects abnormal raw material delivery, it may immediately suspend the delivery of raw materials and issue an alarm.

7. The visual automatic control system for yellow phosphorus production according to claim 1, characterized in that: The visual monitoring unit (4) includes a real-time data panel, an alarm information window and a control status display; The real-time data panel displays the data of the electric furnace temperature, electric furnace pressure, yellow phosphorus gas concentration, and the amount of coke and phosphate added in the data acquisition unit (1) in real time; The control status display is used to display the control input results of the LQR control layer of the hierarchical control unit (2) and the control input results of the sliding mode control layer; The alarm information window displays the alarm information of the safety protection unit (3) in real time, including temperature exceeding the limit, pressure abnormality and abnormal raw material feeding.

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