CN116540803A - Temperature control method and system of evaporation tank, electronic equipment and storage medium - Google Patents
Temperature control method and system of evaporation tank, electronic equipment and storage medium Download PDFInfo
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- CN116540803A CN116540803A CN202310595315.4A CN202310595315A CN116540803A CN 116540803 A CN116540803 A CN 116540803A CN 202310595315 A CN202310595315 A CN 202310595315A CN 116540803 A CN116540803 A CN 116540803A
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- 238000001704 evaporation Methods 0.000 title claims abstract description 65
- 230000008020 evaporation Effects 0.000 title claims abstract description 47
- 238000000034 method Methods 0.000 title claims abstract description 44
- 238000010438 heat treatment Methods 0.000 claims abstract description 187
- 238000001914 filtration Methods 0.000 claims abstract description 89
- 230000036760 body temperature Effects 0.000 claims abstract description 76
- 239000011159 matrix material Substances 0.000 claims description 84
- 230000008859 change Effects 0.000 claims description 24
- 230000008569 process Effects 0.000 claims description 10
- 238000004590 computer program Methods 0.000 claims description 7
- 238000009529 body temperature measurement Methods 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000004422 calculation algorithm Methods 0.000 description 12
- 238000005259 measurement Methods 0.000 description 12
- 230000003444 anaesthetic effect Effects 0.000 description 10
- 239000007789 gas Substances 0.000 description 7
- 206010002091 Anaesthesia Diseases 0.000 description 5
- 230000037005 anaesthesia Effects 0.000 description 5
- 230000004044 response Effects 0.000 description 4
- 230000026676 system process Effects 0.000 description 4
- 230000009286 beneficial effect Effects 0.000 description 2
- 125000004122 cyclic group Chemical group 0.000 description 2
- 238000013178 mathematical model Methods 0.000 description 2
- 230000010355 oscillation Effects 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 230000001360 synchronised effect Effects 0.000 description 2
- 230000007704 transition Effects 0.000 description 2
- 239000006200 vaporizer Substances 0.000 description 2
- 239000003994 anesthetic gas Substances 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 239000003193 general anesthetic agent Substances 0.000 description 1
- 230000017525 heat dissipation Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000000630 rising effect Effects 0.000 description 1
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D23/00—Control of temperature
- G05D23/19—Control of temperature characterised by the use of electric means
- G05D23/20—Control of temperature characterised by the use of electric means with sensing elements having variation of electric or magnetic properties with change of temperature
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Abstract
The embodiment of the invention discloses a temperature control method and system of an evaporation tank, electronic equipment and a storage medium, and specifically comprises the following steps: the method comprises the steps of presetting a tank body target temperature T of an evaporation tank, acquiring the measured tank body temperature of the evaporation tank in real time, and carrying out Kalman filtering on the measured tank body temperature of the evaporation tank acquired each time to obtain a feedback tank body temperature T 1 By feeding back the tank temperature T 1 Determining the heating power of the heating plate according to the comparison relation between the heating power and the target tank temperature T, wherein the heating power is realized according to the feedback tank temperature T 1 The heating power of the heating plate is controlled by using different methods, so that the temperature of the heating plate and the temperature of the tank body in the tank body can be controlled simultaneously, and the temperature of the tank body can be kept constant.
Description
Technical Field
The invention relates to the technical field of temperature control, in particular to a temperature control method of an evaporation tank.
Background
The evaporating pot is an important component of the anesthesia machine, and utilizes the change of the ambient temperature or a heat source to change the anesthetic into evaporating gas, the evaporating gas is carried into a loop to become a gas flow with anesthetic vapor with a certain concentration, and the evaporating speed of the anesthetic changes along with the temperature, which means that the temperature of the evaporating pot is required to be ensured to be constant, so that the gas flow with the anesthetic vapor with a stable concentration can be output.
In the prior art, an anesthetic evaporator with a heat source directly heats the tank body of the evaporator through the heat source, and the temperature controlled by the anesthetic evaporator is the heat source temperature or the tank body temperature; if the heat source temperature is directly controlled to enable the heat source to reach a certain temperature, the temperature of the tank body gradually approaches to the heat source temperature along with time, so that temperature difference can be generated, and the overall temperature rise time is longer; if the temperature of the tank body is controlled, the temperature of the heat source is not controlled, so that the temperature of the tank body is easy to be excessively high and unstable.
Disclosure of Invention
In view of the above, it is necessary to provide a method, a system, an electronic device, and a storage medium for controlling the temperature of an evaporation tank.
A method of controlling the temperature of an evaporation tank, the method comprising: determining a tank body target temperature T of an evaporation tank, acquiring the measured tank body temperature of the evaporation tank in real time, and performing Kalman filtering on the measured tank body temperature of the evaporation tank acquired each time to obtain a feedback tank body temperature T 1 According to the feedback tank body temperature T 1 And determining the heating power of the heating plate according to the comparison relation between the heating plate and the tank target temperature T.
In the above scheme, the temperature T of the tank body is fed back according to the temperature T of the tank body 1 The comparison relation with the target temperature T of the tank body is used for determining the heating power of the heating plate, and the method specifically comprises the following steps: if the feedback tank body temperature T 1 <At T-K deg.C, the heating plate is controlled to have maximum heating power W max When the temperature T-K ℃ of the feedback tank body is less than or equal to T 1 When the temperature is less than or equal to T+K ℃, the heating plate is controlled to be at the maximum heating power W max And a minimum heating power W min Work in between, if the temperature T of the tank body is fed back 1 >At T+K ℃, the heating plate is controlled to have minimum heating power W min Working; wherein K is a fixed offset value.
In the above scheme, the control heating plate uses the maximum heating power W max The work specifically includes: w (W) max Is arranged between 50% and 100% of rated power of the heating plate.
In the above scheme, the control heating plate uses the minimum heating power W min The work specifically includes: w (W) min Set to 0 or a positive value near 0.
In the above scheme, the control heating plate is at maximum heating power W max And a minimum heating power W min The working process specifically comprises the following steps: according to the feedback tank body temperature T 1 And determining a desired heating plate temperature change rate according to the tank target temperature T; determining a heating plate working power value according to the expected heating plate temperature change rate and the feedback heating plate temperature change rate, and controlling the heating plate working power to be the value by controlling the PWM wave duty ratio value of the heating plate; the feedback heating plate temperature change rate specifically comprises: the temperature sensor is used for acquiring a temperature measurement value of the heating plate at the moment T and carrying out Kalman filtering on the temperature measurement value to acquire a feedback heating plate temperature T at the moment T 2 And determining the temperature change rate of the feedback heating plate according to the difference between the temperature of the feedback heating plate at the time t and the temperature of the feedback heating plate at the time t-1 divided by the time interval from the time t-1 to the time t.
In the above scheme, the temperature sensor acquires the temperature measurement value of the heating plate at the time T, and performs kalman filtering to the temperature measurement value to obtain the feedback heating plate temperature T at the time T 2 The method specifically comprises the following steps: acquiring a filtering value at the time T-1, namely feeding back the temperature of the heating sheet, calculating a predicted value at the time T according to the filtering value, acquiring a covariance matrix of the filtering value at the time T-1, updating the covariance matrix of the predicted value at the time T according to the covariance matrix of the predicted value at the time T, calculating a Kalman gain according to the covariance matrix of the predicted value at the time T, and calculating an optimal filtering value, namely feeding back the temperature T of the heating sheet according to the predicted value at the time T, the temperature measured value of the heating sheet, the covariance matrix of the predicted value and the Kalman gain 2 Updating the covariance matrix of the optimal filtering value at the time T according to the covariance matrix of the predicted value at the time T and the Kalman gain, and feeding back the optimal filtering value at the time T, namely the temperature T of the heating plate 2 And transmitting the optimal filtering value covariance matrix to the time t+1, and determining the optimal filtering value and the optimal filtering value covariance matrix at the time t+i according to the cycle, wherein i=1, 2 and 3.
In the above scheme, the kalman filtering is performed on the measured tank body temperature of the evaporating tank obtained each time to obtain the feedback tank body temperature T 1 The method specifically comprises the following steps: acquiring a filtering value at the time T-1, namely, feeding back the tank body temperature, calculating a predicted value at the time T according to the filtering value, acquiring a covariance matrix of the filtering value at the time T-1, updating the covariance matrix of the predicted value at the time T according to the covariance matrix of the predicted value at the time T, calculating a Kalman gain according to the covariance matrix of the predicted value at the time T, and calculating an optimal filtering value, namely, feeding back the tank body temperature T according to the predicted value at the time T, the measured tank body temperature, the covariance matrix of the predicted value and the Kalman gain 1 Updating the covariance matrix of the optimal filtering value at the time T according to the covariance matrix of the predicted value at the time T and the Kalman gain, and obtaining the optimal filtering value at the time T, namely the feedback tank body temperature T 1 And transmitting the optimal filtering value covariance matrix to the time t+1, and determining the optimal filtering value and the optimal filtering value covariance matrix at the time t+i according to the cycle, wherein i=1, 2 and 3.
Still further, the present invention also provides a temperature control system of an evaporation tank, the system comprising: the device comprises a first setting unit, a second acquisition unit, a third execution unit and a fourth execution unit; the first setting unit is used for determining a target temperature T of the evaporation tank, the second obtaining unit is used for obtaining a measured tank body temperature of the evaporation tank in real time, and the third executing unit is used for carrying out Kalman filtering on the measured tank body temperature of the evaporation tank obtained each time to obtain a feedback tank body temperature T 1 The fourth calculation unit is used for feeding back the tank body temperature T according to the temperature 1 And determining the heating power of the heating plate according to the comparison relation between the heating plate and the tank target temperature T.
Still further, the present invention also proposes a readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the steps of: determining a tank body target temperature T of an evaporation tank, acquiring the measured tank body temperature of the evaporation tank in real time, and performing Kalman filtering on the measured tank body temperature of the evaporation tank acquired each time to obtain a feedback tank body temperature T 1 According to the feedback tank body temperature T 1 And tank objectThe comparison of the temperatures T determines the heating power of the heater chip.
Still further, the present invention also proposes a computer device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the steps of: determining a tank body target temperature T of an evaporation tank, acquiring the measured tank body temperature of the evaporation tank in real time, and performing Kalman filtering on the measured tank body temperature of the evaporation tank acquired each time to obtain a feedback tank body temperature T 1， According to the feedback tank body temperature T 1 And determining the heating power of the heating plate according to the comparison relation between the heating plate and the tank target temperature T.
The embodiment of the invention has the following beneficial effects: firstly determining a tank body target temperature T of an evaporation tank, acquiring the measured tank body temperature of the evaporation tank in real time, and carrying out Kalman filtering on the measured tank body temperature of the evaporation tank acquired each time to obtain a feedback tank body temperature T 1 By comparing and feeding back the tank temperature T 1 Determining the heating power of the heating plate according to the comparison relation between the tank body target temperature T and the heating power of the heating plate, wherein the method can be used for feeding back the tank body temperature T 1 The heating power of the heating plate is controlled in different modes so as to effectively control the temperature of the tank body, so that the temperature of the tank body can be kept constant all the time, and the air flow with stable concentration is output.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Wherein:
FIG. 1 is a flow chart of a method of evaporator temperature control in one embodiment;
FIG. 2 is a flow chart of Kalman filtering of measured tank temperatures in one embodiment;
FIG. 3 is a control flow diagram of a PID algorithm in one embodiment;
FIG. 4 is a flow chart of Kalman filtering of measured temperature of a heater chip within a tank in one embodiment;
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, not all embodiments.
All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the following description, numerous specific details are set forth in order to provide a more thorough understanding of the present invention. It will be apparent, however, to one skilled in the art that the invention may be practiced without one or more of these details.
In other instances, well-known features have not been described in detail in order to avoid obscuring the invention. It should be understood that the present invention may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise, and it is to be understood that the terms "comprises" and/or "comprising" when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. As used herein, the term "and/or" includes any and all combinations of the associated listed items.
In order to provide a thorough understanding of the present invention, detailed structures will be presented in the following description in order to illustrate the technical solutions presented by the present invention. Alternative embodiments of the invention are described in detail below, however, the invention may have other implementations in addition to these detailed descriptions.
The temperature control method, the temperature control system, the electronic equipment and the storage medium of the evaporating pot are suitable for the evaporator module of the anesthesia machine, the evaporating pot is controlled to be in a constant temperature state by utilizing the change of the ambient temperature and the heat source temperature, anesthetic drugs are changed into evaporating gas, and then a certain amount of anesthetic gas is carried into a loop to become gas flow with anesthetic vapor with a certain concentration, so that anesthetic inhalation gas with a constant concentration is effectively provided for patients.
As shown in fig. 1, in one embodiment, there is provided a temperature control method of an evaporation tank, which includes steps S101 to S104, as follows:
s101, determining a tank body target temperature T of an evaporation tank;
the tank target temperature T can be set manually according to different scenes and different setting rules.
S102, acquiring the temperature of a measuring tank body of the evaporating tank in real time;
the real-time acquired temperature information of the measuring tank can obtain feedback of the current most real situation, and new temperature data can be conveniently received and processed in real time.
S103, carrying out Kalman filtering on the measured tank body temperature of the evaporating tank obtained each time to obtain a feedback tank body temperature T 1 ；
In some embodiments, the specific process of Kalman filtering the measured tank temperature of the evaporation tank as shown in FIG. 2 includes:
s301, obtaining a filtering value at the time t-1, namely a feedback tank body temperature, and calculating a predicted value at the time t according to the filtering value;
s302, acquiring a covariance matrix of a filtering value at the time t-1, and updating the covariance matrix of a predicted value at the time t according to the covariance matrix;
s303, calculating Kalman gain according to a covariance matrix of a predicted value at the moment t;
s304, calculating an optimal filtering value, namely a feedback tank body temperature T, according to the predicted value at the time T, the measured tank body temperature, the covariance matrix of the predicted value and the Kalman gain 1 Updating the covariance matrix of the optimal filtering value at the moment t according to the covariance matrix of the predicted value at the moment t and the Kalman gain;
s305, feeding back the optimal filtering value at the moment T to the tank body temperature T 1 And transmitting the optimal filtering value covariance matrix to the time t+1, and determining the optimal filtering value and the optimal filtering value covariance matrix at the time t+i according to the cycle, wherein i=1, 2 and 3.
Preferably, the above-described process of performing kalman filtering on the measured can body temperature is analyzed using one example of S301 to S305:
given the values of the system process noise covariance matrix Q and the system measurement noise covariance matrix R, a greater value of Q relative to the value of R represents more trusted sensor measurement data, and a greater value of R relative to the value of Q represents more trusted algorithm predictions.
The system process noise covariance matrix Q is a matrix for describing the influence degree of noise in the system on state change, is an important parameter for system state estimation and control, and is 1*1 because the system only has temperature parameters; the process noise covariance matrix Q is generally difficult to theoretically calculate, and is determined by experience judgment of engineers according to specific scenes in most cases. The measurement noise covariance matrix R is the covariance of errors between the measured value and the true value of the sensor, is the inaccuracy of the measurement of the sensor, and can be generally read from the accuracy index in the sensor specification.
Assuming that the current t-time tank body temperature state is k, the t-1 time tank body temperature state is k-1, and the t+1 time tank body temperature state is k+1, the current t-time tank body temperature can be predicted according to the temperature filtered by the t-1 time tank body, and the specific expression is as follows:
X(k|k-1)＝AX(k-1|k-1)+BU(k) (1.0)
in the above expression:
x (k|k-1) is the result of the current t moment tank body temperature state predicted by the filtered value of the tank body temperature at the t-1 moment, X (k-1|k-1) is the optimal filtered value of the tank body temperature state at the t-1 moment, U (k) is the control quantity of the tank body temperature state at the current t moment, the system U (k) without control input is generally set to 0, A is a state transition matrix, B is a control matrix, and A and B can be set according to actual conditions.
Further, updating the covariance matrix of the predicted value of the tank body temperature state at the moment t according to the covariance matrix of the filtered value of the tank body temperature at the moment t-1, wherein the concrete expression is as follows:
P(k|k-1)＝AP(k-1|k-1)A T +Q (2.0)
in the above expression:
p (k|k-1) is the covariance matrix of X (k|k-1), P (k-1|k-1) is the covariance matrix of X (k-1|k-1), A T The transpose of A, Q is the covariance matrix of the system process noise.
Further, the kalman gain can be calculated according to the covariance matrix of the tank temperature predicted value at the current time t: the specific expression is:
Kg(k)＝P(k|k-1)H T /(HP(k|k-1)H T +R) (3.0)
in the above expression:
kg (k) is Kalman gain, H is measurement matrix, H T The transpose of H, R is the covariance matrix of the system measurement noise.
The optimal filter value expression for the tank temperature state at the current time t is:
X(k|k)＝X(k|k-1)+Kg(k)(Z(K)-H(X(k|k-1)) (4.0)
in the above expression: where X (k|k) is the filtered value of the current t-time state and Z (K) is the current t-time sensor measurement.
Further, updating a covariance matrix of the tank temperature filtering value at the current t moment: p (k|k) = (I-Kg (k) H) P (k|k-1) (5.0)
In the above expression: where I is the unit diagonal matrix, i=1 for single model single measurement.
When the system enters a state of the tank temperature k+1 at the next moment, X (k|k) is X (k-1|k-1) of the expression (1.0), P (k|k) is P (k-1|k-1) of the expression (2.0), and the algorithm can go down through autoregressive cyclic operation, so that Kalman filtering is continuously performed on the temperature of the measuring tank.
S104, according to the feedback tank body temperature T 1 Determining the heating power of the heating plate according to the comparison relation between the heating plate and the tank target temperature T; the method specifically comprises the following steps:
if the tank temperature T is fed back 1 <At T-K deg.C, the heating plate in the tank body is controlled to have maximum heating power W max Working;
if the temperature T-K ℃ of the feedback tank body is less than or equal to T 1 When the temperature is less than or equal to T+K ℃, the heating plate in the tank body is controlled to be at the maximum heating power W max And a minimum heating power W min Working in between;
if the tank temperature T is fed back 1 >At T+K ℃, the heating plate in the tank body is controlled to have minimum heating power W min Working; wherein K is a fixed offset value.
In some embodiments, the heater chip is controlled to maximize heating power W max The operation aims to heat the temperature of the anesthesia evaporation tank at the maximum heating speed, so as to reduce the heating time; wherein W is max Can be selected according to the required heating time and rated power of the heating plate, and is generally between 50% and 100% of the rated power.
In some embodiments, the heater chip is controlled to a minimum heating power W min The purpose of the operation is to prevent the temperature of the anesthetic vaporizer from rising further; wherein W is min Can be selected according to the natural heat dissipation speed of the anesthetic vaporizer, and generally takes a very small value, namely W min Can be set to be 0 or a positive value close to 0, so that the temperature is quickly reduced to be within positive and negative K ℃ of the target control temperature T of the tank body, and K is different deviation values set according to actual conditions.
In some embodiments, the heater chip is controlled at a maximum heating power W max And a minimum heating power W min The operation can be realized by utilizing a PID algorithm to control the working power of the heating plate so as to keep the temperature of the anesthesia evaporation tank near the target control temperature of the tank body, and the details are as follows:
as shown in fig. 3, the PID algorithm includes an outer loopAnd the input of the inner ring and the outer ring is the tank target control temperature T, the output is the tank temperature, and the feedback is the temperature value T after the Kalman filtering of the measured tank temperature 1 The purpose of the outer ring is to control the tank temperature so that it stabilizes around the target control temperature T.
The input of the inner ring is the expected temperature change rate of the heating plate, the expected temperature change rate of the heating plate is calculated by the outer ring, the output is the temperature of the heating plate, and the feedback is the temperature value T after the temperature of the heating plate is measured and subjected to Kalman filtering 2 The purpose of the inner ring is to control the temperature of the heating plate, limit the heating speed of the heating plate, prevent the heating plate from heating too fast to generate a large amount of heat in a short time, and make the temperature of the evaporating pot too high after being conducted to the evaporating pot.
The specific expression of the PID algorithm is as follows:
in the above expression:
e (K) is the error between the ideal value and the measured value of the current control target quantity, in the scheme, the control target quantity is the temperature and the change rate of the temperature respectively, e (K-1) is the last error, e (K-2) is the last error, deltaU (K) is the current output increment, U (K-1) is the last output of the PID controller, U (K) is the current output of the PID controller, K p 、K i 、K d Is a PID control parameter;
at the beginning of the algorithm, it is necessary to apply a code to K p 、K i 、K d The initial values of U (K-1), e (K-1) and e (K-2), and the initial values of U (K-1), e (K-1) and e (K-2) are 0, and K is a control system which is easy to establish a mathematical model p 、K i 、K d The optimal set value can be calculated by a theoretical method, but in practice, most control systems are difficult to accurately establish a mathematical model, so K p 、K i 、K d The decision is typically determined by an engineer's experience. General K p The larger the system response speed is, the faster the system response speed is, but the system oscillation is caused by the overlarge system response speed; k (K) i The larger is more beneficial to reducing the static difference of the system control, butExcessive size can cause overshoot and oscillation of system control; k (K) d The larger the system is, the more deviation of the system can be restrained, but the response speed of the system is reduced.
Preferably, the temperature T can be based on feedback tank body 1 And determining the expected heating plate temperature change rate according to the tank target temperature T, and determining the heating plate working power according to the heating plate temperature change rate obtained by calculating the expected heating plate temperature change rate and the feedback heating plate temperature, wherein the heating plate temperature change rate is the change amount of the temperature in unit time, and the algorithm takes the time of dividing the difference value of the heating plate feedback temperature between two times of control by the interval between the two times of control.
In some embodiments, the PWM wave duty cycle value of the heating plate can be controlled, so as to control the working power of the heating plate, and the working power of the heating plate is controlled at the PWM wave duty cycle value; specifically, when the power supply voltage of the heating plate is the rated voltage, the PWM wave duty ratio value of the heating plate is the percentage of the working power of the heating plate to the rated power.
For example: the PWM wave duty ratio of the heating plate is controlled to be 50%, the working power of the heating plate is 50% of the rated power, so that the PID algorithm is used for directly outputting the working power of the heating plate, and the PWM wave duty ratio of the heating plate is controlled, the working power of the heating plate can be limited through a limiter, the output PWM wave duty ratio is limited, and when the working power of the heating plate is limited to be between 0 and 0.6 times of the rated power, the output PWM wave duty ratio is limited to be between 0% and 60%.
In some embodiments, obtaining the temperature change rate of the heating plate at the time t specifically includes: the temperature sensor is used for acquiring the temperature measured by the heating plate at the time T, and Kalman filtering is carried out on the temperature measured by the heating plate to acquire the temperature T of the feedback heating plate at the time T 2 And determining the temperature change rate of the feedback heating plate according to the difference between the temperature of the feedback heating plate at the time t and the temperature of the feedback heating plate at the time t-1 divided by the time interval from the time t-1 to the time t.
As shown in fig. 3, a specific process of performing kalman filtering on the temperature of the heating plate at the time t includes:
s401, obtaining a filtering value at the time t-1, namely feeding back the temperature of the heating sheet, and calculating a predicted value at the time t according to the temperature;
s402, acquiring a covariance matrix of a filtering value at the time t-1, and updating the covariance matrix of a predicted value at the time t according to the covariance matrix;
s403, calculating Kalman gain according to a covariance matrix of a predicted value at the moment t;
s404, calculating an optimal filtering value, namely a feedback heating plate temperature T, according to the predicted value at the time T, the heating plate temperature measured value, the covariance matrix of the predicted value and the Kalman gain 2 Updating the covariance matrix of the optimal filtering value at the moment t according to the covariance matrix of the predicted value at the moment t and the Kalman gain;
s405, feeding back the temperature T of the heating plate as the optimal filtering value at the time T 2 And transmitting the optimal filtering value covariance matrix to the time t+1, and determining the optimal filtering value and the optimal filtering value covariance matrix at the time t+i according to the cycle, wherein i=1, 2 and 3.
Preferably, a specific flow of performing kalman filtering on the temperature of the heating plate will be described with reference to S401 to S405 by using an example: assuming that the temperature state of the heating plate at the current t moment is k, the temperature state of the heating plate at the t-1 moment is k-1, and the temperature state of the heating plate at the t+1 moment is k+1, the temperature of the heating plate at the current t moment can be predicted according to the temperature filtered by the heating plate at the t-1 moment, and the specific expression is as follows:
X(k|k-1)＝AX(k-1|k-1)+BU(k) (1.1)
in the above expression:
x (k|k-1) is the temperature of the heating plate at the current time t predicted by the filtered value of the temperature of the heating plate at the time t-1, X (k-1|k-1) is the temperature value of the heating plate after the filtering at the time t-1, U (k) is the control quantity of the temperature of the heating plate at the current time t, U (k) is generally set to 0 for a system U (k) without control input, A is a state transition matrix, B is a control matrix, and A and B can be set according to the actual condition of the system.
Further, updating the covariance matrix of the predicted value of the temperature of the heating plate at the time t according to the covariance matrix of the filtered value of the temperature of the heating plate at the time t-1, wherein the specific expression is as follows:
P(k|k-1)＝AP(k-1|k-1)A T +Q (2.1)
in the above expression:
p (k|k-1) is the covariance matrix of X (k|k-1), P (k-1|k-1) is the covariance matrix of X (k-1|k-1), A T The transpose of A, Q is the covariance matrix of the system process noise.
Calculating Kalman gain according to the covariance matrix of the temperature predicted value of the heating plate at the current t moment: the specific expression is:
Kg(k)＝P(k|k-1)H T /(HP(k|k-1)H T +R) (3.1)
in the above expression:
kg (k) is Kalman gain, H is measurement matrix, H T The transpose of H, R is the covariance matrix of the system measurement noise.
The optimal filter value expression of the state of the heating plate at the current t moment is as follows:
X(k|k)＝X(k|k-1)+Kg(k)(Z(K)-H(X(k|k-1)) (4.1)
in the above expression: where X (k|k) is the filtered value of the current t-time state and Z (K) is the current t-time sensor measurement.
Further, updating a covariance matrix of the temperature filtering value of the heating plate at the current t moment:
P(k|k)＝(I-Kg(k)H)P(k|k-1)(5.1)
in the above expression: where I is the unit diagonal matrix, i=1 for single model single measurement.
When the system enters a heating plate k+1 state at the next moment, X (k|k) is X (k-1|k-1) of the expression (1.1), P (k|k) is P (k-1|k-1) of the expression (2.1), and the algorithm can go on through autoregressive cyclic operation, so that the Kalman filtering on the temperature of the heating plate in the tank body is continuously carried out.
Preferably, when Kalman filtering is used for the tank and heater chip measured temperatures, X (k-1|k-1) and P (k-1|k-1) need to be initialized when first entering the filtering process, and P (k-1|k-1) cannot be initialized to 0, typically to the same order of magnitude as the ideal value or a smaller number, for faster convergence.
It can be seen that the kalman filtering performed on the measured heating plate temperature and the measured tank temperature has the same processing procedure, and in addition, although the kalman filtering used in the scheme processes the temperature value, the noise of the measured signal is filtered, other algorithms capable of filtering the sensor noise may be used instead, such as a least mean square algorithm (LSM), etc.
To sum up, this application scheme carries out filtering control through the heating plate temperature to jar body temperature and heat source temperature simultaneously and adjusts, not only can restrict the intensification speed of heating plate, has prevented that the excessive overshoot from appearing in jar body temperature, can also control jar body overall heating time fast, reduces the difference in temperature for jar body temperature keeps invariable, and temperature fluctuation range is little, can guarantee to export the air current of invariable concentration when using on the anesthesia machine.
The invention also provides a temperature control system of the evaporating pot, which comprises: the device comprises a first setting unit, a second acquisition unit, a third execution unit and a fourth execution unit;
a first setting unit for determining a target temperature T of the evaporation tank;
the second acquisition unit is used for acquiring the measured tank body temperature of the evaporation tank in real time;
a third execution unit for performing Kalman filtering on the measured tank body temperature of the evaporating tank obtained each time to obtain a feedback tank body temperature T 1 ；
A fourth calculation unit for feeding back the tank temperature T 1 And determining the heating power of the heating plate according to the comparison relation between the heating plate and the tank target temperature T.
In one embodiment, a computer device is presented comprising a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of: determining a tank body target temperature T of the evaporation tank, acquiring the measured tank body temperature of the evaporation tank in real time, and performing Kalman filtering on the measured tank body temperature of the evaporation tank acquired each time to obtain a feedback tank body temperature T 1 According to the feedback tank body temperature T 1 And determining the heating power of the heating plate according to the comparison relation between the heating plate and the tank target temperature T.
In one implementationIn an example, a computer-readable storage medium is proposed, storing a computer program which, when executed by a processor, causes the processor to perform the steps of: determining a tank body target temperature T of the evaporation tank, acquiring the measured tank body temperature of the evaporation tank in real time, and performing Kalman filtering on the measured tank body temperature of the evaporation tank acquired each time to obtain a feedback tank body temperature T 1 According to the feedback tank body temperature T 1 And determining the heating power of the heating plate according to the comparison relation between the heating plate and the tank target temperature T.
Those skilled in the art will appreciate that the processes implementing all or part of the methods of the above embodiments can be implemented by means of hardware associated with a computer program, where the program can be stored on a non-volatile computer readable storage medium, and the program when executed can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments can be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be regarded as the scope described in the present specification.
The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it is also possible for a person skilled in the art to make several variations and modifications without departing from the spirit of the present application, which are all within the scope of protection of the present application, and what has been disclosed above is only a preferred embodiment of the present invention, and it is needless to say that the scope of the claims of the present invention shall not be limited thereto, and therefore equivalent variations according to the claims of the present invention shall still fall within the scope of the present invention.
Claims (10)
1. A method of controlling the temperature of an evaporation tank, the method comprising:
determining a tank body target temperature T of the evaporation tank;
acquiring the temperature of a measuring tank body of the evaporating tank in real time;
carrying out Kalman filtering on the measured tank body temperature of the evaporating tank obtained each time to obtain a feedback tank body temperature T 1 ；
According to the feedback tank body temperature T 1 And determining the heating power of the heating plate according to the comparison relation between the heating plate and the tank target temperature T.
2. The method according to claim 1, wherein the temperature of the evaporation tank is based on the feedback tank temperature T 1 The comparison relation with the target temperature T of the tank body is used for determining the heating power of the heating plate, and the method specifically comprises the following steps:
if the feedback tank body temperature T 1 <At T-K deg.C, the heating plate is controlled to have maximum heating power W max Working;
if the temperature T-K ℃ of the feedback tank body is less than or equal to T 1 When the temperature is less than or equal to T+K ℃, the heating plate is controlled to be at the maximum heating power W max And a minimum heating power W min Working in between;
if the tank temperature T is fed back 1 >At T+K ℃, the heating plate is controlled to have minimum heating power W min Working; wherein K is a fixed offset value.
3. The method of controlling the temperature of an evaporation tank according to claim 2, wherein said heating sheet is controlled to be maximum addedThermal power W max The work specifically includes:
W max is arranged between 50% and 100% of rated power of the heating plate.
4. A temperature control method of an evaporation tank according to claim 3, wherein said control heating plate is operated at a minimum heating power W min The work specifically includes:
W min set to 0 or a positive value near 0.
5. The method of controlling the temperature of an evaporation tank according to claim 4, wherein said control heating plate has a maximum heating power W max And a minimum heating power W min The working process specifically comprises the following steps:
according to the feedback tank body temperature T 1 And determining a desired heating plate temperature change rate according to the tank target temperature T;
determining a heating plate working power value according to the expected heating plate temperature change rate and the feedback heating plate temperature change rate, and controlling the heating plate working power to be the value by controlling the PWM wave duty ratio value of the heating plate;
the feedback heating plate temperature change rate specifically comprises: the temperature sensor is used for acquiring a temperature measurement value of the heating plate at the moment T and carrying out Kalman filtering on the temperature measurement value to acquire a feedback heating plate temperature T at the moment T 2 And determining the temperature change rate of the feedback heating plate according to the difference between the temperature of the feedback heating plate at the time t and the temperature of the feedback heating plate at the time t-1 divided by the time interval from the time t-1 to the time t.
6. The method according to claim 5, wherein the temperature sensor obtains the temperature of the heating plate at time T, and performs Kalman filtering to obtain the feedback heating plate temperature T at time T 2 The method specifically comprises the following steps:
acquiring a filtering value at the time t-1, namely feeding back the temperature of the heating sheet, and calculating a predicted value at the time t according to the temperature;
acquiring a covariance matrix of a filtering value at the time t-1, and updating the covariance matrix of a predicted value at the time t according to the covariance matrix;
calculating Kalman gain according to the covariance matrix of the predicted value at the moment t;
calculating an optimal filtering value, namely feeding back the temperature T of the heating plate according to the predicted value at the time T, the temperature measured value of the heating plate, the covariance matrix of the predicted value and the Kalman gain 2 Updating the covariance matrix of the optimal filtering value at the moment t according to the covariance matrix of the predicted value at the moment t and the Kalman gain;
the optimal filtering value at the time T is feedback heating plate temperature T 2 And transmitting the optimal filtering value covariance matrix to the time t+1, and determining the optimal filtering value and the optimal filtering value covariance matrix at the time t+i according to the cycle, wherein i=1, 2 and 3.
7. The method according to any one of claims 1 to 6, wherein the kalman filter is performed on the measured tank temperature of the evaporation tank obtained each time to obtain a feedback tank temperature T 1 The method specifically comprises the following steps:
acquiring a filtering value at the time t-1, namely feeding back the tank temperature, and calculating a predicted value at the time t according to the filtering value;
acquiring a covariance matrix of a filtering value at the time t-1, and updating the covariance matrix of a predicted value at the time t according to the covariance matrix;
calculating Kalman gain according to the covariance matrix of the predicted value at the moment t;
calculating an optimal filtering value, namely a feedback tank body temperature T, according to the predicted value at the time T, the measured tank body temperature, the covariance matrix of the predicted value and the Kalman gain 1 Updating the covariance matrix of the optimal filtering value at the moment t according to the covariance matrix of the predicted value at the moment t and the Kalman gain;
the optimal filtering value at the time T is the feedback tank body temperature T 1 And transmitting the optimal filtering value covariance matrix to the time t+1, and determining the optimal filtering value and the optimal filtering value covariance matrix at the time t+i according to the cycle, wherein i=1, 2 and 3.
8. A temperature control system for an evaporator tank, the system comprising: the device comprises a first setting unit, a second acquisition unit, a third execution unit and a fourth execution unit;
the first setting unit is used for determining a target temperature T of the evaporation tank;
the second acquisition unit is used for acquiring the measured tank body temperature of the evaporation tank in real time;
the third execution unit is used for carrying out Kalman filtering on the measured tank body temperature of the evaporating tank obtained each time to obtain a feedback tank body temperature T 1 ；
The fourth calculation unit is used for feeding back the tank body temperature T according to the temperature 1 And determining the heating power of the heating plate according to the comparison relation between the heating plate and the tank target temperature T.
9. A readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the steps of the method as claimed in any one of claims 1 to 7.
10. A computer device comprising a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of the method as claimed in any one of claims 1 to 7.
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| CN202310595315.4A CN116540803A (en) | 2023-05-24 | 2023-05-24 | Temperature control method and system of evaporation tank, electronic equipment and storage medium |
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| CN202310595315.4A CN116540803A (en) | 2023-05-24 | 2023-05-24 | Temperature control method and system of evaporation tank, electronic equipment and storage medium |
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