CN110953837B - Water-cooling cabinet control method, device, equipment and medium - Google Patents
Water-cooling cabinet control method, device, equipment and medium Download PDFInfo
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- CN110953837B CN110953837B CN201911292890.7A CN201911292890A CN110953837B CN 110953837 B CN110953837 B CN 110953837B CN 201911292890 A CN201911292890 A CN 201911292890A CN 110953837 B CN110953837 B CN 110953837B
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
- F25D—REFRIGERATORS; COLD ROOMS; ICE-BOXES; COOLING OR FREEZING APPARATUS NOT OTHERWISE PROVIDED FOR
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Abstract
The embodiment of the invention discloses a water-cooling cabinet control method, a water-cooling cabinet control device, water-cooling equipment and a water-cooling medium. The method comprises the following steps: acquiring the water outlet temperature of the water-cooling cabinet, the rotating speed of a fan of the water-cooling cabinet and a given water outlet temperature; determining control parameters of a first controller of the water cooling cabinet and control parameters of a second controller of the water cooling cabinet when the water outlet temperature of the water cooling cabinet reaches the given water outlet temperature and the energy consumption of the water cooling cabinet is minimum based on the water outlet temperature, the rotating speed and the given water outlet temperature; and controlling the opening degree of a water valve of the water-cooling cabinet based on the control parameter of the first controller, and controlling the rotating speed of the fan based on the control parameter of the second controller so as to control the minimum energy consumption of the water-cooling cabinet when the outlet water temperature of the water-cooling cabinet reaches the given outlet water temperature. The water-cooling cabinet control method, the device, the equipment and the medium can ensure that the energy consumption of the water-cooling cabinet is minimum when the outlet water temperature of the water-cooling cabinet reaches the given outlet water temperature, and can save energy consumption.
Description
Technical Field
The invention relates to the technical field of automatic control, in particular to a water-cooling cabinet control method, device, equipment and medium.
Background
At present, there are mainly two ways for the control of a water-cooled cabinet:
in the first mode, different rotating speeds of the fan of the water cooling cabinet are set to correspond to different temperature intervals, and when the outlet water temperature of the water cooling cabinet is in a certain temperature interval, the fan is controlled to rotate at the rotating speed corresponding to the temperature interval so as to control the outlet water temperature of the water cooling cabinet.
In the second mode, the rotational speed of the fan or the opening of the water valve is controlled by adopting a proportional-integral-derivative (PID) to control the outlet water temperature of the water cooling cabinet.
By adopting the two modes, although the water outlet temperature of the water cooling cabinet can be controlled to reach the given water outlet temperature, the minimum energy consumption of the water cooling cabinet can not be ensured, the energy consumption of the water cooling cabinet is possibly very large, and the energy consumption is relatively large.
Disclosure of Invention
The embodiment of the invention provides a water-cooling cabinet control method, a device, equipment and a medium, which can ensure that the energy consumption of the water-cooling cabinet is minimum when the outlet water temperature of the water-cooling cabinet reaches a given outlet water temperature, and can save energy consumption.
In one aspect, an embodiment of the present invention provides a method for controlling a water-cooling cabinet, including:
acquiring the water outlet temperature of the water-cooling cabinet, the rotating speed of a fan of the water-cooling cabinet and a given water outlet temperature;
determining control parameters of a first controller of the water cooling cabinet and control parameters of a second controller of the water cooling cabinet when the water outlet temperature of the water cooling cabinet reaches the given water outlet temperature and the energy consumption of the water cooling cabinet is minimum based on the water outlet temperature, the rotating speed and the given water outlet temperature; the first controller is used for controlling the opening of a water valve of the water cooling cabinet, and the second controller is used for controlling the rotating speed of the fan;
and controlling the opening degree of a water valve of the water-cooling cabinet based on the control parameter of the first controller, and controlling the rotating speed of the fan based on the control parameter of the second controller so as to control the minimum energy consumption of the water-cooling cabinet when the outlet water temperature of the water-cooling cabinet reaches the given outlet water temperature.
In an embodiment of the present invention, when determining that the outlet water temperature of the water-cooling cabinet reaches the given outlet water temperature and the energy consumption of the water-cooling cabinet is minimum based on the outlet water temperature, the rotation speed and the given outlet water temperature, the determining the control parameter of the first controller of the water-cooling cabinet and the control parameter of the second controller of the water-cooling cabinet includes:
and determining control parameters of a first controller of the water cooling cabinet and control parameters of a second controller of the water cooling cabinet when the outlet water temperature of the water cooling cabinet reaches the given outlet water temperature and the energy consumption of the water cooling cabinet is minimum by adopting a fusion algorithm of a particle swarm algorithm and a bacterial foraging algorithm based on the outlet water temperature, the rotating speed and the given outlet water temperature.
In an embodiment of the present invention, acquiring the outlet water temperature of the water-cooling cabinet and the rotation speed of the fan of the water-cooling cabinet includes:
detecting the outlet water temperature of the water-cooling cabinet by using a temperature sensor;
and detecting the rotating speed of a fan of the water-cooling cabinet by using the wind speed sensor.
In one embodiment of the invention, the first controller and the second controller are both proportional-integral-derivative controllers; the control parameters include: a proportionality coefficient, an integral coefficient, and a differential coefficient.
On the other hand, the embodiment of the invention provides a control device of a water cooling cabinet, which comprises the following components:
the acquisition module is used for acquiring the water outlet temperature of the water cooling cabinet, the rotating speed of a fan of the water cooling cabinet and the given water outlet temperature;
the determining module is used for determining control parameters of a first controller of the water cooling cabinet and control parameters of a second controller of the water cooling cabinet when the water outlet temperature of the water cooling cabinet reaches the given water outlet temperature and the energy consumption of the water cooling cabinet is minimum based on the water outlet temperature, the rotating speed and the given water outlet temperature; the first controller is used for controlling the opening of a water valve of the water cooling cabinet, and the second controller is used for controlling the rotating speed of the fan;
and the control module is used for controlling the opening of a water valve of the water cooling cabinet based on the control parameter of the first controller and controlling the rotating speed of the fan based on the control parameter of the second controller so as to control the minimum energy consumption of the water cooling cabinet when the outlet water temperature of the water cooling cabinet reaches the given outlet water temperature.
In an embodiment of the present invention, the determining module is specifically configured to:
and determining control parameters of a first controller of the water cooling cabinet and control parameters of a second controller of the water cooling cabinet when the outlet water temperature of the water cooling cabinet reaches the given outlet water temperature and the energy consumption of the water cooling cabinet is minimum by adopting a fusion algorithm of a particle swarm algorithm and a bacterial foraging algorithm based on the outlet water temperature, the rotating speed and the given outlet water temperature.
In an embodiment of the present invention, the obtaining module is specifically configured to:
detecting the outlet water temperature of the water-cooling cabinet by using a temperature sensor;
and detecting the rotating speed of a fan of the water-cooling cabinet by using the wind speed sensor.
In one embodiment of the invention, the first controller and the second controller are both proportional-integral-derivative controllers; the control parameters include: a proportionality coefficient, an integral coefficient, and a differential coefficient.
In another aspect, an embodiment of the present invention provides a water-cooled cabinet control device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor;
the processor executes the computer program to realize the water-cooling cabinet control method provided by the embodiment of the invention.
In another aspect, an embodiment of the present invention provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the method for controlling a water-cooling cabinet provided by the embodiment of the present invention is implemented.
The water-cooling cabinet control method, the device, the equipment and the medium can ensure that the energy consumption of the water-cooling cabinet is minimum when the outlet water temperature of the water-cooling cabinet reaches the given outlet water temperature, and can save energy consumption.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the embodiments of the present invention will be briefly described below, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart illustrating a water-cooling cabinet control method according to an embodiment of the present invention;
FIG. 2 illustrates a schematic diagram of PID control provided by an embodiment of the invention;
FIG. 3 is a schematic diagram illustrating particle operating logic provided by embodiments of the present invention;
FIG. 4 is a schematic diagram of a PID control based on a fusion algorithm according to an embodiment of the invention;
FIG. 5 is a schematic diagram illustrating a fusion algorithm based determination of control parameters provided by an embodiment of the present invention;
FIG. 6 is a schematic diagram illustrating a fusion algorithm based control of a water-cooled cabinet according to an embodiment of the present invention;
FIG. 7 is a schematic diagram illustrating a water-cooled cabinet control model provided by an embodiment of the invention;
FIG. 8 is a schematic diagram illustrating temperature adjustment of a water-cooled cabinet according to an embodiment of the present invention;
FIG. 9 is a schematic diagram illustrating power regulation of a water-cooled cabinet according to an embodiment of the present invention;
FIG. 10 is a schematic structural diagram of a water-cooling cabinet control device provided by an embodiment of the invention;
fig. 11 is a block diagram illustrating an exemplary hardware architecture of a computing device capable of implementing the water-cooled cabinet control method and apparatus according to an embodiment of the invention.
Detailed Description
Features and exemplary embodiments of various aspects of the present invention will be described in detail below, and in order to make objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not to be construed as limiting the invention. It will be apparent to one skilled in the art that the present invention may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present invention by illustrating examples of the present invention.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
In order to solve the problems in the prior art, embodiments of the present invention provide a method, an apparatus, a device, and a medium for controlling a water-cooling cabinet. First, a method for controlling a water-cooling cabinet according to an embodiment of the present invention will be described.
Fig. 1 shows a schematic flow chart of a water-cooling cabinet control method provided by an embodiment of the invention. The water-cooling cabinet control method can comprise the following steps:
s101: and acquiring the water outlet temperature of the water-cooling cabinet, the rotating speed of a fan of the water-cooling cabinet and the given water outlet temperature.
S102: and determining control parameters of a first controller of the water cooling cabinet and control parameters of a second controller of the water cooling cabinet when the outlet water temperature of the water cooling cabinet reaches the given outlet water temperature and the energy consumption of the water cooling cabinet is minimum based on the outlet water temperature of the water cooling cabinet, the rotating speed of a fan of the water cooling cabinet and the given outlet water temperature.
The first controller is used for controlling the opening of a water valve of the water-cooling cabinet, and the second controller is used for controlling the rotating speed of a fan of the water-cooling cabinet.
S103: and controlling the opening degree of a water valve of the water-cooling cabinet based on the control parameter of the first controller, and controlling the rotating speed of a fan of the water-cooling cabinet based on the control parameter of the second controller so as to control the energy consumption of the water-cooling cabinet to be minimum when the outlet water temperature of the water-cooling cabinet reaches the given outlet water temperature.
The control method of the water-cooling cabinet provided by the embodiment of the invention can ensure that the energy consumption of the water-cooling cabinet is minimum when the outlet water temperature of the water-cooling cabinet reaches the given outlet water temperature, and can save energy consumption.
In one embodiment of the invention, the outlet water temperature of the water-cooling cabinet can be detected by using a temperature sensor; and detecting the rotating speed of a fan of the water-cooling cabinet by using the wind speed sensor.
In one embodiment of the present invention, the first controller and the second controller may be both proportional-integral-derivative (PID) controllers; the control parameters include: a proportionality coefficient, an integral coefficient, and a differential coefficient.
Fig. 2 shows a schematic diagram of the PID control provided by the embodiment of the present invention.
And controlling the controlled object by adopting PID (proportion integration differentiation) based on the actual output value y (t) and the given value r (t) of the controlled object.
Based on fig. 2, the mathematical model corresponding to PID control is expressed by equation (1):
in the formula (1), u (t) is the output of PID control, KpProportional coefficient, K, for PID controliIntegral coefficient, K, for PID controldIn the PID control, e (t) is r (t) to y (t), r (t) is a given value, and y (t) is an actual output value of the controlled object.
In an embodiment of the invention, a fusion algorithm of a particle swarm algorithm and a bacterial foraging algorithm can be adopted, and based on the outlet water temperature, the rotating speed and the given outlet water temperature, when the outlet water temperature of the water-cooling cabinet reaches the given outlet water temperature and the energy consumption of the water-cooling cabinet is minimum, the control parameters of the first controller of the water-cooling cabinet and the control parameters of the second controller of the water-cooling cabinet are determined.
Fig. 3 is a schematic diagram illustrating a particle operation logic provided by an embodiment of the present invention. The inertia factors in FIG. 3 reflect the motion habit of the particles, indicating that the particles tend to maintain their previous velocity; the memory factor reflects the memory of the particles on the self historical experience and represents the trend that the particles approach to the self historical optimal position; the group factors reflect group historical experiences of cooperative cooperation and knowledge sharing among the particles and represent the trend of the particles following group operation. The updated formula for the velocity and position of the particle is as follows:
wherein, in the formulas (2) and (3),the d-dimension speed of the particle i at the moment t + 1; w is the particle inertial weight coefficient;is the speed of the particle i at the d-th dimension of the time t; c. C1The self-learning factor represents the judging capability of the particles on the self position and speed degrees, namely the weight coefficient of the particles tracking the self historical optimal value; r is1Is a random number between (0, 1);the optimal position of the d-dimension individual of the particle i in the motion process is determined;is the position of the d-dimension of the particle i at the time t; c. C2For the mutual learning factor, the degree of closeness of the optimal solution of the particle and the particle group is expressed, namely the particle tracking group is the mostA weight coefficient of the merit value; r is2Is a random number between (0, 1);the optimal position of the particle swarm in the d-th dimension at the time t is defined;the d-dimension speed of the particle i at the moment t + 1; r is a velocity constraint factor. It will be appreciated that time t +1 is the time next to time t.
In the usual case, c1And c2The value is 2. r takes the value of 1.
The bacterial foraging algorithm comprises: chemotaxis, replication and migration. Chemotaxis is a chemotactic operation, which includes two forms of rotation, which means that bacteria change direction during movement, and swimming, which means that bacteria travel in this direction. The replication operation means that in the process of optimizing bacteria, part of the bacteria are eliminated without finding a proper living environment, and the living bacteria can be propagated in order to ensure the colony scale of the bacteria. The migration operation means that a large area of bacterial colonies die due to mutation of the living environment of bacteria, and the remaining bacterial colonies migrate to a new environment. The tropism operation can embody the local searching capacity of the bacterial foraging algorithm, and the replication and migration can embody the global searching capacity of the bacterial foraging algorithm.
The tropism of each bacterium was expressed as in equation (4).
In the formula (4), θi(j +1, k, l) is the position of bacterium i after the (j +1) th tropism operation of k replications and l migrations; thetai(j, k, l) is the position of bacterium i after the jth tropism operation of k replications and l migrations; c (i) random movement step size for bacteria i each time tropism operation is performed; and delta (i) is a movement direction vector of the bacteria i.
In one embodiment of the invention, to make the fusion algorithm more efficient and practicalIn the former stage, the overall search capability is required to be stronger, the bacterial tropism operation step length C (i) is required to be larger, in the later stage of the algorithm, the local search capability is required to be stronger, so as to improve the accuracy of the algorithm, and the bacterial tropism operation step length C (i) is required to be reduced. The bacterial tropism operation step length C (i) is gradually changed along with the running of the algorithm, and C (i +1) ═ C (i) × e-t(ii) a And t is the running time of the algorithm.
When the particle swarm algorithm and the bacterial foraging algorithm are fused, each particle in the particle swarm algorithm is used as a bacterium in the bacterial foraging algorithm, and the movement direction vector of the bacterium in the bacterial foraging algorithm is replaced by the speed of the particle in the particle swarm algorithm.
After replacing the bacterial motion direction vector in the bacterial foraging algorithm with the velocity of the particles in the particle swarm algorithm, the tropism operation of each bacterium is expressed as:
in the formula (5), Pi(j +1, k, l) is the position of bacterium i after the (j +1) th tropism operation of k replications and l migrations; pi(j, k, l) is the position of bacterium i after the jth tropism operation of k replications and l migrations; c (i) random movement step size for bacteria i each time tropism operation is performed; v. ofk+1Is the velocity of the particles.
The particle swarm algorithm has weak global search capability and strong local search capability, and is easy to fall into a local optimal solution; and the bacterial foraging algorithm has strong global searching capability, weak local searching capability and inaccurate optimizing effect. According to the embodiment of the invention, the two algorithms are fused, so that the local searching performance of the two algorithms is well combined, the local searching capacity is improved, the copy operation and the migration operation of the bacterial foraging algorithm are not changed, and the global searching capacity of the fusion algorithm is ensured.
Fig. 4 shows a PID control schematic diagram based on a fusion algorithm according to an embodiment of the present invention.
And determining control parameters (a proportional system Kp, an integral coefficient Ki and a differential coefficient Kd) of PID control by using the output value of the sensor detection system and based on the system output value and the system output value detected by the sensor and adopting a fusion algorithm of a particle swarm algorithm and a bacterial foraging algorithm. And the PID controller controls the controlled equipment based on the determined control parameters.
Fig. 5 is a schematic diagram illustrating determination of a control parameter based on a fusion algorithm according to an embodiment of the present invention.
Firstly, particle initialization and bacterial initialization; the method comprises the steps of initializing the particle number n of a particle swarm, enabling the dimension of a search space to be 6 dimensions, enabling the inertia weight coefficient of particles, the speed and the position of each particle, the maximum number of bacteria tropism operations, the maximum number of bacteria replication operations, the maximum number of bacteria migration operations, the size of a step of movement step of the bacteria tropism operations, the migration probability, a learning factor and two random numbers of 0-1. 6 dimensions are respectively the proportionality coefficient K of the first controllerp1Integral coefficient Ki1Differential coefficient Kd1Proportional coefficient K of the second controllerp2Integral coefficient Ki2And a differential coefficient Kd2。
The position of the ith particle can be represented as xi=(xi1,xi2,xi3,xi4,xi5,xi6),xi1,xi2,xi3,xi4,xi5And xi6Respectively showing the position of the ith particle in the 1 st, 2 nd, 3 rd, 4 th, 5 th and 6 th dimensions.
The velocity of the ith particle can be expressed as vi=(vi1,vi2,vi3,vi4,vi5,vi6),vi1,vi2,vi3,vi4,vi5And vi6Respectively representing the velocities of the ith particle in the 1 st, 2 nd, 3 rd, 4 th, 5 th and 6 th dimensions.
Calculating the fitness value of each particle, solving the individual optimal position of each particle, and solving the global optimal position of the particle swarm;
updating the speed and position of the particles;
judging whether an end condition is met; if the end condition is not met, continuing to calculate the fitness value of each particle; if the end condition is met, each particle in the particle swarm algorithm is used as a bacterium in the bacterium foraging algorithm, the movement direction vector of the bacterium in the bacterium foraging algorithm is replaced by the speed of the particle in the particle swarm algorithm, and the optimization result (global optimal position) of the particle swarm algorithm is used as the initial position of the bacterium.
Performing a tropism operation in a bacterial foraging algorithm;
judging whether the times of executing the tropism operation reach the maximum times of the bacterial tropism operation;
if the times of executing the tropism operation do not reach the maximum times of the bacterial tropism operation, continuing executing the tropism operation in the bacterial foraging algorithm;
if the times of executing the tropism operation reach the maximum times of the bacterial tropism operation, executing the copy operation in the bacterial foraging algorithm;
judging the number of times of executing the replication operation reaches the maximum number of times of the bacterial replication operation;
if the number of times of executing the copy operation does not reach the maximum number of times of the bacterial copy operation, continuing to execute the tropism operation in the bacterial foraging algorithm;
if the number of times of executing the replication operation reaches the maximum number of times of the bacterial replication operation, judging whether the number of times of bacterial migration reaches the maximum number of times of the bacterial migration operation;
if the bacteria migration times do not reach the maximum times of the bacteria migration operation, migrating the bacteria according to the migration probability, and continuing to execute the tropism operation in the bacterial foraging algorithm;
and if the number of times of bacteria migration reaches the maximum number of times of bacteria migration operation, taking each dimensional position in the 6 dimensional positions included in the global optimal position of the bacteria at the moment as one coefficient in 6 coefficients of the two controllers respectively.
In an embodiment of the present invention, the ending condition may be that the fitness value reaches a certain data or that the fitness value is cycled for a certain number of times.
In one embodiment of the present invention, the fitness function is used as a main index for measuring the optimal performance of the algorithm, and the reasonable design of the fitness function has a critical influence on the performance of the algorithm. For the control of the water-cooling cabinet, the optimization process of the algorithm is defined as searching the minimum power consumption value when the system normally works, namely, in the operation process of the algorithm, the fitness function is continuously optimized, the minimum power consumption is ensured when the system works, and meanwhile, the optimization output result is used as the operation parameter of the PID controller. According to the relationship between the water valve opening and the fan rotating speed to the cooling capacity, the relationship between the fan rotating speed and the energy consumption and the purpose of avoiding the overshoot phenomenon of the system, the method can obtain the fitness function as follows:
wherein, in the formula (6), e (t) is the system error, u (t) is the output of the system, trOutputting stable time for the system, and outputting a difference value between the current output and the last time of the system to measure the overshoot of the system; w is a1、w2、w3And w4The index coefficient of each index is respectively.
When the value of the fitness function J is smaller, the system is better in precision and efficiency, and energy is saved.
When the algorithm runs to the set iteration times, the PID parameter corresponding to the extreme value point of the fitness function is the optimal solution.
The parameters of the fusion algorithm of the particle swarm algorithm and the bacterial foraging algorithm are initialized as follows:
the population number is 30, the dimension is 6, the algorithm iteration number is 200, the learning factor is 2, the particle inertia weight coefficient is 0.75, the maximum bacterial migration operation number is 2, the maximum bacterial replication operation number is 4, the maximum bacterial tropism operation number is 10, the bacterial tropism operation movement step size is 4, and the migration probability is 0.25.
After the system is stabilized, the control parameters of the first controller and the second controller are shown in table 1.
TABLE 1
The opening of a water valve of the water cooling cabinet and the rotating speed of a fan are controlled by PID, and control parameters of the PID controller are determined through a fusion algorithm of a particle swarm algorithm and a bacterial foraging algorithm. The principle of controlling a water-cooled cabinet based on a fusion algorithm is shown in fig. 6. Fig. 6 shows a schematic diagram of a fusion algorithm based control water-cooled cabinet according to an embodiment of the present invention.
As can be seen from fig. 6, the water-cooling cabinet control method according to the embodiment of the present invention adopts a cascade control strategy, that is, the water valve opening and the fan rotation speed are both controlled by PID, and the difference between the water outlet temperature and the water outlet temperature of the water-cooling cabinet monitored by the temperature sensor and the difference between the voltage value corresponding to the water valve opening and the voltage value corresponding to the fan rotation speed monitored by the air volume sensor are given as inputs of a fusion algorithm of a particle swarm optimization and a bacterial foraging algorithm. The fusion algorithm outputs values for 6 dimensions. The value of each dimension is taken as the parameter value of each of the six control parameters (three control parameters of the first controller and three control parameters of the second controller), respectively.
According to the working condition of the water-cooling cabinet, the mathematical model of the water-cooling cabinet can be expressed by a first-order inertia time-lag system. A water-cooled cabinet control model represented as a transfer function of a first order inertia time lag system is shown in fig. 7. Fig. 7 shows a schematic diagram of a water-cooled cabinet control model provided by an embodiment of the present invention.
fig. 8 shows a schematic diagram of temperature adjustment of a water-cooled cabinet provided by an embodiment of the present invention. As can be seen from FIG. 8, the water valve opening and the fan rotating speed of the water cooling cabinet are controlled by PID according to the embodiment of the invention, and compared with the prior art, the water outlet temperature of the water cooling cabinet can reach the given water outlet temperature quickly, and the regulation efficiency is higher.
Fig. 9 shows a schematic diagram of power adjustment of a water-cooling cabinet provided by an embodiment of the present invention. As can be seen from fig. 9, the water valve opening and the fan rotation speed of the water-cooling cabinet are controlled by PID according to the embodiment of the present invention, and compared with the prior art, the power of the water-cooling cabinet can be reduced, and the energy consumption can be saved.
The control method of the embodiment of the invention follows the following principle:
in principle 1, since the control effect of the second controller is most direct and energy-saving, the system interference factor should be adjusted by the second controller as much as possible, the function of the second controller is exerted to the greatest extent, and when the second controller cannot meet the adjustment requirement, the first controller is adjusted.
Corresponding to the method embodiment, the embodiment of the invention also provides a water cooling cabinet control device.
Fig. 10 shows a schematic structural diagram of a water-cooling cabinet control device provided by an embodiment of the invention.
The water-cooled cabinet control device may include:
the acquiring module 101 is used for acquiring the water outlet temperature of the water-cooling cabinet, the rotating speed of a fan of the water-cooling cabinet and the given water outlet temperature;
the determining module 102 is configured to determine, based on the outlet water temperature, the rotation speed, and the given outlet water temperature, a control parameter of a first controller of the water-cooling cabinet and a control parameter of a second controller of the water-cooling cabinet when the outlet water temperature of the water-cooling cabinet reaches the given outlet water temperature and energy consumption of the water-cooling cabinet is minimum.
The first controller is used for controlling the opening of a water valve of the water cooling cabinet, and the second controller is used for controlling the rotating speed of the fan;
the control module 103 is configured to control the opening of a water valve of the water-cooling cabinet based on the control parameter of the first controller, and control the rotation speed of the fan based on the control parameter of the second controller, so as to control the minimum energy consumption of the water-cooling cabinet when the outlet water temperature of the water-cooling cabinet reaches a given outlet water temperature.
In an embodiment of the present invention, the determining module 102 may be specifically configured to:
and determining control parameters of a first controller of the water cooling cabinet and control parameters of a second controller of the water cooling cabinet when the outlet water temperature of the water cooling cabinet reaches the given outlet water temperature and the energy consumption of the water cooling cabinet is minimum by adopting a fusion algorithm of a particle swarm algorithm and a bacterial foraging algorithm based on the outlet water temperature, the rotating speed and the given outlet water temperature.
In an embodiment of the present invention, the obtaining module 101 may be specifically configured to:
detecting the outlet water temperature of the water-cooling cabinet by using a temperature sensor;
and detecting the rotating speed of a fan of the water-cooling cabinet by using the wind speed sensor.
In one embodiment of the invention, the first controller and the second controller are both proportional-integral-derivative controllers; the control parameters include: a proportionality coefficient, an integral coefficient, and a differential coefficient.
Fig. 11 is a block diagram illustrating an exemplary hardware architecture of a computing device capable of implementing the water-cooled cabinet control method and apparatus according to an embodiment of the invention. As shown in fig. 11, computing device 1100 includes an input device 1101, an input interface 1102, a central processor 1103, a memory 1104, an output interface 1105, and an output device 1106. The input interface 1102, the central processor 1103, the memory 1104, and the output interface 1105 are connected to each other via a bus 1110, and the input device 1101 and the output device 1106 are connected to the bus 1110 via the input interface 1102 and the output interface 1105, respectively, and further connected to other components of the computing device 1100.
Specifically, the input device 1101 receives input information from the outside and transmits the input information to the central processor 1103 through the input interface 1102; the central processor 1103 processes the input information based on computer-executable instructions stored in the memory 1104 to generate output information, temporarily or permanently stores the output information in the memory 1104, and then transmits the output information to the output device 1106 through the output interface 1105; the output device 1106 outputs output information external to the computing device 1100 for use by a user.
That is, the computing device shown in fig. 11 may also be implemented as a water-cooled cabinet control device, which may include: a memory storing a computer program; and the processor can realize the water-cooling cabinet control method provided by the embodiment of the invention when executing the computer program.
An embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium; when being executed by a processor, the computer program realizes the water-cooling cabinet control method provided by the embodiment of the invention.
It is to be understood that the invention is not limited to the specific arrangements and instrumentality described above and shown in the drawings. A detailed description of known methods is omitted herein for the sake of brevity. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present invention are not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications and additions or change the order between the steps after comprehending the spirit of the present invention.
The functional blocks shown in the above-described structural block diagrams may be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, plug-in, function card, or the like. When implemented in software, the elements of the invention are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine-readable medium or transmitted by a data signal carried in a carrier wave over a transmission medium or a communication link. A "machine-readable medium" may include any medium that can store or transfer information. Examples of a machine-readable medium include electronic circuits, semiconductor memory devices, ROM, flash memory, Erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, Radio Frequency (RF) links, and so forth. The code segments may be downloaded via computer networks such as the internet, intranet, etc.
It should also be noted that the exemplary embodiments mentioned in this patent describe some methods or systems based on a series of steps or devices. However, the present invention is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, may be performed in an order different from the order in the embodiments, or may be performed simultaneously.
As described above, only the specific embodiments of the present invention are provided, and it can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the system, the module and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again. It should be understood that the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive various equivalent modifications or substitutions within the technical scope of the present invention, and these modifications or substitutions should be covered within the scope of the present invention.
Claims (10)
1. A water-cooled cabinet control method, characterized in that the method comprises:
acquiring the water outlet temperature of a water-cooling cabinet, the rotating speed of a fan of the water-cooling cabinet and a given water outlet temperature;
determining control parameters of a first controller of the water-cooling cabinet and control parameters of a second controller of the water-cooling cabinet when the water outlet temperature of the water-cooling cabinet reaches the given water outlet temperature and the energy consumption of the water-cooling cabinet is minimum based on the water outlet temperature, the rotating speed and the given water outlet temperature; the first controller is used for controlling the opening of a water valve of the water-cooling cabinet, and the second controller is used for controlling the rotating speed of the fan;
and controlling the water valve opening degree of the water-cooling cabinet based on the control parameter of the first controller, and controlling the rotating speed of the fan based on the control parameter of the second controller so as to control the water outlet temperature of the water-cooling cabinet to reach the given water outlet temperature, wherein the energy consumption of the water-cooling cabinet is minimum.
2. The method of claim 1, wherein the determining, based on the outlet water temperature, the rotation speed, and the given outlet water temperature, the control parameters of the first controller of the water-cooling cabinet and the control parameters of the second controller of the water-cooling cabinet when the outlet water temperature of the water-cooling cabinet reaches the given outlet water temperature and the energy consumption of the water-cooling cabinet is minimum comprises:
and determining control parameters of a first controller of the water-cooling cabinet and control parameters of a second controller of the water-cooling cabinet when the water-cooling cabinet has the lowest energy consumption and the water-cooling temperature reaches the given water-outlet temperature by adopting a fusion algorithm of a particle swarm algorithm and a bacterial foraging algorithm based on the water-outlet temperature, the rotating speed and the given water-outlet temperature.
3. The method of claim 1, wherein the obtaining of the outlet water temperature of the water-cooled cabinet, the rotational speed of the fan of the water-cooled cabinet, and the given outlet water temperature comprises:
detecting the outlet water temperature of the water-cooling cabinet by using a temperature sensor;
and detecting the rotating speed of a fan of the water-cooling cabinet by using a wind speed sensor.
4. The method of claim 1, wherein the first controller and the second controller are both proportional integral derivative controllers; the control parameters of the first controller and the control parameters of the second controller include: a proportionality coefficient, an integral coefficient, and a differential coefficient.
5. A water cooled cabinet control apparatus, the apparatus comprising:
the acquisition module is used for acquiring the water outlet temperature of the water-cooling cabinet, the rotating speed of a fan of the water-cooling cabinet and the given water outlet temperature;
the determining module is used for determining control parameters of a first controller of the water-cooling cabinet and control parameters of a second controller of the water-cooling cabinet when the water outlet temperature of the water-cooling cabinet reaches the given water outlet temperature and the energy consumption of the water-cooling cabinet is minimum based on the water outlet temperature, the rotating speed and the given water outlet temperature; the first controller is used for controlling the opening of a water valve of the water-cooling cabinet, and the second controller is used for controlling the rotating speed of the fan;
and the control module is used for controlling the water valve opening degree of the water-cooling cabinet based on the control parameters of the first controller and controlling the rotating speed of the fan based on the control parameters of the second controller so as to control the water outlet temperature of the water-cooling cabinet to reach the given water outlet temperature, wherein the energy consumption of the water-cooling cabinet is minimum.
6. The apparatus of claim 5, wherein the determining module is specifically configured to:
and determining control parameters of a first controller of the water-cooling cabinet and control parameters of a second controller of the water-cooling cabinet when the water-cooling cabinet has the lowest energy consumption and the water-cooling temperature reaches the given water-outlet temperature by adopting a fusion algorithm of a particle swarm algorithm and a bacterial foraging algorithm based on the water-outlet temperature, the rotating speed and the given water-outlet temperature.
7. The apparatus of claim 5, wherein the obtaining module is specifically configured to:
detecting the outlet water temperature of the water-cooling cabinet by using a temperature sensor;
and detecting the rotating speed of a fan of the water-cooling cabinet by using a wind speed sensor.
8. The apparatus of claim 5, wherein the first controller and the second controller are both proportional integral derivative controllers; the control parameters of the first controller and the control parameters of the second controller include: a proportionality coefficient, an integral coefficient, and a differential coefficient.
9. A water-cooled cabinet control apparatus, comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor;
the processor, when executing the computer program, implements the water-cooled cabinet control method of any one of claims 1 to 4.
10. A computer-readable storage medium, wherein the computer-readable storage medium has a computer program stored thereon, and the computer program, when executed by a processor, implements the method of controlling a water-cooling cabinet as recited in any one of claims 1 to 4.
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Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP2180277B1 (en) * | 2008-10-24 | 2015-08-12 | Thermo King Corporation | Controlling chilled state of a cargo |
CN107514731A (en) * | 2017-07-03 | 2017-12-26 | 青岛海尔空调电子有限公司 | The frequency conversion fan control method and air conditioner of handpiece Water Chilling Units |
Family Cites Families (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR101479809B1 (en) * | 2010-04-30 | 2015-02-06 | 김덕모 | Method For Improving Performance Of Heating And Cooling System And Heating and Cooling System Using The Method |
CN103744451A (en) * | 2014-01-23 | 2014-04-23 | 浪潮电子信息产业股份有限公司 | Water-cooling cabinet temperature keeping regulation and control method capable of improving noise and condensed water |
CN204177282U (en) * | 2014-09-12 | 2015-02-25 | 乐山东方动力节能设备有限公司 | Based on the intelligent cooling tower for waterpower fan of PLC VFC |
CN204902662U (en) * | 2015-08-25 | 2015-12-23 | 林尧林 | Adaptive cooling tower fan controller |
CN106438435A (en) * | 2016-12-02 | 2017-02-22 | 英业达科技有限公司 | Temperature control method and cabinet |
CN109711072B (en) * | 2018-12-29 | 2023-04-07 | 北京化工大学 | Seismic vector wave field numerical simulation method and system based on hybrid cluster intelligent algorithm |
-
2019
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Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP2180277B1 (en) * | 2008-10-24 | 2015-08-12 | Thermo King Corporation | Controlling chilled state of a cargo |
CN107514731A (en) * | 2017-07-03 | 2017-12-26 | 青岛海尔空调电子有限公司 | The frequency conversion fan control method and air conditioner of handpiece Water Chilling Units |
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