CN115424783A - Superconducting cable refrigeration control and early warning system and method - Google Patents
Superconducting cable refrigeration control and early warning system and method Download PDFInfo
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Abstract
The invention provides a refrigeration control and early warning system for a superconducting cable, which comprises a sensor, a data processor and a controller, wherein the sensor is used for detecting the refrigeration state of the superconducting cable; the method comprises the following steps that a sensor collects relevant operation data of a superconducting cable refrigerating system, wherein the relevant operation data comprise the temperature of liquid nitrogen at an inlet and an outlet of a superconducting cable terminal, the pressure value of the liquid nitrogen at the inlet and the outlet of the superconducting cable, the flow rate of the liquid nitrogen in the refrigerating system, the water temperature of a water cooling unit, the high and low pressure value of Freon of the water cooling unit and the flow rate of a circulating water cooling system; the data processor carries out preprocessing and feature extraction on related operation data, and then the related operation data are led into a trained superconducting cable refrigeration control and early warning model, and the failure probability, the number of starting refrigerating unit sets and the control frequency of a liquid nitrogen pump are analyzed; the controller controls the superconducting cable refrigerating system according to the number of the started refrigerating units and the control frequency of the liquid nitrogen pump, and determines whether to alarm or not according to the fault probability. The invention can carry out comprehensive and intelligent monitoring, control and early warning on the superconducting cable refrigerating system and has the advantages of strong reliability, high response speed and the like.
Description
Technical Field
The invention relates to the technical field of power systems, in particular to a superconducting cable refrigeration control and early warning system and method.
Background
At present, in the first 10kV three-phase coaxial high-temperature superconducting cable refrigerating system in China, the control method of the inlet and outlet temperature of the supercooled liquid nitrogen of the cable only adopts the traditional upper and lower limit control method, namely, when the temperature exceeds the set upper temperature limit, part of the refrigerating machines are started, and when the temperature is lower than the set lower temperature limit, part of the refrigerating machines are closed. However, the actually required precooling time of the refrigerator is long (about half an hour is needed to reach the rated operation condition), which causes the upper and lower limit control method to have great time-delay property, so that the temperature can not be quickly and effectively adjusted under the condition of fast liquid nitrogen temperature change rate, thereby causing the superconducting quench protection action caused by the exceeding of the liquid nitrogen temperature, and further causing the tripping of the superconducting cable to seriously affect the safe and stable operation of the power system. In addition, the control method for driving the liquid nitrogen pump in the liquid nitrogen circulation in the refrigerating system is a PID control method, namely, a set voltage frequency (converted from a set liquid nitrogen flow rate) of the liquid nitrogen pump is given, and if the liquid nitrogen flow rate is higher or lower than the set flow rate, the system outputs a voltage frequency to the liquid nitrogen pump through a PID controller for regulation. However, when the flow velocity of the liquid nitrogen is suddenly changed, the control method cannot effectively respond, but a certain overshoot amount is generated, so that the flowing stability of the liquid nitrogen in the refrigerating system is influenced, and once the fluctuation range of the flow velocity of the liquid nitrogen is overlarge and exceeds the upper and lower limit thresholds set by the flow velocity, the superconducting cable can be tripped due to the quench protection action. Therefore, it is necessary to effectively control parameters such as the temperature of liquid nitrogen and the circulation frequency of a liquid nitrogen pump in the superconducting cable refrigeration system, so as to efficiently manage the superconducting cable refrigeration system.
However, in practice, some measurement and control quantities inside the superconducting cable refrigeration system have a crucial influence on the operation stability of the superconducting cable refrigeration system. For example, the pressure value of the terminal of the cable at the inlet and the outlet of the superconducting cable can cause the quench protection action once the pressure value is beyond a threshold value; for another example, once the flow and the water temperature of the inlet and the outlet of the water chiller unit are abnormal, the helium compressor is stopped, and then the refrigerator is stopped. However, no corresponding early warning method is established for the measurement and control quantities in the superconducting cable refrigeration system, and data inspection and judgment evaluation are carried out daily only by manpower.
Therefore, it is necessary to provide a superconducting cable refrigeration control and early warning method, which can perform comprehensive and intelligent monitoring, control and early warning on a superconducting cable refrigeration system, and has the advantages of strong reliability, fast response speed, and the like.
Disclosure of Invention
The technical problem to be solved by the embodiments of the present invention is to provide a superconducting cable refrigeration control and early warning system and method, which can perform comprehensive and intelligent monitoring, control and early warning on a superconducting cable refrigeration system, and have the advantages of strong reliability, fast response speed, and the like.
In order to solve the above technical problem, an embodiment of the present invention provides a superconducting cable refrigeration control and early warning system, which is used for a superconducting cable refrigeration system, and includes a sensor, a data processor, and a controller; wherein the content of the first and second substances,
the sensor is used for collecting relevant operation data of the superconducting cable refrigeration system, and the relevant operation data comprises the temperature of liquid nitrogen at an inlet and an outlet of a superconducting cable terminal, the pressure value of liquid nitrogen at an inlet and an outlet of the superconducting cable, the flow rate of liquid nitrogen in the superconducting cable refrigeration system, the water temperature of the water cooling unit, the Freon high-low pressure value of the water cooling unit and the flow rate of the circulating water cooling system;
the data processor is used for preprocessing relevant operation data of the superconducting cable refrigeration system, extracting characteristics of the preprocessed data, importing the extracted characteristic data into a trained superconducting cable refrigeration control and early warning model, and analyzing the fault probability of the superconducting cable refrigeration system, the number of started refrigeration units and the control frequency of a liquid nitrogen pump;
the controller is used for controlling the superconducting cable refrigerating system according to the number of the started refrigerating units and the control frequency of the liquid nitrogen pump, and determining whether to give an alarm to the superconducting cable refrigerating system or not according to the fault probability of the superconducting cable refrigerating system.
The superconducting cable refrigeration control and early warning model adopts a LeNet convolutional neural network model and comprises an input layer, two convolutional layers, two pooling layers, a full-connection layer and an output layer; the input data of the input layer is 64 × 5 three-dimensional data consisting of temperature, pressure and flow after feature extraction; the output types of the output layer are three, including the probability of faults, the number of the started refrigerating units and the control frequency of the liquid nitrogen pump.
The superconducting cable refrigeration control and early warning model is obtained by training and testing a data set formed by preprocessing and characteristic extraction of historical operating data when the superconducting cable refrigeration system fails and historical operating data when the superconducting cable refrigeration system is normal respectively.
The embodiment of the invention also provides a refrigeration control and early warning method for the superconducting cable, which is used for a refrigeration system of the superconducting cable, and the method comprises the following steps:
the sensor collects relevant operation data of the superconducting cable refrigeration system, wherein the relevant operation data comprises the temperature of liquid nitrogen at an inlet and an outlet of a superconducting cable terminal, the pressure value of the liquid nitrogen at the inlet and the outlet of the superconducting cable, the flow rate of the liquid nitrogen in the superconducting cable refrigeration system, the water temperature of a water cooling unit, the high and low pressure numerical value of Freon of the water cooling unit and the flow rate of a circulating water cooling system;
the data processor preprocesses the relevant operation data of the superconducting cable refrigeration system, extracts the characteristics of the preprocessed data, guides the extracted characteristic data into a trained superconducting cable refrigeration control and early warning model, and analyzes the fault probability of the superconducting cable refrigeration system, the number of started refrigeration units and the control frequency of a liquid nitrogen pump;
and the controller controls the superconducting cable refrigeration system according to the number of started refrigeration units and the control frequency of the liquid nitrogen pump, and determines whether to alarm the superconducting cable refrigeration system according to the fault probability of the superconducting cable refrigeration system.
Wherein the method further comprises:
the data processor is used for training and testing data sets formed by preprocessing and characteristic extraction of historical operating data when the superconducting cable refrigerating system fails and historical operating data when the superconducting cable refrigerating system is normal in advance, so that a trained superconducting cable refrigerating control and early warning model is obtained.
The superconducting cable refrigeration control and early warning model adopts a LeNet convolutional neural network model and comprises an input layer, two convolutional layers, two pooling layers, a full-connection layer and an output layer; the input data of the input layer is 64 × 5 three-dimensional data consisting of temperature, pressure and flow after feature extraction; the output types of the output layer are three, including the probability of faults, the number of the started refrigerating units and the control frequency of the liquid nitrogen pump.
Wherein the method further comprises:
the data processor responds when receiving parameters set by a user according to the characteristics of the local refrigeration system, and forms corresponding control quantity according to the set parameters and sends the control quantity to the controller, so that the controller updates the control state of the superconducting cable refrigeration system according to the received control quantity.
The embodiment of the invention has the following beneficial effects:
the invention collects Guan Yun row data such as the temperature of liquid nitrogen at the inlet and the outlet of a superconducting cable terminal, the pressure value of the liquid nitrogen at the inlet and the outlet of the superconducting cable, the flow of the liquid nitrogen in the superconducting cable refrigerating system, the water temperature of a water cooling unit, the high and low pressure value of Freon of the water cooling unit, the flow of a circulating water cooling system and the like based on a sensor, the data are processed by a deep neural network algorithm model (such as a superconducting cable refrigerating control and early warning model) processed by a data processor, a driving controller controls the superconducting cable refrigerating system according to the number of started refrigerating units and the control frequency of the liquid nitrogen pump obtained by the algorithm model, and whether to alarm is determined according to the fault probability obtained by the algorithm model, so that the superconducting cable refrigerating system is comprehensively and intelligently monitored, controlled and early warned, and has the advantages of strong reliability, high response speed and the like.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is within the scope of the present invention for those skilled in the art to obtain other drawings based on the drawings without inventive exercise.
Fig. 1 is a schematic structural diagram of a superconducting cable refrigeration control and warning system according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of the operation of the data processor of FIG. 1;
fig. 3 is a flowchart of a superconducting cable refrigeration control and early warning method according to an embodiment of the present invention.
Detailed Description
To make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings.
As shown in fig. 1, in an embodiment of the present invention, a superconducting cable refrigeration control and early warning system is provided, which is used for a superconducting cable refrigeration system, and includes a sensor 1, a data processor 2, and a controller 3; wherein the content of the first and second substances,
the sensor 1 is used for collecting relevant operation data of the superconducting cable refrigeration system, and comprises liquid nitrogen temperature at an inlet and an outlet of a superconducting cable terminal, liquid nitrogen pressure values at an inlet and an outlet of the superconducting cable, liquid nitrogen flow inside the superconducting cable refrigeration system, water temperature of a water cooling unit, freon high and low pressure values of the water cooling unit and flow of a circulating water cooling system;
the data processor 2 is used for preprocessing relevant operation data of the superconducting cable refrigeration system, extracting characteristics of the preprocessed data, importing the extracted characteristic data into a trained superconducting cable refrigeration control and early warning model, and analyzing the fault probability of the superconducting cable refrigeration system, the number of starting units of the refrigeration unit and the control frequency of the liquid nitrogen pump, wherein the specific flow is shown in fig. 2;
and the controller 3 is used for controlling the superconducting cable refrigerating system according to the number of started refrigerating units and the control frequency of the liquid nitrogen pump, and determining whether to give an alarm to the superconducting cable refrigerating system or not according to the fault probability of the superconducting cable refrigerating system. For example, if the failure probability > threshold P (e.g., 0.5), then an alarm is determined; otherwise, if the failure probability is less than the threshold P (e.g., 0.5), it is determined not to alarm.
It should be noted that, a superconducting cable refrigeration control and early warning model needs to be defined in advance in the data processor 2, and the model adopts a LeNet convolutional neural network model, which includes an input layer, two convolutional layers, two pooling layers, a full-connection layer and an output layer; wherein, the input data of the input layer is 64 × 5 three-dimensional data consisting of temperature, pressure and flow after feature extraction; the output types of the output layer are three, including the probability of failure, the number of the started refrigerating units and the control frequency of the liquid nitrogen pump.
At the moment, the superconducting cable refrigeration control and early warning model is obtained by training and testing a data set formed by preprocessing and characteristic extraction of historical operating data when the superconducting cable refrigeration system fails and historical operating data when the superconducting cable refrigeration system is normal, namely, classifying and marking fault data which have occurred in the operation stage of the superconducting cable refrigeration system and classifying and marking normal data which have occurred, dividing all data into a training group and a testing group, training the superconducting cable refrigeration control and early warning model by using the training group data, and checking the prediction capability of the superconducting cable refrigeration control and early warning model by using the testing group data after the expected accuracy is reached.
The working principle of the superconducting cable refrigeration control and early warning system in the embodiment of the invention is that relevant operation data (liquid nitrogen temperature at an inlet and an outlet of a superconducting cable terminal, liquid nitrogen pressure at an inlet and an outlet of the superconducting cable, liquid nitrogen flow inside the superconducting cable refrigeration system, water temperature of a water-cooling unit, freon high and low voltage numerical value of the water-cooling unit and circulating water cooling system flow) of the superconducting cable refrigeration system which is actually operated are collected through a sensor 1, and after a deep neural network algorithm (namely a superconducting cable refrigeration control and early warning model) in a data processor 2, the corresponding number of starting refrigerators, liquid nitrogen pump control frequency and early warning signals are output and fed back to the superconducting cable refrigeration system, so that the relevant operation data in the superconducting cable refrigeration system can stably fluctuate in a tiny range, and a coping strategy can be rapidly made for sudden change conditions, and the whole superconducting cable refrigeration system is in an extremely high-stability operation state. In addition, the user can set parameters according to the characteristics of the local refrigeration system so as to realize the possibility of mass production and commercial popularization and application of the control and early warning system.
As shown in fig. 3, an embodiment of the present invention provides a superconducting cable refrigeration control and warning method, which is used in a superconducting cable refrigeration system, where the method includes the following steps:
s1, collecting relevant operation data of the superconducting cable refrigerating system by a sensor, wherein the relevant operation data comprise the temperature of liquid nitrogen at an inlet and an outlet of a superconducting cable terminal, the pressure value of liquid nitrogen at an inlet and an outlet of the superconducting cable, the flow rate of liquid nitrogen in the superconducting cable refrigerating system, the water temperature of a water cooling unit, the high and low pressure numerical value of Freon of the water cooling unit and the flow rate of a circulating water cooling system;
s2, preprocessing relevant operation data of the superconducting cable refrigerating system by a data processor, extracting characteristics of the preprocessed data, importing the extracted characteristic data into a trained superconducting cable refrigerating control and early warning model, and analyzing the fault probability of the superconducting cable refrigerating system, the number of started refrigerating units and the control frequency of a liquid nitrogen pump;
and S3, controlling the superconducting cable refrigerating system by the controller according to the starting number of the refrigerating units and the control frequency of the liquid nitrogen pump, and determining whether to give an alarm to the superconducting cable refrigerating system or not according to the fault probability of the superconducting cable refrigerating system.
Wherein the method further comprises:
the data processor is used for training and testing data sets formed by respectively preprocessing and extracting characteristics of historical operating data when the superconducting cable refrigerating system fails and historical operating data when the superconducting cable refrigerating system is normal in advance, and a trained superconducting cable refrigeration control and early warning model is obtained.
The superconducting cable refrigeration control and early warning model adopts a LeNet convolutional neural network model and comprises an input layer, two convolutional layers, two pooling layers, a full-connection layer and an output layer; the input data of the input layer is 64 × 5 three-dimensional data consisting of temperature, pressure and flow after feature extraction; the output types of the output layer are three, including the probability of faults, the number of the started refrigerating units and the control frequency of the liquid nitrogen pump.
Wherein the method further comprises:
the data processor responds when receiving parameters set by a user according to the characteristics of the local refrigeration system, and forms corresponding control quantity according to the set parameters and sends the control quantity to the controller, so that the controller updates the control state of the superconducting cable refrigeration system according to the received control quantity.
The embodiment of the invention has the following beneficial effects:
the invention collects Guan Yun row data such as the temperature of liquid nitrogen at the inlet and the outlet of a superconducting cable terminal, the pressure value of the liquid nitrogen at the inlet and the outlet of the superconducting cable, the flow of the liquid nitrogen in the superconducting cable refrigerating system, the water temperature of a water cooling unit, the high and low pressure value of Freon of the water cooling unit, the flow of a circulating water cooling system and the like based on a sensor, the data are processed by a deep neural network algorithm model (such as a superconducting cable refrigerating control and early warning model) processed by a data processor, a driving controller controls the superconducting cable refrigerating system according to the number of started refrigerating units and the control frequency of the liquid nitrogen pump obtained by the algorithm model, and whether to alarm is determined according to the fault probability obtained by the algorithm model, so that the superconducting cable refrigerating system is comprehensively and intelligently monitored, controlled and early warned, and has the advantages of strong reliability, high response speed and the like.
It will be understood by those skilled in the art that all or part of the steps in the method for implementing the above embodiments may be implemented by relevant hardware instructed by a program, and the program may be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc.
The above disclosure is only for the purpose of illustrating the preferred embodiments of the present invention, and it is therefore to be understood that the invention is not limited by the scope of the appended claims.
Claims (7)
1. A refrigeration control and early warning system for a superconducting cable is used for the refrigeration system for the superconducting cable and is characterized by comprising a sensor, a data processor and a controller; wherein, the first and the second end of the pipe are connected with each other,
the sensor is used for collecting relevant operation data of the superconducting cable refrigeration system, and the relevant operation data comprises the temperature of liquid nitrogen at an inlet and an outlet of a superconducting cable terminal, the pressure value of liquid nitrogen at an inlet and an outlet of the superconducting cable, the flow rate of liquid nitrogen in the superconducting cable refrigeration system, the water temperature of the water cooling unit, the Freon high-low pressure value of the water cooling unit and the flow rate of the circulating water cooling system;
the data processor is used for preprocessing relevant operation data of the superconducting cable refrigeration system, extracting characteristics of the preprocessed data, importing the extracted characteristic data into a trained superconducting cable refrigeration control and early warning model, and analyzing the fault probability of the superconducting cable refrigeration system, the number of started refrigeration units and the control frequency of a liquid nitrogen pump;
the controller is used for controlling the superconducting cable refrigerating system according to the number of the started refrigerating units and the control frequency of the liquid nitrogen pump, and determining whether to give an alarm to the superconducting cable refrigerating system or not according to the fault probability of the superconducting cable refrigerating system.
2. The superconducting cable refrigeration control and warning system as claimed in claim 1, wherein the superconducting cable refrigeration control and warning model is a LeNet convolutional neural network model, which includes an input layer, two convolutional layers, two pooling layers, a full connection layer and an output layer; the input data of the input layer is 64 × 5 three-dimensional data consisting of temperature, pressure and flow after feature extraction; the output types of the output layer are three, including the probability of faults, the number of the started refrigerating units and the control frequency of the liquid nitrogen pump.
3. The superconducting cable refrigeration control and early warning system of claim 2, wherein the superconducting cable refrigeration control and early warning model is obtained by training and testing a data set formed by preprocessing and feature extraction of historical operating data when the superconducting cable refrigeration system fails and historical operating data when the superconducting cable refrigeration system is normal.
4. A superconducting cable refrigeration control and early warning method is used for a superconducting cable refrigeration system and is characterized by comprising the following steps:
the sensor collects relevant operation data of the superconducting cable refrigeration system, wherein the relevant operation data comprises the temperature of liquid nitrogen at an inlet and an outlet of a superconducting cable terminal, the pressure value of the liquid nitrogen at the inlet and the outlet of the superconducting cable, the flow rate of the liquid nitrogen in the superconducting cable refrigeration system, the water temperature of a water cooling unit, the high and low pressure numerical value of Freon of the water cooling unit and the flow rate of a circulating water cooling system;
the data processor preprocesses the relevant operation data of the superconducting cable refrigeration system, extracts the characteristics of the preprocessed data, guides the extracted characteristic data into a trained superconducting cable refrigeration control and early warning model, and analyzes the fault probability of the superconducting cable refrigeration system, the number of started refrigeration units and the control frequency of a liquid nitrogen pump;
and the controller controls the superconducting cable refrigeration system according to the number of started refrigeration units and the control frequency of the liquid nitrogen pump, and determines whether to alarm the superconducting cable refrigeration system according to the fault probability of the superconducting cable refrigeration system.
5. The superconducting cable refrigeration control and early warning method of claim 4, wherein the method further comprises:
the data processor is used for training and testing data sets formed by preprocessing and characteristic extraction of historical operating data when the superconducting cable refrigerating system fails and historical operating data when the superconducting cable refrigerating system is normal in advance, so that a trained superconducting cable refrigerating control and early warning model is obtained.
6. The superconducting cable refrigeration control and early warning method as claimed in claim 5, wherein the superconducting cable refrigeration control and early warning model is a LeNet convolutional neural network model, which includes an input layer, two convolutional layers, two pooling layers, a full connection layer and an output layer; the input data of the input layer is 64 × 5 three-dimensional data consisting of temperature, pressure and flow after feature extraction; the output types of the output layer are three, including the probability of failure, the number of started refrigerating units and the control frequency of the liquid nitrogen pump.
7. The superconducting cable refrigeration control and early warning method of claim 4, wherein the method further comprises:
the data processor responds when receiving parameters set by a user according to the characteristics of the local refrigeration system, and forms corresponding control quantity according to the set parameters and sends the control quantity to the controller, so that the controller updates the control state of the superconducting cable refrigeration system according to the received control quantity.
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| CN116087846A (en) * | 2023-03-17 | 2023-05-09 | 江西联创光电超导应用有限公司 | Superconducting magnet fault detection method and system |
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| CN116087846A (en) * | 2023-03-17 | 2023-05-09 | 江西联创光电超导应用有限公司 | Superconducting magnet fault detection method and system |
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