A determination method and system of a vehicle-mounted superconducting magnet monitoring system and a storage medium

Abstract

Embodiments of the present application provide a kind of vehicle-mounted superconducting magnet monitoring system determination method, system and storage medium, wherein, method includes: obtaining the identification of vehicle-mounted superconducting magnet and multiple sampling parameter information, obtain the initial monitoring system corresponding to the identification of vehicle-mounted superconducting magnet, based on each sampling parameter information and magnet structure information, each sensor and monitoring module in monitoring system are selected, the identification of each sensor and monitoring module is obtained respectively, based on the preset mapping relationship, the identification of each sensor and the identification of monitoring module are added to the respective target position in initial monitoring system respectively, and based on the identification of each sensor and the identification of monitoring module, initial monitoring system is corrected, and the initial monitoring system after parameter correction is determined as the vehicle-mounted superconducting magnet monitoring system matched with the identification of vehicle-mounted superconducting magnet.The design efficiency of vehicle-mounted superconducting magnet monitoring system is improved.

Description

Technical Field

[0001] This invention relates to the field of vehicle-mounted equipment design technology, and in particular to a method, system, and storage medium for determining a vehicle-mounted superconducting magnet monitoring system. Background Technology

[0002] Maglev trains are vehicles that achieve levitation by utilizing the interaction between an onboard superconducting magnet and a track levitation coil. The operational stability of the onboard superconducting magnet is a crucial factor affecting the stable operation of a maglev train. Therefore, a magnet monitoring system is needed to monitor the operating parameters of the onboard superconducting magnet.

[0003] However, the speed changes and steering of maglev trains during operation cause variations in parameters such as the temperature, magnetic field strength, and shape of the superconducting magnets. This makes the design methods for static superconducting magnet monitoring systems unsuitable for onboard superconducting magnet data acquisition systems. Furthermore, the parameter variations differ between different maglev train models, requiring manual design of magnet monitoring systems for each model, leading to reduced design efficiency. Summary of the Invention

[0004] The purpose of this invention is to provide a method, system, and storage medium for determining a vehicle-mounted superconducting magnet monitoring system, thereby improving the design efficiency of such systems. The specific technical solution is as follows:

[0005] A method for determining a vehicle-mounted superconducting magnet monitoring system, the method comprising:

[0006] The identification and multiple sampling parameter information of the vehicle-mounted superconducting magnet are obtained, including: parameter type identification and multiple other sampling parameters;

[0007] An initial monitoring system corresponding to the identification of the vehicle-mounted superconducting magnet is obtained. The initial monitoring system includes the installation position, installation method, wiring position between each installation position, and parameters of the supporting components of each component in the monitoring system.

[0008] Based on the sampling parameter information and magnet structure information, the sensors and monitoring modules in the monitoring system are selected, and the identifiers of each sensor and monitoring module are obtained respectively. The magnet structure information corresponds to the identifier of the vehicle-mounted superconducting magnet.

[0009] Based on a preset mapping relationship, the identifiers of each sensor and the identifier of each monitoring module are added to their respective target locations in the initial monitoring system, and the parameters of the initial monitoring system are corrected based on the identifiers of each sensor and the identifier of each monitoring module.

[0010] The initial monitoring system, after being corrected by the parameters, is determined to be a vehicle-mounted superconducting magnet monitoring system that matches the identification of the vehicle-mounted superconducting magnet.

[0011] Optionally, the selection of each sensor and monitoring module in the monitoring system based on the sampling parameter information and magnet structure information, and the acquisition of the identifiers of each sensor and monitoring module, includes:

[0012] For each sampling parameter information: identify multiple candidate sensors that correspond to the parameter type identifier in the sampling parameter information, and filter each candidate sensor based on the comprehensive matching degree of each of the other sampling parameters and the design parameter group of the candidate sensor to obtain one sensor and its identifier;

[0013] Based on the identifiers of each sensor, the output data type of each sensor is obtained. Based on the output data type and the magnet structure information, each candidate monitoring module is screened to obtain one monitoring module and its identifier.

[0014] Optionally, the step of filtering each of the candidate sensors based on the comprehensive matching degree between each of the other sampling parameters and the design parameter group of the candidate sensors to obtain one sensor and its identifier includes:

[0015] For each candidate sensor: determine whether the value of the sampling sensitivity parameter is within the sampling sensitivity range of the candidate sensor; if so, output a positive matching identifier, where the sampling sensitivity parameter is one of the other sampling parameters and the sampling sensitivity range is one of the design parameter groups; determine whether the signal frequency is within the frequency response range of the candidate sensor; if so, output a positive matching identifier, where the signal frequency is one of the other sampling parameters and the frequency response range is one of the design parameter groups; determine whether the operating stability identifier is consistent with the operating condition identifier of the candidate sensor; if so, output a positive matching identifier, where the operating stability identifier is one of the other sampling parameters and the operating condition identifier is one of the design parameter groups; determine whether the installation method identifier is consistent with the assembly identifier of the candidate sensor; if so, output a positive matching identifier, where the installation method identifier is one of the other sampling parameters and the assembly identifier is one of the design parameter groups; determine the total number of positive matching identifiers as the overall matching degree of the candidate sensor;

[0016] The candidate sensor with the highest overall matching degree among all the candidate sensors is determined as the sensor, and the identifier of the sensor is obtained.

[0017] Optionally, the step of filtering each candidate monitoring module based on the output data type and the magnet structure information to obtain one monitoring module and its identifier includes:

[0018] For each alternative monitoring module:

[0019] Based on each of the output data types, obtain the transmission rate corresponding to each of the output data types; determine whether the sampling data type group of the candidate monitoring module includes each of the output data types; if so, determine whether the sampling efficiency of the candidate monitoring module is not less than the sum of the transmission rates.

[0020] If the sampling efficiency is not less than the sum of the transmission rates, determine whether the number of channels of the alternative monitoring module is not less than the total number of the output data types.

[0021] If the number of channels is not less than the total number of output data types, determine whether each type of operating condition interval in the operating condition parameter group of the candidate monitoring module is located within its corresponding magnet internal environment parameter interval. If so, the candidate monitoring module is determined as the monitoring module, and the identifier of the monitoring module is obtained. The magnet internal environment parameter interval is a parameter in the magnet structure information, and the magnet internal environment parameter interval has a corresponding relationship with the operating condition interval.

[0022] Optionally, the parameter correction of the initial monitoring system based on the identifiers of each sensor and the identifier of the monitoring module includes:

[0023] Identification of each sensor: Based on the sensor identifier, identify the identifiers of each component that is connected to the sensor; obtain the component installation parameters corresponding to each component identifier in the initial monitoring system, and obtain the sensor installation parameters corresponding to the sensor identifier in the initial monitoring system; display the component installation parameters and the sensor installation parameters through a preset human-machine interface, and obtain the user's installation parameter correction results for the component installation parameters and the sensor installation parameters;

[0024] Based on the identifier of the monitoring module, the identifiers of each auxiliary module that interacts with the monitoring module are determined from the initial monitoring system, and the configuration parameters of each auxiliary module are obtained based on the identifier of each auxiliary module; the configuration parameters of the monitoring module and the configuration parameters of each auxiliary module are displayed through the preset human-computer interaction interface, and the user's configuration parameter correction results for the configuration parameters of each auxiliary module are obtained.

[0025] Based on the installation parameter correction results and the configuration parameter correction results, the parameters of the initial monitoring system are corrected.

[0026] Optionally, before the step of determining the initial monitoring system, after parameter correction, as a vehicle-mounted superconducting magnet monitoring system matching the identifier of the vehicle-mounted superconducting magnet, the method further includes:

[0027] Based on the output data type of each sensor, a target monitoring program package is extracted from a preset database and loaded into the processor of the monitoring module. The target monitoring program package is a preset program package used to parse each output data type and determine the magnet state based on each output data type.

[0028] A determination system for a vehicle-mounted superconducting magnet monitoring system, the system comprising:

[0029] The first data acquisition module is used to acquire the identification of the vehicle-mounted superconducting magnet and multiple sampling parameter information, the sampling parameter information including: parameter type identification and multiple other sampling parameters;

[0030] The second data acquisition module is used to acquire the initial monitoring system corresponding to the identification of the vehicle-mounted superconducting magnet. The initial monitoring system includes the installation position, installation method, wiring position between each installation position, and parameters of the supporting components of each component in the monitoring system.

[0031] The equipment selection module is used to select each sensor and monitoring module in the monitoring system based on the sampling parameter information and magnet structure information, and obtain the identifiers of each sensor and monitoring module respectively, wherein the magnet structure information has a corresponding relationship with the identifier of the vehicle-mounted superconducting magnet;

[0032] The data filling module is used to add the identifiers of each sensor and the identifier of the monitoring module to their respective target positions in the initial monitoring system based on a preset mapping relationship, and to correct the parameters of the initial monitoring system based on the identifiers of each sensor and the identifier of the monitoring module.

[0033] The system determination module is used to determine the initial monitoring system, after parameter correction, as a vehicle-mounted superconducting magnet monitoring system that matches the identifier of the vehicle-mounted superconducting magnet.

[0034] Optionally, the equipment selection module is configured as follows:

[0035] For each sampling parameter information: identify multiple candidate sensors that correspond to the parameter type identifier in the sampling parameter information, and filter each candidate sensor based on the comprehensive matching degree of each of the other sampling parameters and the design parameter group of the candidate sensor to obtain one sensor and its identifier;

[0036] Based on the identifiers of each sensor, the output data type of each sensor is obtained. Based on the output data type and the magnet structure information, each candidate monitoring module is screened to obtain one monitoring module and its identifier.

[0037] Optionally, when the device selection module filters the candidate sensors based on the comprehensive matching degree between each of the other sampling parameters and the design parameter group of the candidate sensors to obtain a sensor and its identifier, it is set to:

[0038] For each candidate sensor: determine whether the value of the sampling sensitivity parameter is within the sampling sensitivity range of the candidate sensor; if so, output a positive matching identifier, where the sampling sensitivity parameter is one of the other sampling parameters and the sampling sensitivity range is one of the design parameter groups; determine whether the signal frequency is within the frequency response range of the candidate sensor; if so, output a positive matching identifier, where the signal frequency is one of the other sampling parameters and the frequency response range is one of the design parameter groups; determine whether the operating stability identifier is consistent with the operating condition identifier of the candidate sensor; if so, output a positive matching identifier, where the operating stability identifier is one of the other sampling parameters and the operating condition identifier is one of the design parameter groups; determine whether the installation method identifier is consistent with the assembly identifier of the candidate sensor; if so, output a positive matching identifier, where the installation method identifier is one of the other sampling parameters and the assembly identifier is one of the design parameter groups; determine the total number of positive matching identifiers as the overall matching degree of the candidate sensor;

[0039] The candidate sensor with the highest overall matching degree among all the candidate sensors is determined as the sensor, and the identifier of the sensor is obtained.

[0040] Optionally, when the device selection module filters each candidate monitoring module based on each of the output data types and the magnet structure information to obtain a monitoring module and its identifier, it is set to:

[0041] For each alternative monitoring module:

[0042] Based on each of the output data types, obtain the transmission rate corresponding to each of the output data types; determine whether the sampling data type group of the candidate monitoring module includes each of the output data types; if so, determine whether the sampling efficiency of the candidate monitoring module is not less than the sum of the transmission rates.

[0043] If the sampling efficiency is not less than the sum of the transmission rates, determine whether the number of channels of the alternative monitoring module is not less than the total number of the output data types.

[0044] If the number of channels is not less than the total number of output data types, determine whether each type of operating condition interval in the operating condition parameter group of the candidate monitoring module is located within its corresponding magnet internal environment parameter interval. If so, the candidate monitoring module is determined as the monitoring module, and the identifier of the monitoring module is obtained. The magnet internal environment parameter interval is a parameter in the magnet structure information, and the magnet internal environment parameter interval has a corresponding relationship with the operating condition interval.

[0045] Optionally, the data filling module is configured to: correct the parameters of the initial monitoring system based on the identifiers of each sensor and the identifier of the monitoring module.

[0046] Identification of each sensor: Based on the sensor identifier, identify the identifiers of each component that is connected to the sensor; obtain the component installation parameters corresponding to each component identifier in the initial monitoring system, and obtain the sensor installation parameters corresponding to the sensor identifier in the initial monitoring system; display the component installation parameters and the sensor installation parameters through a preset human-machine interface, and obtain the user's installation parameter correction results for the component installation parameters and the sensor installation parameters;

[0047] Based on the identifier of the monitoring module, the identifiers of each auxiliary module that interacts with the monitoring module are determined from the initial monitoring system, and the configuration parameters of each auxiliary module are obtained based on the identifier of each auxiliary module; the configuration parameters of the monitoring module and the configuration parameters of each auxiliary module are displayed through the preset human-computer interaction interface, and the user's configuration parameter correction results for the configuration parameters of each auxiliary module are obtained.

[0048] Based on the installation parameter correction results and the configuration parameter correction results, the parameters of the initial monitoring system are corrected.

[0049] Optionally, the system further includes:

[0050] The program loading module is used to extract a target monitoring program package from a preset database according to the output data types of each sensor before determining the initial monitoring system after parameter correction as a vehicle-mounted superconducting magnet monitoring system that matches the identifier of the vehicle-mounted superconducting magnet, and load the target monitoring program package into the processor of the monitoring module. The target monitoring program package is a preset program package used to parse each output data type and determine the magnet status based on each output data type.

[0051] A determination system for a vehicle-mounted superconducting magnet monitoring system, the determination system comprising:

[0052] processor;

[0053] Memory used to store the processor's executable instructions;

[0054] The processor is configured to execute the instructions to implement the determination method of the vehicle-mounted superconducting magnet monitoring system as described above.

[0055] A computer-readable storage medium, when the instructions in the computer-readable storage medium are executed by a processor of a determination system of a vehicle-mounted superconducting magnet monitoring system, enables the determination system to perform the determination method of the vehicle-mounted superconducting magnet monitoring system as described above.

[0056] The method, system, and storage medium for determining a vehicle-mounted superconducting magnet monitoring system provided in this invention can determine the basic design parameters of the system by obtaining sampling parameter information. By obtaining an initial monitoring system, this invention eliminates the need for researchers to repeatedly perform extensive theoretical verification and parameter design compared to existing technologies. Instead, it directly obtains an editable monitoring system design drawing, and subsequent steps involve adding and correcting parameters to obtain the design drawing of the vehicle-mounted superconducting magnet monitoring system. Simultaneously, based on the sampling parameter information and magnet structure information, the invention selects various sensors and monitoring modules in the monitoring system, omitting the step in existing technologies where designers need to consult numerous experimental parameters for component selection. Finally, by obtaining relevant component parameters based on the identifiers of each sensor and monitoring module, and correcting the parameters of the initial monitoring system based on these parameters, the design accuracy and efficiency of the final vehicle-mounted superconducting magnet monitoring system are improved. Therefore, this invention improves the design efficiency of vehicle-mounted superconducting magnet monitoring systems.

[0057] Of course, any product or method implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0058] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0059] Figure 1 A flowchart illustrating a method for determining a vehicle-mounted superconducting magnet monitoring system provided in an embodiment of the present invention;

[0060] Figure 2 A block diagram of a determination system for a vehicle-mounted superconducting magnet monitoring system is provided as an optional embodiment of the present invention;

[0061] Figure 3 A block diagram of a determination system for a vehicle-mounted superconducting magnet monitoring system, provided as another optional embodiment of the present invention. Detailed Implementation

[0062] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0063] This invention provides a method for determining a vehicle-mounted superconducting magnet monitoring system, such as... Figure 1 As shown, the determination method includes:

[0064] S101. Obtain the identification of the vehicle-mounted superconducting magnet and multiple sampling parameter information, including: parameter type identification and multiple other sampling parameters.

[0065] It should be noted that, in practical application scenarios, the markings on the aforementioned vehicle-mounted superconducting magnets can be assigned after the vehicle-mounted superconducting magnets have undergone structural design and the structure has been finalized, in order to distinguish different models of vehicle-mounted superconducting magnets.

[0066] Optionally, in one alternative embodiment of the present invention, the aforementioned sampling parameter information may be parameter information that needs to be monitored during the operation of the vehicle-mounted superconducting magnet. The aforementioned sampling parameter information can be determined based on the type approval test data of the vehicle-mounted superconducting magnet. Specifically, the variable parameters and related information of the vehicle-mounted superconducting magnet whose values ​​change due to changes in operating state during the type approval test are determined as the aforementioned sampling parameter information.

[0067] Optionally, in another alternative embodiment of the present invention, the aforementioned parameter type identifier can be an identifier used to distinguish different types of sampling parameters. It should be noted that the types of the aforementioned sampling parameters can be various, including but not limited to: structural stress, temperature, vacuum level, magnetic field strength, etc.

[0068] It should be noted that, in practical applications, the other sampling parameters mentioned above are parameters used to characterize the associated information of this type of sampling parameter. For example, the numerical range, sensitivity level, and signal frequency of this type of sampling parameter. There is a correspondence between the parameter type identifiers and multiple other sampling parameters.

[0069] By obtaining the above-mentioned sampling parameter information, this invention enables the determination of the basic design parameters of the vehicle-mounted superconducting magnet monitoring system.

[0070] S102. Obtain the initial monitoring system corresponding to the identification of the vehicle-mounted superconducting magnet. The initial monitoring system includes the installation position, installation method, wiring position between each installation position, and parameters of the supporting components of each component in the monitoring system.

[0071] Optionally, in one alternative embodiment of the present invention, the aforementioned initial monitoring system may be an editable structural diagram of an onboard superconducting magnet. The initial monitoring system may be constructed as follows: based on the type-approval test data of the onboard superconducting magnet, determine the generation locations of various variable parameters within the onboard superconducting magnet, and determine the variable parameter types corresponding to each generation location. Simultaneously, based on the structural characteristics, material characteristics, and environmental characteristics of the variable parameter generation locations, determine the installation process data, supporting component parameters, and wiring paths between components for arranging sensors at those locations. Finally, based on the variable parameter types, determine the sensor types that need to be deployed at each variable parameter generation location, and establish a mapping relationship between the generation locations of each variable parameter, sensor types, wiring paths, supporting component parameters, and installation process data. This results in an initial monitoring system that includes the installation locations of each component, installation methods, wiring positions between installation locations, and supporting component parameters.

[0072] By obtaining the aforementioned initial monitoring system, this invention eliminates the need for researchers to repeatedly perform extensive theoretical verification and parameter design compared to existing technologies. Instead, it directly obtains editable design drawings that include the installation positions, installation methods, wiring positions between installation positions, and parameters of supporting components in the monitoring system. By adding and modifying the parameters in subsequent steps, the design drawings of the vehicle-mounted superconducting magnet monitoring system can be obtained, thus improving design efficiency.

[0073] S103. Based on the sampling parameter information and magnet structure information, select the sensors and monitoring modules in the monitoring system and obtain the identification of each sensor and monitoring module. The magnet structure information corresponds to the identification of the vehicle-mounted superconducting magnet.

[0074] Optionally, in one alternative embodiment of the present invention, the aforementioned magnet structure information may be information characterizing the internal environmental parameters of the vehicle-mounted superconducting magnet. For example, the temperature, magnetic field strength, and interference levels of various regions within the vehicle-mounted superconducting magnet.

[0075] Optionally, in another alternative embodiment of the present invention, the monitoring module described above can be a functional module for collecting, summarizing, and processing data from various sensors. It should be noted that in practical applications, the data collected by each sensor is different, and the output data is mostly analog signal data. However, the monitoring module needs to perform complex processing on the sensor data, which requires a digital signal processor capable of loading complex algorithms. Therefore, the detection module needs to be equipped with an analog-to-digital (AD) converter circuit to convert analog signals into digital signals, thus converting the analog signals output by the sensors into digital signals that the processor can recognize.

[0076] It should be noted that in practical applications, the number of sensors mentioned above will vary depending on the structural differences of different models of automotive superconductors. Therefore, to improve design redundancy, the digital signal processor mentioned above can be a field-programmable gate array (FPGA).

[0077] It should be noted that in practical applications, the magnetic field inside the onboard superconducting magnet can interfere with the analog signal output by the sensor during operation. Therefore, to improve the data quality input to the processor and reduce interference, a filtering circuit can also be configured in the aforementioned monitoring module.

[0078] It should be noted that, in practical application scenarios, the specific models and configuration information of the AD circuit, FPGA and filter circuit in the above monitoring module can be set according to the specific model parameters of the vehicle-mounted superconducting magnet. This invention will not impose too many restrictions or elaborate on this.

[0079] This invention selects sensors and monitoring modules in the monitoring system based on sampling parameter information and magnet structure information, eliminating the step in the prior art that requires designers to consult a large number of test parameters for component selection, thus improving design efficiency.

[0080] S104. Based on the preset mapping relationship, add the identifiers of each sensor and the identifiers of the monitoring module to their respective target positions in the initial monitoring system, and correct the parameters of the initial monitoring system based on the identifiers of each sensor and the identifiers of the monitoring module.

[0081] It should be noted that in practical applications, since the installation parameters of each target location in the initial monitoring system are based on experimental data, there is design redundancy to ensure compatibility with the component sizes of different monitoring system models. Therefore, this invention obtains relevant component parameters based on the identifiers of each sensor and monitoring module, and corrects parameters in the initial monitoring system, such as component installation location, wiring location, and cable type, based on these parameters, thereby improving the design accuracy of the final vehicle-mounted superconducting magnet monitoring system.

[0082] S105. The initial monitoring system after parameter correction is determined to be a vehicle-mounted superconducting magnet monitoring system that matches the identification of the vehicle-mounted superconducting magnet.

[0083] This invention determines the basic design parameters of a vehicle-mounted superconducting magnet monitoring system by obtaining sampling parameter information. By acquiring an initial monitoring system, this invention eliminates the need for researchers to repeatedly perform extensive theoretical verification and parameter design compared to existing technologies. Instead, it directly obtains an editable monitoring system design drawing, and subsequent steps involve adding and correcting parameters to obtain the design drawing of the vehicle-mounted superconducting magnet monitoring system. Simultaneously, based on the sampling parameter information and magnet structure information, the invention selects various sensors and monitoring modules in the monitoring system, omitting the step in existing technologies where designers need to consult numerous experimental parameters for component selection. Finally, by obtaining relevant component parameters based on the identifiers of each sensor and monitoring module, and correcting the parameters of the initial monitoring system based on these parameters, the invention improves the design accuracy and efficiency of the final vehicle-mounted superconducting magnet monitoring system. Therefore, this invention significantly improves the design efficiency of vehicle-mounted superconducting magnet monitoring systems.

[0084] Optionally, based on the sampling parameter information and magnet structure information, the sensors and monitoring modules in the monitoring system are selected, and the identifiers of each sensor and monitoring module are obtained, including:

[0085] For each sampling parameter information: identify multiple candidate sensors that correspond to the parameter type identifier in the sampling parameter information, and screen each candidate sensor based on the comprehensive matching degree of the design parameter group of each other sampling parameter and candidate sensor to obtain a sensor and its identifier;

[0086] Based on the identifiers of each sensor, the output data type of each sensor is obtained. Based on the output data type and magnet structure information, each candidate monitoring module is screened to obtain a monitoring module and its identifier.

[0087] Optionally, in one alternative embodiment of the present invention, the candidate sensors corresponding to the parameter type identifier can be sensors whose data acquisition data is consistent with the parameter type identifier. For example, if the parameter type identifier is an identifier representing a temperature parameter, then the candidate sensors can be different models of temperature sensors. If the parameter type identifier is an identifier representing a magnetic field strength, then the candidate sensors can be different models of Hall sensors.

[0088] Optionally, based on the comprehensive matching degree between each other sampling parameter and the design parameter group of the candidate sensors, each candidate sensor is screened to obtain a sensor and its identifier, including:

[0089] For each candidate sensor: Determine if the value of the sampling sensitivity parameter is within the sampling sensitivity range of the candidate sensor. If so, output a positive matching identifier. Here, the sampling sensitivity parameter is one of the other sampling parameters, and the sampling sensitivity range is one of the design parameter groups. Determine if the signal frequency is within the frequency response range of the candidate sensor. If so, output a positive matching identifier. Here, the signal frequency is one of the other sampling parameters, and the frequency response range is one of the design parameter groups. Determine if the operating stability identifier is consistent with the operating condition identifier of the candidate sensor. If so, output a positive matching identifier. Here, the operating stability identifier is one of the other sampling parameters, and the operating condition identifier is one of the design parameter groups. Determine if the installation method identifier is consistent with the assembly identifier of the candidate sensor. If so, output a positive matching identifier. Here, the installation method identifier is one of the other sampling parameters, and the assembly identifier is one of the design parameter groups. The total number of positive matching identifiers is determined as the overall matching degree of the candidate sensor.

[0090] The sensor with the highest overall matching degree among all candidate sensors is selected as the sensor, and its identifier is obtained.

[0091] Optionally, based on the data types of each output and the magnet structure information, each candidate monitoring module is screened to obtain a monitoring module and its identifier, including:

[0092] For each alternative monitoring module:

[0093] Based on each output data type, obtain the transmission rate corresponding to each output data type; determine whether the sampling data type group of the candidate monitoring module includes each output data type; if so, determine whether the sampling efficiency of the candidate monitoring module is not less than the sum of the transmission rates.

[0094] Provided that the sampling efficiency is not less than the sum of the transmission rates, determine whether the number of channels of the candidate monitoring module is not less than the total number of output data types.

[0095] If the number of channels is not less than the total number of output data types, determine whether each type of operating condition interval in the operating condition parameter group of the candidate monitoring module is located within its corresponding magnetic internal environment parameter interval. If so, the candidate monitoring module is determined as the monitoring module and the identification of the monitoring module is obtained. The magnetic internal environment parameter interval is a parameter in the magnetic structure information, and the magnetic internal environment parameter interval has a corresponding relationship with the operating condition interval.

[0096] Optionally, in one alternative embodiment of the present invention, the operating condition parameter set of the monitoring module can be a data set constructed based on the environmental parameters required for the stable operation of each component in the monitoring module. For example, the range of magnetic field strength, the range of temperature, and the range of vacuum that allow for normal operation.

[0097] Optionally, based on the identifiers of each sensor and the identifiers of the monitoring module, the initial monitoring system parameters are corrected, including:

[0098] Sensor identification: Based on the sensor identification, identify the identification of each component that is connected to the sensor; obtain the component installation parameters corresponding to each component identification in the initial monitoring system, and obtain the sensor installation parameters corresponding to the sensor identification in the initial monitoring system; display the component installation parameters and sensor installation parameters through a preset human-machine interface, and obtain the user's installation parameter correction results for the component installation parameters and sensor installation parameters;

[0099] Based on the identifier of the monitoring module, identify the identifiers of each auxiliary module that interacts with the monitoring module from the initial monitoring system, and obtain the configuration parameters of each auxiliary module based on the identifier of each auxiliary module; display the configuration parameters of the monitoring module and each auxiliary module through a preset human-computer interaction interface, and obtain the user's configuration parameter correction results for each auxiliary module.

[0100] Based on the results of the installation parameter correction and the configuration parameter correction, the parameters of the initial monitoring system are corrected.

[0101] Optionally, before determining the initial monitoring system, after parameter correction, as a vehicle-mounted superconducting magnet monitoring system that matches the identification of the vehicle-mounted superconducting magnet, the above-mentioned... Figure 1 The determination method shown also includes:

[0102] Based on the output data types of each sensor, the target monitoring program package is extracted from the preset database and loaded into the processor of the monitoring module. The target monitoring program package is a preset program package used to parse each output data type and determine the magnet status based on each output data type.

[0103] It should be noted that in practical applications, for the purpose of monitoring and displaying data from the vehicle-mounted superconducting magnet and monitoring system, in addition to loading the target detection program package into the aforementioned processor, communication protocol packages and interactive interface programs can also be loaded so that the host computer can manage and display the data.

[0104] Corresponding to the above-described method embodiments, the present invention also provides a determination system for a vehicle-mounted superconducting magnet monitoring system, such as... Figure 2 As shown, the determining system includes:

[0105] The first data acquisition module 201 is used to acquire the identification of the vehicle-mounted superconducting magnet and multiple sampling parameter information, including: parameter type identification and multiple other sampling parameters;

[0106] The second data acquisition module 202 is used to acquire the initial monitoring system corresponding to the identification of the vehicle-mounted superconducting magnet. The initial monitoring system includes the installation position, installation method, wiring position between each installation position, and parameters of the supporting components of each component in the monitoring system.

[0107] The equipment selection module 203 is used to select each sensor and monitoring module in the monitoring system based on the sampling parameter information and magnet structure information, and obtain the identification of each sensor and monitoring module. The magnet structure information corresponds to the identification of the vehicle-mounted superconducting magnet.

[0108] The data filling module 204 is used to add the identifiers of each sensor and the identifiers of the monitoring module to their respective target positions in the initial monitoring system based on a preset mapping relationship, and to correct the parameters of the initial monitoring system based on the identifiers of each sensor and the identifiers of the monitoring module.

[0109] The system determination module 205 is used to determine the initial monitoring system after parameter correction as a vehicle-mounted superconducting magnet monitoring system that matches the identification of the vehicle-mounted superconducting magnet.

[0110] Optionally, the above-mentioned equipment selection module 203 is configured as follows:

[0111] For each sampling parameter information: identify multiple candidate sensors that correspond to the parameter type identifier in the sampling parameter information, and screen each candidate sensor based on the comprehensive matching degree of the design parameter group of each other sampling parameter and candidate sensor to obtain a sensor and its identifier;

[0112] Based on the identifiers of each sensor, the output data type of each sensor is obtained. Based on the output data type and magnet structure information, each candidate monitoring module is screened to obtain a monitoring module and its identifier.

[0113] Optionally, when the above-mentioned equipment selection module 203 filters candidate sensors based on the comprehensive matching degree between other sampling parameters and the design parameter group of candidate sensors to obtain a sensor and its identifier, it is set to:

[0114] For each candidate sensor: Determine if the value of the sampling sensitivity parameter is within the sampling sensitivity range of the candidate sensor. If so, output a positive matching identifier. Here, the sampling sensitivity parameter is one of the other sampling parameters, and the sampling sensitivity range is one of the design parameter groups. Determine if the signal frequency is within the frequency response range of the candidate sensor. If so, output a positive matching identifier. Here, the signal frequency is one of the other sampling parameters, and the frequency response range is one of the design parameter groups. Determine if the operating stability identifier is consistent with the operating condition identifier of the candidate sensor. If so, output a positive matching identifier. Here, the operating stability identifier is one of the other sampling parameters, and the operating condition identifier is one of the design parameter groups. Determine if the installation method identifier is consistent with the assembly identifier of the candidate sensor. If so, output a positive matching identifier. Here, the installation method identifier is one of the other sampling parameters, and the assembly identifier is one of the design parameter groups. The total number of positive matching identifiers is determined as the overall matching degree of the candidate sensor.

[0115] The sensor with the highest overall matching degree among all candidate sensors is selected as the sensor, and its identifier is obtained.

[0116] Optionally, when the above-mentioned equipment selection module 203 filters each candidate monitoring module based on the data types of each output type and the magnet structure information to obtain a monitoring module and its identifier, it is set to:

[0117] For each alternative monitoring module:

[0118] Based on each output data type, obtain the transmission rate corresponding to each output data type; determine whether the sampling data type group of the candidate monitoring module includes each output data type; if so, determine whether the sampling efficiency of the candidate monitoring module is not less than the sum of the transmission rates.

[0119] Provided that the sampling efficiency is not less than the sum of the transmission rates, determine whether the number of channels of the candidate monitoring module is not less than the total number of output data types.

[0120] If the number of channels is not less than the total number of output data types, determine whether each type of operating condition interval in the operating condition parameter group of the candidate monitoring module is located within its corresponding magnetic internal environment parameter interval. If so, the candidate monitoring module is determined as the monitoring module and the identification of the monitoring module is obtained. The magnetic internal environment parameter interval is a parameter in the magnetic structure information, and the magnetic internal environment parameter interval has a corresponding relationship with the operating condition interval.

[0121] Optionally, the data filling module 204 described above is configured to perform parameter correction on the initial monitoring system based on the identifiers of each sensor and the identifiers of the monitoring module:

[0122] Sensor identification: Based on the sensor identification, identify the identification of each component that is connected to the sensor; obtain the component installation parameters corresponding to each component identification in the initial monitoring system, and obtain the sensor installation parameters corresponding to the sensor identification in the initial monitoring system; display the component installation parameters and sensor installation parameters through a preset human-machine interface, and obtain the user's installation parameter correction results for the component installation parameters and sensor installation parameters;

[0123] Based on the identifier of the monitoring module, identify the identifiers of each auxiliary module that interacts with the monitoring module from the initial monitoring system, and obtain the configuration parameters of each auxiliary module based on the identifier of each auxiliary module; display the configuration parameters of the monitoring module and each auxiliary module through a preset human-computer interaction interface, and obtain the user's configuration parameter correction results for each auxiliary module.

[0124] Based on the results of the installation parameter correction and the configuration parameter correction, the parameters of the initial monitoring system are corrected.

[0125] Optionally, the above are as follows: Figure 2 The determination system shown also includes:

[0126] The program loading module is used to extract the target monitoring program package from the preset database according to the output data type of each sensor before determining the vehicle-mounted superconducting magnet monitoring system that matches the identifier of the vehicle-mounted superconducting magnet after the parameter correction of the initial monitoring system. The target monitoring program package is a preset program package used to parse each output data type and determine the magnet status based on each output data type.

[0127] This invention also provides a determination system for a vehicle-mounted superconducting magnet monitoring system, such as... Figure 3 As shown, the determining system includes:

[0128] Processor 301;

[0129] Memory 302 is used to store executable instructions of processor 301;

[0130] The processor 301 is configured to execute instructions to implement the determination method of the vehicle-mounted superconducting magnet monitoring system as described above.

[0131] This invention also provides a computer-readable storage medium, which, when the instructions in the computer-readable storage medium are executed by the processor of the determination system of the vehicle-mounted superconducting magnet monitoring system, enables the determination system to perform the determination method of the vehicle-mounted superconducting magnet monitoring system as described above.

[0132] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and memory includes at least one memory chip. Memory is an example of computer-readable media.

[0133] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0134] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0135] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0136] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0137] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for determining a vehicle-mounted superconducting magnet monitoring system, characterized in that, The method includes: The identification and multiple sampling parameter information of the vehicle-mounted superconducting magnet are obtained, including: parameter type identification and multiple other sampling parameters; An initial monitoring system corresponding to the identification of the vehicle-mounted superconducting magnet is obtained. The initial monitoring system includes the installation position, installation method, wiring position between each installation position, and parameters of the supporting components of each component in the monitoring system. Based on the sampling parameter information and magnet structure information, the sensors and monitoring modules in the monitoring system are selected, and the identifiers of each sensor and monitoring module are obtained respectively. The magnet structure information corresponds to the identifier of the vehicle-mounted superconducting magnet. The magnet structure information is information characterizing the internal environmental parameters of the vehicle-mounted superconducting magnet, including the temperature, magnetic field strength and interference degree of each region inside the vehicle-mounted superconducting magnet. Based on a preset mapping relationship, the identifiers of each sensor and the identifier of each monitoring module are added to their respective target locations in the initial monitoring system, and the parameters of the initial monitoring system are corrected based on the identifiers of each sensor and the identifier of each monitoring module. The initial monitoring system, after being corrected by the aforementioned parameters, is determined to be a vehicle-mounted superconducting magnet monitoring system that matches the identification of the vehicle-mounted superconducting magnet. Specifically, based on the sampling parameter information and magnet structure information, the sensors and monitoring modules in the monitoring system are selected, and the identifiers of each sensor and monitoring module are obtained, including: For each sampling parameter information: Multiple candidate sensors corresponding to the parameter type identifier in the sampling parameter information are identified. Based on the comprehensive matching degree between each of the other sampling parameters and the design parameter group of the candidate sensors, each candidate sensor is screened to obtain one sensor and its identifier. This includes: For each candidate sensor: determining whether the value of the sampling sensitivity parameter is within the sampling sensitivity range of the candidate sensor; if so, a positive matching identifier is output, where the sampling sensitivity parameter is one of the other sampling parameters, and the sampling sensitivity range is one of the design parameter group; determining whether the signal frequency is within the frequency response range of the candidate sensor; if so, a positive matching identifier is output, where... The signal frequency is one of the other sampling parameters, and the frequency response range is one of the design parameter groups. The system determines whether the operating stability indicator matches the operating condition indicator of the candidate sensor; if so, a positive matching indicator is output. The operating stability indicator is one of the other sampling parameters, and the operating condition indicator is one of the design parameter groups. The system also determines whether the installation method identifier matches the assembly identifier of the candidate sensor; if so, a positive matching indicator is output. The installation method identifier is one of the other sampling parameters, and the assembly identifier is one of the design parameter groups. The total number of positive matching identifiers is determined as the overall matching degree of the candidate sensor. The candidate sensor with the highest overall matching degree among all the candidate sensors is determined as the sensor, and the identifier of the sensor is obtained; Based on the identifiers of each sensor, the output data type of each sensor is obtained. Based on the output data type and the magnet structure information, each candidate monitoring module is screened to obtain one monitoring module and its identifier.

2. The method according to claim 1, characterized in that, The step of filtering each candidate monitoring module based on the output data type and the magnet structure information to obtain one monitoring module and its identifier includes: For each alternative monitoring module: Based on each of the output data types, obtain the transmission rate corresponding to each of the output data types; determine whether the sampling data type group of the candidate monitoring module includes each of the output data types; if so, determine whether the sampling efficiency of the candidate monitoring module is not less than the sum of the transmission rates. If the sampling efficiency is not less than the sum of the transmission rates, determine whether the number of channels of the alternative monitoring module is not less than the total number of the output data types. If the number of channels is not less than the total number of output data types, determine whether each type of operating condition interval in the operating condition parameter group of the candidate monitoring module is located within its corresponding magnet internal environment parameter interval. If so, the candidate monitoring module is determined as the monitoring module, and the identifier of the monitoring module is obtained. The magnet internal environment parameter interval is a parameter in the magnet structure information, and the magnet internal environment parameter interval has a corresponding relationship with the operating condition interval.

3. The method according to claim 1, characterized in that, The parameter correction of the initial monitoring system based on the identifiers of each sensor and the identifier of the monitoring module includes: Identification of each sensor: Based on the sensor identifier, identify the identifiers of each component that is connected to the sensor; obtain the component installation parameters corresponding to each component identifier in the initial monitoring system, and obtain the sensor installation parameters corresponding to the sensor identifier in the initial monitoring system; display the component installation parameters and the sensor installation parameters through a preset human-machine interface, and obtain the user's installation parameter correction results for the component installation parameters and the sensor installation parameters; Based on the identifier of the monitoring module, the identifiers of each auxiliary module that interacts with the monitoring module are determined from the initial monitoring system, and the configuration parameters of each auxiliary module are obtained based on the identifier of each auxiliary module; the configuration parameters of the monitoring module and the configuration parameters of each auxiliary module are displayed through the preset human-computer interaction interface, and the user's configuration parameter correction results for the configuration parameters of each auxiliary module are obtained. Based on the installation parameter correction results and the configuration parameter correction results, the parameters of the initial monitoring system are corrected.

4. The method according to claim 1, characterized in that, Prior to the step of determining the initial monitoring system, after parameter correction, as a vehicle-mounted superconducting magnet monitoring system matching the identifier of the vehicle-mounted superconducting magnet, the method further includes: Based on the output data type of each sensor, a target monitoring program package is extracted from a preset database and loaded into the processor of the monitoring module. The target monitoring program package is a preset program package used to parse each output data type and determine the magnet state based on each output data type.

5. A determination system for a vehicle-mounted superconducting magnet monitoring system, characterized in that, The system includes: The first data acquisition module is used to acquire the identification of the vehicle-mounted superconducting magnet and multiple sampling parameter information, the sampling parameter information including: parameter type identification and multiple other sampling parameters; The second data acquisition module is used to acquire the initial monitoring system corresponding to the identification of the vehicle-mounted superconducting magnet. The initial monitoring system includes the installation position, installation method, wiring position between each installation position, and parameters of the supporting components of each component in the monitoring system. The equipment selection module is used to select each sensor and monitoring module in the monitoring system based on the sampling parameter information and magnet structure information, and obtain the identifiers of each sensor and monitoring module respectively. The magnet structure information corresponds to the identifier of the vehicle-mounted superconducting magnet. The magnet structure information is information characterizing the internal environmental parameters of the vehicle-mounted superconducting magnet, including the temperature, magnetic field strength and interference of each region inside the vehicle-mounted superconducting magnet. The data filling module is used to add the identifiers of each sensor and the identifier of the monitoring module to their respective target positions in the initial monitoring system based on a preset mapping relationship, and to correct the parameters of the initial monitoring system based on the identifiers of each sensor and the identifier of the monitoring module. The system determination module is used to determine the initial monitoring system after parameter correction as a vehicle-mounted superconducting magnet monitoring system that matches the identifier of the vehicle-mounted superconducting magnet; The equipment selection module, based on the sampling parameter information and magnet structure information, selects each sensor and monitoring module in the monitoring system, and obtains the identifiers of each sensor and monitoring module, specifically for: For each sampling parameter information: Multiple candidate sensors corresponding to the parameter type identifier in the sampling parameter information are identified. Based on the comprehensive matching degree between each of the other sampling parameters and the design parameter group of the candidate sensors, each candidate sensor is screened to obtain one sensor and its identifier. This includes: For each candidate sensor: determining whether the value of the sampling sensitivity parameter is within the sampling sensitivity range of the candidate sensor; if so, a positive matching identifier is output, where the sampling sensitivity parameter is one of the other sampling parameters, and the sampling sensitivity range is one of the design parameter group; determining whether the signal frequency is within the frequency response range of the candidate sensor; if so, a positive matching identifier is output, where... The signal frequency is one of the other sampling parameters, and the frequency response range is one of the design parameter groups. The system determines whether the operating stability indicator matches the operating condition indicator of the candidate sensor; if so, a positive matching indicator is output. The operating stability indicator is one of the other sampling parameters, and the operating condition indicator is one of the design parameter groups. The system also determines whether the installation method identifier matches the assembly identifier of the candidate sensor; if so, a positive matching indicator is output. The installation method identifier is one of the other sampling parameters, and the assembly identifier is one of the design parameter groups. The total number of positive matching identifiers is determined as the overall matching degree of the candidate sensor. The candidate sensor with the highest overall matching degree among all the candidate sensors is determined as the sensor, and the identifier of the sensor is obtained; Based on the identifiers of each sensor, the output data type of each sensor is obtained. Based on the output data type and the magnet structure information, each candidate monitoring module is screened to obtain one monitoring module and its identifier.

6. The system according to claim 5, characterized in that, The system also includes: The program loading module is used to extract a target monitoring program package from a preset database according to the output data types of each sensor before determining the initial monitoring system after parameter correction as a vehicle-mounted superconducting magnet monitoring system that matches the identifier of the vehicle-mounted superconducting magnet, and load the target monitoring program package into the processor of the monitoring module. The target monitoring program package is a preset program package used to parse each output data type and determine the magnet state based on each output data type.

7. A determination system for a vehicle-mounted superconducting magnet monitoring system, characterized in that, The determining system includes: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the determination method of the vehicle-mounted superconducting magnet monitoring system as described in any one of claims 1 to 4.

8. A computer-readable storage medium, characterized in that, When the instructions in the computer-readable storage medium are executed by the processor of the determination system of the vehicle-mounted superconducting magnet monitoring system, the determination system is able to perform the determination method of the vehicle-mounted superconducting magnet monitoring system as described in any one of claims 1 to 4.

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