System and method for remotely monitoring magnetic suspension equipment

Abstract

The invention provides a system and a method for remotely monitoring magnetic suspension equipment. The system comprises management control software, equipment checking software, a magnetic suspension cloud platform and an Internet of Things gateway, the management control software and the equipment checking software are deployed in the terminal; the Internet of Things gateway is mounted on the magnetic suspension equipment; the magnetic suspension cloud platform is in communication connection with the terminal and the Internet of Things gateway through a double-layer encryption transmission protocol; the magnetic suspension cloud platform receives the magnetic suspension equipment alarm information and the magnetic suspension equipment state information sent by the Internet of Things gateway, and analyzes and stores the magnetic suspension equipment alarm information and the magnetic suspension equipment state information; when a viewing instruction sent by the terminal is received, acquiring data corresponding to the viewing instruction and sending the data to the terminal for visual display; and when a control instruction sent by the terminal is received, forwarding the control instruction to the Internet of Things gateway to enable the magnetic suspension equipment to execute the control instruction. The system optimizes the remote monitoring, intelligent diagnosis and automatic adjustment capabilities of the equipment, enhances the data security, and promotes the development of the magnetic suspension equipment towards a more efficient and intelligent direction.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things, and in particular to a system and method for remotely monitoring magnetic levitation equipment. Background Art

[0002] As a high-precision, high-efficiency advanced technology, magnetic levitation equipment is widely used in high-speed transportation, energy, mechanical processing and other fields. However, the current management model of magnetic levitation equipment is still mainly based on local operation and maintenance, and there are many technical bottlenecks, which affect its operational efficiency and intelligence level.

[0003] Because magnetic levitation equipment operates under high load and high speed conditions, it requires precise control and real-time monitoring. However, existing monitoring methods rely on on-site instruments or manual inspections, which cannot obtain core parameters in real time, resulting in delayed abnormal response and affecting equipment safety and reliability. Secondly, traditional fault diagnosis systems only record simple fault codes and lack historical analysis of key parameters such as vibration and pressure. They are unable to conduct remote fault tracing, which increases troubleshooting time and downtime costs. In addition, in terms of parameter adjustment, the equipment still requires manual adjustment and lacks dynamic optimization and adjustment based on changes in operating conditions, which limits the intelligence and automation of the equipment. Furthermore, control authority is decentralized and there is a lack of a centralized remote management platform, resulting in inefficient management. In addition, existing remote monitoring systems have data security risks and are susceptible to tampering or illegal manipulation, increasing security risks.

[0004] Therefore, the technical defects in the current magnetic levitation equipment management model result in low equipment operation and maintenance efficiency and high maintenance costs, making it difficult to adapt to the high requirements of modern industry for intelligent and unmanned operation and maintenance. Summary of the Invention

[0005] In view of this, an embodiment of the present invention provides a system and method for remotely monitoring a magnetic levitation device to solve the problems of low equipment operation and maintenance efficiency and high maintenance costs.

[0006] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:

[0007] The first aspect of the present invention discloses a system for remotely monitoring a magnetic levitation device, the system comprising: management and control software, device viewing software, a magnetic levitation cloud platform, and an Internet of Things gateway;

[0008] The management control software and the device viewing software are deployed in the terminal; the Internet of Things gateway is installed on the magnetic levitation device;

[0009] The magnetic levitation cloud platform communicates with the terminal and the Internet of Things gateway respectively through a double-layer encrypted transmission protocol;

[0010] The magnetic levitation cloud platform receives the magnetic levitation device alarm information and magnetic levitation device status information sent by the Internet of Things gateway, and parses and stores them; when the magnetic levitation cloud platform receives the viewing instruction sent by the terminal, it obtains the data corresponding to the viewing instruction and sends it to the terminal for visual display; when the magnetic levitation cloud platform receives the control instruction sent by the terminal, it forwards it to the Internet of Things gateway to enable the magnetic levitation device to execute the control instruction.

[0011] Preferably, the management and control software includes: a user management module and a device management module;

[0012] The user management module is used to manage user accounts and user devices;

[0013] The device management module is used to manage the magnetic levitation device and generate control instructions according to user operations and send them to the magnetic levitation cloud platform.

[0014] Preferably, the device viewing software includes: a status viewing module and a history information viewing module;

[0015] The status viewing module is used to obtain a list of magnetic levitation devices and magnetic levitation device status information, and to display them visually;

[0016] The historical information viewing module is used to obtain historical magnetic levitation equipment alarm information and historical operation data information, and to display them visually.

[0017] Preferably, the magnetic levitation cloud platform includes: a data processing module, a data storage module and a data analysis module;

[0018] The data processing module is configured to receive the alarm information and status information of the magnetic levitation device in real time and perform standardized analysis; and is further configured to forward, upon receiving a control instruction sent by the terminal, the control instruction to the Internet of Things gateway so that the magnetic levitation device executes the control instruction;

[0019] The data storage module is used to persistently store the standardized parsed magnetic levitation device alarm information and the magnetic levitation device status information in a relational database; and is also used to filter out high-frequency access data from the standardized parsed magnetic levitation device alarm information and the magnetic levitation device status information, and store the high-frequency access data in a memory database;

[0020] The data analysis module is configured to retrieve data corresponding to the viewing instruction from a database upon receiving the viewing instruction sent by the terminal, and send the data to the terminal for visual display.

[0021] Preferably, the magnetic levitation cloud platform further includes:

[0022] A fault tracing module is used to extract parameter information from the status information of the magnetic levitation equipment; use a machine learning algorithm to analyze the parameter information to obtain the dynamic change trend of the parameters and the correlation between each parameter; locate the fault point of the magnetic levitation equipment according to preset rules, the dynamic change trend and the correlation, and generate maintenance suggestion information to send to the terminal.

[0023] Preferably, the Internet of Things gateway includes: an indicator light, a collection module and an analysis module;

[0024] The indicator light is used to display the status of the IoT gateway;

[0025] The acquisition module is used to collect the magnetic levitation device status information of the magnetic levitation device and read the magnetic levitation device alarm information from the register of the controller of the magnetic levitation device, and send the magnetic levitation device status information and the magnetic levitation device alarm information to the magnetic levitation cloud platform;

[0026] The parsing module is used to receive the control instructions forwarded by the magnetic levitation cloud platform and perform protocol parsing and authority verification, and send the control instructions after protocol parsing and authority verification to the corresponding magnetic levitation device so that the magnetic levitation device executes the control instructions.

[0027] A second aspect of the present invention discloses a method for remotely monitoring a magnetic levitation device, the method comprising:

[0028] Collect the maglev equipment status information and maglev equipment alarm information of the maglev equipment through the Internet of Things gateway and send it to the maglev cloud platform;

[0029] Utilizing the magnetic levitation cloud platform to analyze the magnetic levitation device status information and the magnetic levitation device alarm information and store them in a database;

[0030] Generate a viewing instruction based on the user's operation in the management control software and / or the device viewing software, and send the viewing instruction through the terminal;

[0031] When a viewing instruction is received, the data corresponding to the viewing instruction is obtained through the magnetic levitation cloud platform and sent to the terminal for visual display.

[0032] Preferably, the method further comprises:

[0033] Generate a control instruction based on the user's operation in the management control software and / or the device viewing software, and send the control instruction through the terminal;

[0034] forwarding the control instruction to the IoT gateway using the magnetic levitation cloud platform;

[0035] The control instructions are executed by the Internet of Things gateway to control the magnetic levitation device.

[0036] Preferably, the sending of the control instruction through the terminal includes:

[0037] Encrypting the control instructions using a double-layer encryption transmission protocol;

[0038] The encrypted control instruction is sent through the terminal.

[0039] Preferably, the method further comprises:

[0040] extracting parameter information from the magnetic levitation device status information through the magnetic levitation cloud platform;

[0041] Analyzing the parameter information using a machine learning algorithm to obtain dynamic change trends of the parameters and correlations between the parameters;

[0042] Locating the fault point of the magnetic levitation equipment according to the preset rules, the dynamic change trend and the correlation;

[0043] Maintenance suggestion information is generated based on the fault point and sent to the terminal.

[0044] Based on the above-mentioned embodiments of the present invention, a system and method for remotely monitoring a magnetic levitation device are provided. The system includes management and control software, device viewing software, a magnetic levitation cloud platform, and an Internet of Things gateway. The management and control software and device viewing software are deployed in a terminal; the Internet of Things gateway is installed on the magnetic levitation device; the magnetic levitation cloud platform communicates with the terminal and the Internet of Things gateway via a dual-layer encrypted transmission protocol. The magnetic levitation cloud platform receives, parses, and stores magnetic levitation device alarms and status information from the Internet of Things gateway. Upon receiving a viewing command from the terminal, the magnetic levitation cloud platform obtains the data corresponding to the viewing command and sends it to the terminal for visual display. Upon receiving a control command from the terminal, the system forwards the command to the Internet of Things gateway, causing the magnetic levitation device to execute the control command. This system optimizes the device's remote monitoring, intelligent diagnosis, and automatic adjustment capabilities, while enhancing data security and promoting the development of magnetic levitation devices towards greater efficiency and intelligence. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0046] Figure 1A schematic structural diagram of a system for remotely monitoring magnetic levitation equipment provided by an embodiment of the present invention;

[0047] Figure 2 This is an example diagram of the device list interface in the management and control software provided in an embodiment of the present invention;

[0048] Figure 3 This is an example diagram of the command sending list interface in the management control software provided by an embodiment of the present invention;

[0049] Figure 4 This is an example diagram of the real-time operating status interface of the device in the device viewing software provided in an embodiment of the present invention;

[0050] Figure 5 This is an example diagram of the magnetic levitation device list interface in the device viewing software provided in an embodiment of the present invention;

[0051] Figure 6 This is an example diagram of the magnetic levitation device alarm information interface in the device viewing software provided in an embodiment of the present invention;

[0052] Figure 7 This is an example diagram of the historical operation data curve interface in the device viewing software provided by an embodiment of the present invention;

[0053] Figure 8 This is an example diagram of the historical magnetic levitation device alarm information interface in the device viewing software provided in an embodiment of the present invention;

[0054] Figure 9 This is an example diagram of the download interface in the device viewing software provided by an embodiment of the present invention;

[0055] Figure 10 A schematic diagram of an indicator light system for an IoT gateway provided by an embodiment of the present invention;

[0056] Figure 11 This is a flow chart of a method for remotely monitoring a magnetic levitation device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0057] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0058] In this application, the terms "comprises," "comprising," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not preclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0059] As can be seen from the background technology, the existing magnetic levitation equipment monitoring and control system relies on on-site instruments and manual inspections, lacks real-time data acquisition, intelligent fault diagnosis and dynamic optimization and adjustment, has decentralized management and data security risks, affecting the safety, reliability and efficiency of the equipment.

[0060] Therefore, embodiments of the present invention provide a system and method for remotely monitoring a magnetic levitation device. The system comprises management and control software, device viewing software, a magnetic levitation cloud platform, and an Internet of Things gateway. The management and control software and device viewing software are deployed in a terminal; the Internet of Things gateway is installed on the magnetic levitation device. The magnetic levitation cloud platform communicates with the terminal and the Internet of Things gateway via a dual-layer encrypted transmission protocol. The magnetic levitation cloud platform receives, parses, and stores magnetic levitation device alarms and status information from the Internet of Things gateway. Upon receiving a viewing command from the terminal, the magnetic levitation cloud platform obtains the data corresponding to the viewing command and sends it to the terminal for visual display. Upon receiving a control command from the terminal, the data is forwarded to the Internet of Things gateway, causing the magnetic levitation device to execute the control command. The Internet of Things gateway collects magnetic levitation device data in real time, significantly improving the efficiency of device status perception. Combined with the magnetic levitation cloud platform's multi-level data caching mechanism, data response speed is further improved, ensuring efficient data processing. This system optimizes the device's remote monitoring, intelligent diagnosis, and automatic adjustment capabilities while enhancing data security, driving the development of magnetic levitation devices towards greater efficiency and intelligence.

[0061] See also Figure 1 , shows a structural diagram of a system for remotely monitoring magnetic levitation equipment provided by an embodiment of the present invention.

[0062] The system includes: management and control software, equipment viewing software, magnetic levitation cloud platform and Internet of Things gateway.

[0063] Specifically, the management control software and the device viewing software are deployed in a terminal, which can be any electronic device with a display screen that supports data input, including but not limited to a smartphone, tablet computer, portable computer, desktop computer, etc.

[0064] The IoT gateway is installed on a magnetic levitation device.

[0065] It should be noted that the magnetic levitation cloud platform communicates with the terminal and the IoT gateway respectively through a double-layer encrypted transmission protocol (such as Hypertext Transfer Protocol Secure (HTTPS)).

[0066] In actual applications, the maglev cloud platform implements a two-way authentication mechanism with the terminal through the TLS-based message queue telemetry transmission security protocol (MQTT over TLS, MQTTs).

[0067] It is understandable that by adopting a dual-layer encryption transmission protocol and a two-way authentication mechanism, a complete security protection chain from the terminal to the magnetic levitation cloud platform is built. This can effectively improve the encryption strength and anti-tampering capabilities of data transmission, effectively prevent various network attacks, and meet the security protection needs of industrial control systems.

[0068] In the scenario of remote monitoring of magnetic levitation equipment, the magnetic levitation cloud platform receives the magnetic levitation equipment alarm information and magnetic levitation equipment status information sent by the IoT gateway, and parses and stores them; when the magnetic levitation cloud platform receives the viewing instruction sent by the terminal, it obtains the data corresponding to the viewing instruction and sends it to the terminal for visual display; when the magnetic levitation cloud platform receives the control instruction sent by the terminal, it forwards it to the IoT gateway so that the magnetic levitation equipment executes the control instruction.

[0069] The following is a detailed description of each part of the system.

[0070] Specifically, the management and control software includes a user management module and a device management module. The user management module manages user accounts and user devices. The device management module manages the magnetic levitation devices and generates control commands based on user operations and sends them to the magnetic levitation cloud platform. In other words, the management and control software can use the device management module to view a list of active magnetic levitation devices and manage them.

[0071] It should be noted that the list information in the device list uses the HTTPS protocol for end-to-end encrypted transmission. For example, the device list Figure 2 Specifically, in response to the user clicking on the first-level menu corresponding to any device in the device list, the instruction sending list interface (such as Figure 3 (As shown in the figure), the system generates control commands based on user operations in the command sending list interface, such as remote start, remote stop, speed setting, flow setting, and pressure setting. These control commands are then transmitted end-to-end encrypted via the HTTPS protocol to the magnetic levitation cloud platform.

[0072] In actual applications, after receiving the control instructions, the maglev cloud platform implements two-way authenticated transmission of the control instructions through the MQTT over TLS security protocol (MQTTs), and finally sends it to the IoT gateway so that the maglev device can execute the control instructions.

[0073] Specifically, the device viewing software includes: a status viewing module and a historical information viewing module. The status viewing module is used to obtain the list of magnetic levitation devices and the status information of the magnetic levitation devices, and to display them visually. The historical information viewing module is used to obtain historical magnetic levitation device alarm information and historical operating data information, and to display them visually. The status information of the magnetic levitation devices includes but is not limited to the real-time operating status of the magnetic levitation devices (such as Figure 4 shown).

[0074] That is, the device viewing software can view the list of magnetic levitation devices (such as Figure 5 As shown in the figure), real-time operation status, magnetic levitation equipment alarm information (such as Figure 6 as shown) and historical operating data curves (as shown Figure 7 As shown in the figure), as well as historical magnetic levitation equipment alarm information (such as Figure 8 All data transmission is encrypted end-to-end via HTTPS protocol, and supports functions such as viewing historical alarms and downloading historical operation data (e.g. Figure 9 (see the example download interface picture).

[0075] It is understandable that the alarm information of magnetic levitation equipment, such as: chiller alarm, emergency stop alarm, inverter alarm, DC power supply alarm, motor does not rotate after starting, ABM alarm, rotating motor does not levitate, expansion alarm, motor temperature alarm, low suction temperature alarm, high exhaust temperature alarm, etc., has different alarm contents for different magnetic levitation equipment.

[0076] It should be noted that both the management and control software and the device viewing software can be used to add or delete magnetic levitation devices. The remote control function in the management and control software and the device viewing software is provided to users according to business needs.

[0077] Specifically, the Tianrui Magnetic Levitation Cloud Platform is built on the Spring Boot framework, with Java as the core development language for backend logic. The Magnetic Levitation Cloud Platform can be deployed on servers to provide continuous high-availability services. The Magnetic Levitation Cloud Platform performs data processing, data storage, data analysis, command forwarding, and data transmission for maglev equipment, making it the core and hub of the entire system.

[0078] It should be noted that the magnetic levitation cloud platform includes: a data processing module, a data storage module and a data analysis module.

[0079] First, the data processing module is used to receive the alarm information and status information of the magnetic levitation equipment in real time and perform standardized analysis; it is also used to forward the control instructions sent by the terminal to the Internet of Things gateway so that the magnetic levitation equipment can execute the control instructions.

[0080] It should be noted that standardized parsing refers to the conversion and processing of received maglev equipment alarm and status information into a unified format, ensuring that it conforms to the data structure and standards defined by the maglev cloud platform. This ensures that diverse data can be managed and analyzed uniformly on the same platform, ensuring that the system can correctly understand and utilize it regardless of its original format.

[0081] In remote device control scenarios, control commands are transmitted end-to-end encrypted via the HTTPS protocol. Upon receiving the control commands, the maglev cloud platform implements bidirectional authentication via the MQTT over TLS (MQTTs) security protocol. The IoT gateway then sends the commands to the corresponding maglev device for execution. This entire communication link, from the application layer to the IoT layer, utilizes an encrypted transmission system, effectively ensuring tamper-proof control commands and traceability.

[0082] Secondly, the data storage module is used to persistently store the standardized parsed magnetic levitation equipment alarm information and magnetic levitation equipment status information in a relational database; it is also used to filter out high-frequency access data from the standardized parsed magnetic levitation equipment alarm information and magnetic levitation equipment status information, and store the high-frequency access data in the memory database.

[0083] In other words, a hierarchical storage mechanism is adopted: the full amount of data such as the standardized parsed magnetic levitation equipment alarm information and magnetic levitation equipment status information is persistently stored in the MySQL relational database. At the same time, a Redis memory database cache is established for high-frequency access data, and high-frequency access data is stored in the memory database to significantly improve the reading and writing performance of hot data.

[0084] It should be noted that high-frequency access data includes, but is not limited to, real-time operating status information of maglev equipment, real-time alarm information, historical operating data, and other real-time changing content. Low-frequency access data includes, but is not limited to, relatively fixed content such as user names, equipment lists, equipment information, and customer information.

[0085] Third, the data analysis module is used to retrieve the data corresponding to the viewing instruction from the database when receiving the viewing instruction sent by the terminal, and send it to the terminal for visual display.

[0086] That is to say, when receiving a viewing instruction sent by the terminal (such as a device status viewing instruction), the data analysis module responds immediately and accurately retrieves the data corresponding to the viewing instruction from the database (such as real-time operating parameters, historical status records, etc.), and returns it to the terminal through a secure transmission channel for visual display.

[0087] In some specific embodiments, the magnetic levitation cloud platform also includes: a fault tracing module for extracting parameter information from the status information of the magnetic levitation equipment; using a machine learning algorithm to analyze the parameter information to obtain the dynamic change trend of the parameters and the correlation between each parameter; locating the fault point of the magnetic levitation equipment according to preset rules, dynamic change trends and correlations, and generating maintenance recommendation information to send to the terminal.

[0088] Taking a chiller as an example, the maglev cloud platform extracts time-series parameter information (such as motor speed, chilled water inlet temperature, chilled water outlet temperature, cooling water inlet temperature, cooling water outlet temperature, motor temperature, liquid level, exhaust temperature, suction temperature, exhaust pressure, suction pressure, exhaust superheat, motor voltage, motor current, and motor power) from the maglev equipment's status information. It then uses machine learning algorithms (such as intelligent early warning models built based on historical data mining) to analyze the dynamic trends and interrelationships of these parameters. For example, when exhaust pressure rises abnormally, the maglev cloud platform, combined with the time-series fluctuations of parameters such as cooling water temperature and liquid level, can quickly locate the root cause of the fault (such as a clogged cooling tower or insufficient heat dissipation) and automatically generate maintenance recommendations. This reduces fault diagnosis time from hours to minutes, reducing unplanned downtime and extending equipment life.

[0089] As can be seen, machine learning algorithms can analyze the time series of parameters in the maglev equipment's status information and accurately trace the root cause of the fault. Compared with traditional passive maintenance methods, this fault diagnosis method greatly improves efficiency, significantly reduces the equipment's unplanned downtime rate, and effectively extends the service life of the maglev equipment's core components.

[0090] Specifically, the IoT gateway includes: indicator lights, collection modules and analysis modules.

[0091] It's important to note that the IoT Gateway integrates multi-dimensional status monitoring and dual-mode communication capabilities, and its hardware is equipped with multiple sets of highly recognizable indicator light systems. Regarding data flow, the IoT Gateway is deeply coupled with the maglev cloud platform through standardized Modbus and Ethernet communication protocols.

[0092] Among them, the indicator light is used to display the status of the IoT gateway. Figure 10As shown in the schematic diagram, the indicator light system of the IoT gateway includes but is not limited to the RS485 communication status indicator, the PWR power supply indicator, the 4G network signal strength indicator, the LINK server connection status indicator, and the NET module operation indicator, forming a visual device health diagnosis system.

[0093] It should be noted that 485: 485 operation status indicator light, if 485 is not connected, this indicator light will remain off.

[0094] SYS: The indicator light for normal program operation. When the program starts running, this light will flash permanently at a fixed frequency. If the program does not run normally, this light will stop flashing.

[0095] PWR: Circuit board power supply indicator. When the power supply is normal, this indicator will remain on.

[0096] 4G: Signal strength indicator. When the signal is strong, this light remains on. When the signal is medium, this light flashes slowly. When the signal is weak, this light flashes quickly. When the signal strength is no longer detected, this light goes off.

[0097] LINK: Server connection status indicator. When the module is successfully connected to the MQTT server, this light will remain on.

[0098] NET: Gateway module operation status indicator light, flashing at a certain frequency. When there is data transmission, the flashing frequency will change.

[0099] In terms of communication architecture, it supports dual-mode access of RS485 serial communication interface and Ethernet communication interface, and can intelligently switch data interaction channels according to the industrial site environment.

[0100] The acquisition module is used to collect the magnetic levitation device status information of the magnetic levitation device and read the magnetic levitation device alarm information from the register of the magnetic levitation device controller, and send the magnetic levitation device status information and the magnetic levitation device alarm information to the magnetic levitation cloud platform.

[0101] It's understandable that magnetic levitation equipment is controlled by a PLC controller or a PCB controller. Both controllers have alarm detection capabilities, and different alarm types correspond to different alarm codes. When an alarm occurs, the controller stores the alarm information in its registers. The IoT gateway reads the value in the alarm register in real time, processes it through edge computing, and forwards the alarm information to the magnetic levitation cloud platform via the MQTT over TLS encryption protocol. Upon receiving the alarm information, the magnetic levitation cloud platform identifies and stores it, and simultaneously sends the alarm information to the terminal.

[0102] It should be noted that the alarm information is forwarded to the maglev cloud platform through the MQTT over TLS encryption protocol, ensuring the confidentiality and integrity of data transmission.

[0103] The parsing module is used to receive the control instructions forwarded by the magnetic levitation cloud platform and perform protocol parsing and authority verification, and send the control instructions after protocol parsing and authority verification to the corresponding magnetic levitation device so that the magnetic levitation device executes the control instructions.

[0104] That is to say, in the reverse control link, the IoT gateway continuously monitors the control instructions issued by the maglev cloud platform. After protocol analysis and permission verification, the control instructions are accurately delivered to the target maglev equipment through the physical communication interface, completing the complete control closed loop from cloud decision-making to on-site execution, ensuring the real-time and security of remote control of the equipment.

[0105] In this embodiment of the present invention, the dual-mode communication interface and multi-dimensional indicator light system of the IoT gateway enable real-time collection of maglev equipment operating data, supporting multi-protocol adaptation and significantly improving the efficiency of device status perception. Combined with the maglev cloud platform's multi-level data caching mechanism, the response speed for high-frequency data queries reaches industry-leading levels, achieving breakthroughs in the accuracy of real-time monitoring of key operating parameters. This is particularly suitable for industrial control scenarios with strict latency requirements. Furthermore, remote centralized control of equipment via a centralized management platform significantly reduces the average annual operation and maintenance cost of a single device. Furthermore, combined with historical data visualization and analysis capabilities, equipment maintenance decision cycles are significantly shortened, significantly improving overall operation and maintenance efficiency. This is particularly suitable for the intelligent management needs of cross-regional equipment clusters. Overall, the system architecture design conforms to mainstream Industrial IoT standards and supports seamless integration with existing enterprise information systems. Most importantly, the modular software architecture enables rapid iteration, significantly reducing the integration cycle for new device types. This provides the infrastructure support for the intelligent transformation of maglev equipment and digital twin applications, and is adaptable to future industrial upgrades.

[0106] Corresponding to the system for remotely monitoring magnetic levitation equipment in the above embodiment of the present invention, see Figure 11 , shows a flow chart of a method for remotely monitoring a magnetic levitation device according to an embodiment of the present invention, which is applicable to a system for remotely monitoring a magnetic levitation device proposed in the above embodiment. The method includes:

[0107] Step S1101: Collect the magnetic levitation device status information and magnetic levitation device alarm information of the magnetic levitation device through the Internet of Things gateway and send it to the magnetic levitation cloud platform.

[0108] Step S1102: Utilize the magnetic levitation cloud platform to analyze the magnetic levitation equipment status information and magnetic levitation equipment alarm information and store them in the database.

[0109] Step S1103: Generate a viewing instruction based on the user's operation in the management control software and / or the device viewing software, and send the viewing instruction through the terminal.

[0110] Step S1104: When a viewing instruction is received, the data corresponding to the viewing instruction is obtained through the magnetic levitation cloud platform and sent to the terminal for visual display.

[0111] It should be noted that the specific implementation of steps S1101 to S1104 is detailed in the above Figures 1 to 10 The content shown will not be repeated here.

[0112] In some specific embodiments, control instructions are first generated based on the user's operations in the management control software and / or device viewing software, and the control instructions are sent through the terminal; then the control instructions are forwarded to the Internet of Things gateway using the magnetic levitation cloud platform; finally, the control instructions are executed through the Internet of Things gateway to control the magnetic levitation device.

[0113] It should be noted that when a control instruction is sent through a terminal, the control instruction is first encrypted using a double-layer encryption transmission protocol; and then the encrypted control instruction is sent through the terminal.

[0114] Clearly, the closed-loop control algorithm enables coordinated adjustment of multiple parameters, with millisecond-level control command transmission links and advanced control accuracy in industrial control. Compared to traditional on-site manual adjustment methods, this approach significantly improves the efficiency of process parameter optimization and is particularly suitable for complex applications requiring rapid switching between operating conditions.

[0115] In another embodiment, parameter information is first extracted from the status information of the magnetic levitation equipment through the magnetic levitation cloud platform; secondly, the parameter information is analyzed using a machine learning algorithm to obtain the dynamic change trend of the parameters and the correlation between each parameter; then, the fault point of the magnetic levitation equipment is located according to preset rules, dynamic change trends and correlations; finally, maintenance recommendation information is generated based on the fault point and sent to the terminal.

[0116] In this embodiment, the IoT gateway collects real-time maglev equipment operating data, improving equipment status awareness. Combined with the maglev cloud platform's multi-level data caching mechanism, high-frequency data query response speeds reach industry-leading levels, achieving breakthroughs in the accuracy of monitoring key operating parameters. This approach is particularly suitable for latency-sensitive industrial scenarios. Combined with visual analysis of historical data, this significantly shortens equipment maintenance decision cycles and improves operational efficiency.

[0117] Each embodiment in this specification is described in a progressive manner. The same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. In particular, for system or system embodiments, since they are basically similar to method embodiments, the description is relatively simple. For relevant parts, refer to the partial description of the method embodiment. The system and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without expending creative work.

[0118] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the components and steps of each example according to their functions. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0119] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A system for remotely monitoring a magnetic levitation device, characterized in that: The system includes: management and control software, equipment viewing software, magnetic levitation cloud platform and Internet of Things gateway; The management control software and the device viewing software are deployed in the terminal; the Internet of Things gateway is installed on the magnetic levitation device; The magnetic levitation cloud platform communicates with the terminal and the Internet of Things gateway respectively through a double-layer encrypted transmission protocol; The magnetic levitation cloud platform receives the magnetic levitation device alarm information and magnetic levitation device status information sent by the Internet of Things gateway, and parses and stores them; when the magnetic levitation cloud platform receives the viewing instruction sent by the terminal, it obtains the data corresponding to the viewing instruction and sends it to the terminal for visual display; when the magnetic levitation cloud platform receives the control instruction sent by the terminal, it forwards it to the Internet of Things gateway to enable the magnetic levitation device to execute the control instruction.

2. The system according to claim 1, wherein: The management and control software includes: a user management module and a device management module; The user management module is used to manage user accounts and user devices; The device management module is used to manage the magnetic levitation device and generate control instructions according to user operations and send them to the magnetic levitation cloud platform.

3. The system according to claim 1, wherein: The device viewing software includes: a status viewing module and a historical information viewing module; The status viewing module is used to obtain a list of magnetic levitation devices and magnetic levitation device status information, and to display them visually; The historical information viewing module is used to obtain historical magnetic levitation equipment alarm information and historical operation data information, and to display them visually.

4. The system according to claim 1, wherein: The magnetic levitation cloud platform includes: a data processing module, a data storage module and a data analysis module; The data processing module is configured to receive the alarm information and status information of the magnetic levitation device in real time and perform standardized analysis; and is further configured to forward, upon receiving a control instruction sent by the terminal, the control instruction to the Internet of Things gateway so that the magnetic levitation device executes the control instruction; The data storage module is used to persistently store the standardized parsed magnetic levitation device alarm information and the magnetic levitation device status information in a relational database; and is also used to filter out high-frequency access data from the standardized parsed magnetic levitation device alarm information and the magnetic levitation device status information, and store the high-frequency access data in a memory database; The data analysis module is configured to retrieve data corresponding to the viewing instruction from a database upon receiving the viewing instruction sent by the terminal, and send the data to the terminal for visual display.

5. The system according to claim 1, wherein: The magnetic levitation cloud platform also includes: A fault tracing module is used to extract parameter information from the status information of the magnetic levitation equipment; use a machine learning algorithm to analyze the parameter information to obtain the dynamic change trend of the parameters and the correlation between each parameter; locate the fault point of the magnetic levitation equipment according to preset rules, the dynamic change trend and the correlation, and generate maintenance suggestion information to send to the terminal.

6. The system according to claim 1, wherein: The IoT gateway includes: an indicator light, a collection module and an analysis module; The indicator light is used to display the status of the IoT gateway; The acquisition module is used to collect the magnetic levitation device status information of the magnetic levitation device and read the magnetic levitation device alarm information from the register of the controller of the magnetic levitation device, and send the magnetic levitation device status information and the magnetic levitation device alarm information to the magnetic levitation cloud platform; The parsing module is used to receive the control instructions forwarded by the magnetic levitation cloud platform and perform protocol parsing and authority verification, and send the control instructions after protocol parsing and authority verification to the corresponding magnetic levitation device so that the magnetic levitation device executes the control instructions.

7. A method for remotely monitoring a magnetic levitation device, characterized in that: The method comprises: Collect the maglev equipment status information and maglev equipment alarm information of the maglev equipment through the Internet of Things gateway and send it to the maglev cloud platform; Utilizing the magnetic levitation cloud platform to analyze the magnetic levitation device status information and the magnetic levitation device alarm information and store them in a database; Generate a viewing instruction based on the user's operation in the management control software and / or the device viewing software, and send the viewing instruction through the terminal; When a viewing instruction is received, the data corresponding to the viewing instruction is obtained through the magnetic levitation cloud platform and sent to the terminal for visual display.

8. The method according to claim 7, characterized in that The method further comprises: Generate a control instruction based on the user's operation in the management control software and / or the device viewing software, and send the control instruction through the terminal; forwarding the control instruction to the IoT gateway using the magnetic levitation cloud platform; The control instructions are executed by the Internet of Things gateway to control the magnetic levitation device.

9. The method according to claim 8, characterized in that The sending of the control instruction through the terminal includes: Encrypting the control instructions using a double-layer encryption transmission protocol; The encrypted control instruction is sent through the terminal.

10. The method according to claim 7, characterized in that The method further comprises: extracting parameter information from the magnetic levitation device status information through the magnetic levitation cloud platform; Analyzing the parameter information using a machine learning algorithm to obtain dynamic change trends of the parameters and correlations between the parameters; Locating the fault point of the magnetic levitation equipment according to the preset rules, the dynamic change trend and the correlation; Maintenance suggestion information is generated based on the fault point and sent to the terminal.

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