Intelligent airflow dryer

Abstract

The invention relates to the technical field of dryers, and discloses an intelligent airflow dryer which comprises an Internet of Things module used for connecting the intelligent airflow dryer with a cloud platform and a user terminal, supporting multi-protocol conversion, realizing communication and data transmission of equipment and meanwhile having the characteristics of energy conservation and low power consumption; the dryer device group comprises a plurality of dryer devices of different types and different brands, each dryer device is provided with a corresponding assembly used for observing the operation information and state information parameters of the device in real time, and meanwhile an execution mechanism is arranged in the device and used for receiving and executing a control instruction; the intelligent control terminal comprises intelligent equipment operated by a user. The environment sensing and intelligent adjusting module is adopted, the temperature, humidity and air pressure in the cavity can be monitored in real time, and it is ensured that equipment adapts to variable working environments by dynamically adjusting operation parameters. According to the technical scheme, the effect of stable operation is achieved, and the drying efficiency is greatly optimized.

Description

Technical Field

[0001] The invention relates to the technical field of dryers, and in particular to an intelligent airflow dryer. Background Art

[0002] Airflow dryer is a device commonly used in laboratories for drying glassware. It mainly dries glassware by delivering normal temperature airflow or heated airflow, and will not leave water stains in the glassware. It has the advantages of fast, energy-saving, no water stains, easy to use, and simple maintenance. Although this type of equipment has certain basic functions, it still exposes many problems in complex application scenarios.

[0003] 1. Most of the devices in the prior art rely on fixed parameters to operate and lack the ability to perceive changes in the environment inside the cavity. This means that when the ambient humidity or temperature fluctuates, the device cannot dynamically adjust the operating state. For example, in an environment with high humidity, the drying efficiency is significantly reduced, and the user may need to manually adjust the operating parameters, which not only increases the complexity of the operation, but also easily leads to energy waste and incomplete drying due to inaccurate settings.

[0004] 2. The problem of uniform airflow distribution is another major defect of existing equipment. In current technology, airflow is usually delivered to the cavity through a fixed direction or simple air duct design, and this structure is difficult to adapt to the drying needs of different positions of the utensils. Uneven airflow coverage will lead to incomplete drying in some areas, while other areas may have excess energy. This limitation not only reduces the drying quality, but also greatly increases the operating cost.

[0005] 3. At the control level, most traditional devices use local buttons or knobs to adjust parameters, which is neither intuitive nor flexible, and the user experience is poor. In addition, existing devices lack remote control and permission management functions, which can easily lead to misoperation or management confusion when multiple users use them at the same time. This problem is particularly prominent in laboratories or industrial scenarios that require multi-device collaboration, and management efficiency is extremely low.

[0006] 4. Current technology also has deficiencies in informationization and data interaction. The working status of most devices cannot be recorded in real time or uploaded to the management platform, which leads to the isolation and dispersion of data. Especially in large-scale equipment usage scenarios, it is impossible to centrally monitor and analyze the operation of equipment, and the operation and maintenance costs increase significantly. At the same time, the inability to share data also limits the ability of equipment to collaborate with other management systems, making it difficult to meet the needs of intelligent management.

[0007] From the above analysis, it can be seen that although the existing technology can meet the basic drying needs, it has significant deficiencies in environmental adaptability, airflow distribution, control operation and information management.

[0008] Therefore, the present invention proposes an intelligent airflow dryer to solve the deficiencies of the prior art. Summary of the invention

[0009] In view of the deficiencies of the prior art, the present invention provides an intelligent airflow dryer, which solves the problem that although the prior art can meet basic drying needs, it has significant deficiencies in environmental adaptability, airflow distribution, control operation and information management.

[0010] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent airflow dryer, comprising: an Internet of Things module, used to connect the intelligent airflow dryer with a cloud platform and a user terminal, supporting multi-protocol conversion, realizing communication and data transmission of the device, and having the characteristics of energy saving and low power consumption; The dryer equipment group includes multiple dryer equipment of different types and brands. Each dryer equipment is equipped with corresponding components for real-time observation of the equipment's operating information and status information parameters. At the same time, the equipment is equipped with an actuator for receiving and executing control instructions; Smart control terminal, including a user-operated smart device for remotely monitoring and controlling the dryer equipment through a dedicated application; Intelligent management system, used to record equipment operation data, analyze equipment status, push equipment failure warning information, and interact with other systems; Environmental sensing and intelligent adjustment module, which is used to monitor the temperature, humidity and air pressure in the cavity in real time, and dynamically adjust the equipment operating parameters according to environmental changes to optimize drying efficiency; The intelligent airflow optimization module is used to calculate the airflow distribution based on the airflow model in the cavity, and to achieve uniform airflow coverage and energy consumption optimization in the cavity by adjusting the airflow direction and wind speed.

[0011] Preferably, the Internet of Things module includes: Multi-protocol conversion subunit, used to realize conversion between RS485, Modbus, MQTT and other protocols; RF transceiver, integrated into the energy-saving MCU, for wireless data communication; The data processing module is used to convert the format, detect anomalies and correct them for device data to ensure the accuracy and stability of data transmission.

[0012] Preferably, the drying machine equipment comprises: Draining table, located on top of the dryer unit, for placing glassware and collecting liquid left over from the drying process; The coding knob is set on the front panel of the device and is used to adjust the drying parameters by rotation; The LCD touch screen is set on the front panel of the device to display the device operating status and parameters, and supports user touch operation to select functions; The glassware rack is located outside the equipment and is used to fix glassware of different sizes to prevent the glassware from sliding or tipping over during the drying process; A drying port is arranged on the outside of the glassware placement rack and is used to convey airflow into the glassware for drying; The power interface is set on the side of the device and is used to provide power to the device.

[0013] Preferably, the intelligent control terminal includes: User operation interface, supports remote control of equipment operation, parameter adjustment and query of equipment historical data; The permission management function sets different operation permissions according to user roles to ensure the security of device management.

[0014] Preferably, the intelligent management system includes: Data analysis and storage module, used to record equipment operating parameters and perform visual analysis of data; The alarm and notification module is used to generate fault alarms according to the equipment operation status and push them to the user terminal; The collaborative work module supports integration with laboratory management systems or enterprise resource planning systems to achieve information sharing and collaboration.

[0015] Preferably, the environment perception and intelligent adjustment module includes: Temperature and humidity sensor, used to collect real-time air temperature and humidity data in the cavity; Air pressure sensor, used to monitor the pressure distribution of airflow in the cavity; The regulating mechanism, including the wind speed controller and the temperature regulator, adjusts the airflow intensity and temperature in real time according to the collected environmental parameters; remote monitoring and control: the user sets the equipment operating parameters through the smart terminal, the system generates control instructions and sends them to the equipment, and the equipment feeds back the results after execution to achieve closed-loop operation.

[0016] Preferably, the intelligent airflow optimization module includes: The air flow distributor controls the opening degree of the air flow valve through a servo motor to achieve dynamic adjustment of the air flow direction and intensity; The control unit calculates the optimal distribution plan of the airflow in the cavity based on the airflow distribution model and optimization algorithm, and generates control instructions to send to the airflow distributor.

[0017] Preferably, the intelligent management system realizes equipment operation control through the following steps: Device initialization: The IoT module reads the basic information of the device, uploads it to the intelligent management system, completes device registration and generates an initialization configuration file; Data collection and upload: Real-time collection of equipment operating parameters and upload to the cloud platform through the Internet of Things module. The data is stored in the database after preliminary processing; Remote monitoring and control: Users set equipment operating parameters through smart terminals, the system generates control instructions and sends them to the equipment, and the equipment feedbacks the results after execution.

[0018] Preferably, the intelligent management system supports the generation of multiple data reports, the report contents include: Equipment operating efficiency, generate charts based on historical data to intuitively display performance changes; Equipment failure rate, analyzing the main causes of equipment problems based on maintenance records and operating status; User usage, statistics on the operation frequency and parameter adjustments of different users on the device.

[0019] Preferably, the device supports multi-user collaborative management, and different users can operate the device according to their permissions, including: Administrator privileges, allowing monitoring and management of all devices; Ordinary user permissions only allow operating specific devices and adjusting related parameters.

[0020] The present invention provides an intelligent airflow dryer, which has the following beneficial effects: 1. The present invention adopts an environmental perception and intelligent adjustment module, which can monitor the temperature, humidity and air pressure in the cavity in real time, and dynamically adjust the operating parameters to ensure that the equipment can adapt to the changing working environment. This technical solution achieves the effect of stable operation and greatly optimizes the drying efficiency. Compared with the equipment in the prior art that can only manually set fixed parameters, it solves the problems of low drying efficiency and complex operation caused by environmental fluctuations.

[0021] 2. The present invention realizes uniform distribution of airflow in the cavity through the intelligent airflow optimization module, while reducing the energy consumption of fan operation. The module is designed based on the fluid mechanics model and optimization algorithm, and can dynamically adjust the wind speed and airflow direction. Compared with the technical solution of single airflow path and uneven coverage in the prior art, the problem of incomplete local drying caused by uneven airflow is solved, and the drying consistency in the entire cavity is ensured.

[0022] 3. In the design of the intelligent control terminal, the present invention combines authority management with remote control functions, allowing users to operate the device accurately and efficiently, while ensuring the security of multi-user collaborative management. This design achieves the effect of taking both convenience and security into consideration, while traditional devices usually lack remote operation functions and are difficult to implement hierarchical management, thus solving the defects of insufficient flexibility in device use and insufficient management security.

[0023] 4. With the help of the Internet of Things module, the present invention connects the dryer equipment with the intelligent management system, supporting multi-protocol conversion and real-time data transmission. This solution achieves the effect of efficient collaboration of multiple devices and enhances the reliability of data. Compared with the phenomenon that the equipment operates in isolation and the data is difficult to centrally manage in the prior art, it completely solves the problem of low informationization of equipment and difficulty in remote monitoring, and provides an intelligent solution for laboratory and industrial applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a device diagram of the present invention; Figure 2 It is a schematic diagram of the structure of the drying machine of the present invention.

[0025] Among them, 1. Drying port; 2. Draining table; 3. Coding knob; 4. 7-inch LCD touch screen; 5. Glassware rack; 6. Power interface. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the specification of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0027] See also Figure 1-Figure 2 The embodiment of the present invention provides an intelligent airflow dryer, comprising: The IoT module is used to connect the smart airflow dryer with the cloud platform and user terminals, supports multi-protocol conversion, realizes device communication and data transmission, and has the characteristics of energy saving and low power consumption; The IoT module of the intelligent airflow dryer is an important part of the present invention, which is used to realize the communication and data transmission between the device and the cloud platform and user terminal. As a bridge connecting the dryer device and the cloud management system, this module not only provides the basis for device networking, but also supports functions such as multi-protocol conversion and data processing to meet the application requirements of multiple devices and multiple environments. Its design ensures seamless connection with other modules of the device (such as the intelligent management system and control terminal), providing support for the intelligent and remote management of the device.

[0028] In this embodiment, the Internet of Things module specifically includes the following contents: Multi-protocol conversion function The IoT module has the ability to convert between multiple protocols to achieve data compatibility and communication stability for different types of devices. Specifically, the module integrates a multi-protocol conversion subunit to support the following communication protocols: RS485 protocol: used for low-speed serial communication connection between dryer equipment group and IoT module to ensure physical layer compatibility between devices; Modbus protocol: used for equipment parameter collection and control command transmission, supporting multi-point device connection and cluster management; MQTT protocol: It realizes efficient data interaction between the cloud and devices through the message publishing-subscription mode, which is suitable for scenarios with strong real-time requirements.

[0029] As an option, the multi-protocol conversion subunit also supports dynamic protocol identification and switching functions. For example, in a hybrid network, when the IoT module receives an RS485 signal, it can automatically identify and convert it into the MQTT format to enable unified data upload to the cloud platform.

[0030] In general, the workflow of the protocol conversion subunit includes the following steps: Receive data frames transmitted by the underlying device; Determine the protocol type based on the identification bit of the data frame; Use protocol conversion algorithm to convert data into target protocol format; Send the converted data frame to the upper layer network.

[0031] In a possible implementation, the protocol conversion algorithm may calculate the target data frame based on the following formula: D out =T(D in ,P src ,P dst ) Among them, D out Indicates the output data frame, the format conforms to the target protocol P dst ;D in Indicates input data frame, the format conforms to the source protocol P src ; T represents the protocol conversion function, which realizes the conversion of frame formats according to different protocol mapping rules.

[0032] The design of the protocol conversion function T needs to ensure the integrity and structural consistency of the data content. For example, the register mapping relationship of the data needs to be processed in the Modbus to MQTT conversion.

[0033] RF communication function The IoT module has a highly integrated RF transceiver embedded in it for sending and receiving wireless data. This RF transceiver is combined with an energy-saving MCU to meet the needs of low-power operation. Specifically, the RF transceiver supports the following frequency bands: 433MHz band: used for long-distance low-rate communications; 2.4GHz frequency band: suitable for high-bandwidth data transmission scenarios.

[0034] As an option, the antenna design of the RF transceiver adopts a combination of internal and external antennas, which not only improves the portability of the device but also ensures communication performance. In complex indoor environments, signal interference is reduced through automatic frequency band switching technology. For example, when the module detects that the 2.4GHz channel is congested, it will switch to the 433MHz frequency band to ensure data transmission stability.

[0035] Generally, the transmit power and receive sensitivity of the RF transceiver can be adjusted dynamically according to the communication distance. The specific adjustment formula is as follows: P out =P max -ΔP(d,η) Among them, P out Indicates the current transmit power; P max represents the maximum transmission power; d represents the distance between the device and the receiving end; η represents the communication environment attenuation factor, which is determined by the path loss and signal interference intensity.

[0036] In some embodiments, the RF transceiver also supports the LoRa protocol for low-power long-distance transmission scenarios, and is particularly suitable for distributed deployment of industrial dryer equipment.

[0037] Data processing functions The data processing module is an important subunit of the IoT module, which is used to convert the format, detect anomalies and correct the collected data to ensure the integrity and stability of the data. Specifically, the functions of the data processing module include: Format conversion: The raw data collected by different devices (such as temperature, humidity, device status, etc.) are uniformly converted into JSON format for easy subsequent processing and transmission.

[0038] Anomaly detection: Dynamically check the data, such as detecting whether the collected data exceeds the preset range.

[0039] Error correction: Use compensation algorithms to correct abnormal data to ensure that the data uploaded to the cloud is authentic and valid.

[0040] In one possible implementation, the data correction process uses the following formula: D corr =D raw +ΔD(μ,σ) Among them, D corr Indicates the corrected data; D raw represents the original data; ΔD represents the correction value, which is determined by the historical mean μ and standard deviation σ of the data.

[0041] For example, when the temperature acquisition value of the equipment deviates from the set threshold (such as 70℃±2℃), the data processing module automatically corrects the deviation value according to the historical operation data and uploads the corrected data to the intelligent management system.

[0042] Generally, the data processing module also supports batch processing mode. For example, for multiple sets of data collected in real time, the module will perform data grouping operations and upload them to the cloud platform at one time according to the set time interval.

[0043] Connection with other modules As the core bridge between the dryer equipment and the intelligent management system, the IoT module is particularly important to work in collaboration with other modules: in the initialization stage, the IoT module receives the device configuration file from the intelligent management system and passes the parameters to the dryer equipment to complete the initialization settings of the equipment (such as sensor calibration).

[0044] During the operation stage, the Internet of Things module receives the operating data of the dryer equipment in real time, and after processing by the data processing module, uploads the results to the intelligent management system.

[0045] During the control stage, the IoT module receives instructions from the intelligent management system (such as adjusting wind speed, stopping heating, etc.), and converts the instructions into a format recognizable by the device through the protocol conversion subunit to ensure the accurate execution of the instructions.

[0046] The Internet of Things module plays a vital role in the present invention, which not only realizes efficient communication between the device and the cloud platform, but also lays the foundation for the intelligent control of the dryer equipment.

[0047] The dryer equipment group includes multiple dryer equipment of different types and brands. Each dryer equipment is equipped with corresponding components for real-time observation of the equipment's operating information and status information parameters. At the same time, the equipment is equipped with an actuator for receiving and executing control instructions. The dryer equipment group consists of multiple devices of different brands and types. Each device is equipped with a draining table 2, a coding knob 3, a 7-inch LCD touch screen 4, a glassware placement rack 5, a drying port 1, and a power interface 6 components. The draining table 2 is designed with anti-slip features and has a textured surface for collecting residual liquid on the surface of glassware. The LCD touch screen is integrated into the front panel of the device, which can display the operating status of the device and adjust parameters in real time, and supports users to perform touch operations. The glassware placement rack 5 adopts a modular design, which can adjust the size to fit different types of utensils, and fixes the utensils through anti-slip pads to prevent sliding or tipping during operation.

[0048] In this embodiment, the structural design of the dryer equipment emphasizes the improvement of operation convenience and drying efficiency.

[0049] Specifically, the draining table 2 is made of high-strength ABS plastic, and its surface is designed with a grid structure to effectively prevent glassware from sliding during placement. A drainage channel is provided at the bottom of the draining table 2, and the discharged liquid enters the collection container through the connected drain pipe. This container is designed to be detachable for easy cleaning and maintenance by users.

[0050] The LCD touch screen is located in the center of the front panel of the device, with a screen size of 7 inches and a resolution of 1024×768. The display content includes real-time temperature, remaining operation time, alarm information, etc. The touch screen also supports users to adjust the temperature curve by swiping or clicking. The setting of the temperature curve is based on the following formula: T(t)=T 0 +k·t where T(t) is the temperature at time t; T 0 is the initial temperature; k is the temperature change rate.

[0051] The glassware placement rack adopts a modular design, and the position of the support rod can be adjusted according to the size of the utensil, and its adaptation range is from 10 cm to 50 cm. The surface of the rack is covered with a high-temperature resistant silica gel layer to prevent the utensils from sliding due to high temperature during drying.

[0052] An adjustable air flow valve is provided inside the drying port 1, and the air flow valve automatically adjusts the air supply angle according to the size and position of the utensil. The angle adjustment formula is as follows: where θ is the air flow deflection angle; x is the horizontal offset distance from the center of the utensil to the center of the drying port 1; h is the vertical height distance from the drying port 1 to the top of the utensil.

[0053] The intelligent control terminal, including intelligent devices operated by users, is used to remotely monitor and control the dryer equipment through a dedicated application program; The intelligent control terminal is an important component module of the present invention. As the main interactive interface between the user and the device, its function is to provide users with real-time monitoring of the device's operating status, parameter settings, and remote transmission of operating instructions. Through the intelligent control terminal, users can easily adjust the operating parameters of the dryer, manage the device's operating permissions, and receive real-time feedback information from the management system. The intelligent control terminal works closely with the Internet of Things module and the intelligent management system to ensure the efficiency and reliability of the control process.

[0054] In this embodiment, the specific design and function implementation of the intelligent control terminal are as follows: Hardware and communication basics The intelligent control terminal is usually carried by a mobile device (such as a smartphone, tablet) or a desktop device (such as a computer). The terminal device establishes a communication connection with the IoT module and the intelligent management system through a dedicated application to achieve real-time data transmission.

[0055] Specifically, the communication methods of terminal devices include the following: Wi-Fi: Suitable for high-speed data interaction in local environments, supporting large data throughput; 4G / 5G: used for high-bandwidth, low-latency communication scenarios in remote environments, ensuring that terminals can control devices at any location; Bluetooth: suitable for fast pairing and temporary device operations at close range.

[0056] Generally speaking, the communication protocol of terminal devices adopts an encrypted data transmission method based on the TCP / IP protocol stack to ensure the security and privacy protection of the control process.

[0057] As an option, the terminal device also supports offline mode. In the event of a network outage, users can temporarily control the device through locally stored device parameters. When the network is restored, the terminal will automatically synchronize all operation records to the management system.

[0058] User interface The intelligent control terminal provides users with an intuitive and feature-rich operating interface, which displays the operating status and control options of the equipment in a visual way.

[0059] Specifically, the user interface mainly includes the following functional areas: Equipment list: displays all currently operable dryer equipment. Users can click on the equipment name to enter the equipment details page; Real-time monitoring page: displays the real-time operating status of the selected device, including temperature, humidity, operating time, current tasks, etc.; control parameter setting area: provides users with options to adjust operating parameters, such as setting target temperature, wind speed level and operating time; notification center: used to receive important information such as fault warnings and maintenance reminders pushed by the intelligent management system.

[0060] In one possible implementation, the user interface design uses a responsive layout that can automatically adapt to devices of different screen sizes. For example, on smartphones, the interface mainly displays device information in a card-like format, while on tablets, a column-based layout is used to facilitate users to view the status of multiple devices at the same time.

[0061] Permission management function In order to ensure the security of the equipment, the intelligent control terminal provides a multi-level permission management function, and the operation permissions of different users can be flexibly set according to their roles.

[0062] Specifically, permission management includes the following roles: Administrator: has the highest authority and can add or delete devices, adjust all device parameters, and view all operating data; Ordinary user: is limited to operating the devices assigned to them, such as setting operating parameters and starting tasks; Guest user: can only view the real-time status of the device but cannot perform any control operations.

[0063] As an option, the permission management function is implemented based on the binding of the device's unique ID and user account. The management system will assign a permission list to each user, and when the terminal device receives a user request, it will decide whether to allow the relevant operation based on the permission list.

[0064] In general, the permission management function also supports dynamic adjustment. For example, when the administrator needs to temporarily grant ordinary users the operation rights of certain specific devices, the permission adjustment instruction can be sent directly through the terminal without reconfiguring the system.

[0065] Control command generation and transmission The core function of the intelligent control terminal is to generate device control instructions based on user input and send them to the target device through the Internet of Things module.

[0066] Specifically, the generation of control instructions includes the following steps: Parameter parsing: Parsing the target value (such as target temperature, operating time) entered by the user into standardized control parameters; Instruction assembly: According to the communication protocol of the target device, the standardized parameters are encapsulated into instruction data packets that can be recognized by the device; Verify and send: Perform CRC check on the generated command data packet to ensure the integrity of the command, and then send it to the target device through the IoT module.

[0067] In a possible implementation, the instruction generation process can be expressed by the following formula: C out =F(U,E,P) Among them, C out is the generated control instruction data packet; U represents the parameter set input by the user, including target temperature, humidity, time, etc.; E represents the current status information of the target device; P represents the parameter template of the communication protocol, which is preset by the system.

[0068] As an optimization measure, the control command transmission also supports batch mode. For example, when the user needs to start multiple devices at the same time, the terminal will integrate all the commands into a batch command package and send it, thereby reducing communication delays.

[0069] Data synchronization and history The intelligent control terminal also supports real-time data synchronization and history viewing functions, so users can understand the operating status of the equipment and past operation records at any time.

[0070] Specifically, the data synchronization functions include: Real-time synchronization: through continuous communication with the management system, the equipment operation data is updated to the terminal at fixed time intervals (such as every 10 seconds); History query: Users can filter historical data by time, device, or task type, for example, to view the operation log of a device over the past week.

[0071] In a possible implementation, the query function of the historical records adopts the form of paging loading. After the user selects the query range, the terminal will request the management system for data of the corresponding time period, and the system will return the data in the form of pages, reducing the impact of a large amount of data loaded at one time on the performance of the terminal.

[0072] The intelligent control terminal cooperates closely with other modules in the present invention, and its main connection methods include: Communication with the IoT module: The terminal sends control instructions through the IoT module and receives operating status feedback from the device; Collaboration with intelligent management systems: The terminal converts user operations into instructions and sends them to the management system. The management system generates feedback information based on the device status and synchronizes it to the terminal.

[0073] Generally, the connection between the terminal and other modules adopts an asynchronous communication mechanism to ensure that user operations will not be interrupted or lost in the event of network delays or data loss.

[0074] Through the above detailed design, the intelligent control terminal realizes efficient interaction between users and devices, and at the same time forms a complete closed loop with the Internet of Things module and management system, providing strong support for the precise control of the equipment.

[0075] Intelligent management system, used to record equipment operation data, analyze equipment status, push equipment failure warning information, and interact with other systems; The intelligent management system is an important part of the present invention, responsible for key functions such as data processing, status analysis and task scheduling. It realizes comprehensive monitoring and management of the dryer equipment group through collaboration with the Internet of Things module and the intelligent control terminal. The intelligent management system can not only record the operating data of the equipment, but also conduct in-depth analysis of the data, generate visual results and provide operation optimization suggestions. In addition, the intelligent management system also supports integration with external platforms such as laboratory management systems, and has strong scalability and synergy.

[0076] In this embodiment, the specific design and function implementation of the intelligent management system are as follows: System architecture and communication interface The architecture of the intelligent management system is divided into three parts: front-end, back-end and database, ensuring the efficiency and stability of the system operation.

[0077] Specifically: Front-end: interacts with users through user interfaces (such as web pages or mobile applications) to provide functions such as device status display, parameter settings, and data analysis; Backend: responsible for the processing, storage and instruction parsing of device data, including various logic processing modules, such as data processing module, control module, etc. Database: used to store device information, historical data, user operation records and analysis results, and supports efficient query and data management.

[0078] Generally speaking, the communication interface of the intelligent management system adopts a standardized design, such as a communication protocol based on RESTful API. This ensures seamless connection between the system and other modules (such as the Internet of Things module and the control terminal).

[0079] As an option, the system also supports the WebSocket protocol to achieve real-time updates of device status. For example, when the temperature of a device is abnormal, the IoT module sends the alarm information to the management system via WebSocket, which pushes the information to the user terminal for a quick response.

[0080] Detailed description of the intelligent management system The intelligent management system is an important part of the present invention and is responsible for key functions such as data processing, status analysis, and task scheduling. It realizes the comprehensive monitoring and management of the dryer equipment group through cooperation with the Internet of Things module and the intelligent control terminal. The intelligent management system can not only record the operation data of the equipment, but also deeply analyze the data, generate visual results and provide operation optimization suggestions. In addition, the intelligent management system also supports integration with external platforms such as the laboratory management system and has strong scalability and collaboration.

[0081] In this embodiment, the specific design and function implementation of the intelligent management system are as follows: System Architecture and Communication Interface The architecture of the intelligent management system is divided into three parts: the front end, the back end, and the database, ensuring the high efficiency and stability of the system operation.

[0082] Specifically: Front end: Interacts with users through the user interface (such as a Web page or a mobile application), providing functions such as device status display, parameter setting, and data analysis; Back end: Responsible for the processing, storage, and instruction parsing of device data, including various logic processing modules such as a data processing module, a control module, etc.; Database: Used to store device information, historical data, user operation records, and analysis results, supporting efficient query and data management.

[0083] Generally, the communication interface of the intelligent management system adopts a standardized design, such as a communication protocol based on RESTful API. This can ensure the seamless docking of the system with other modules (such as the Internet of Things module and the control terminal).

[0084] As an option, the system also supports the WebSocket protocol to achieve real-time updates of device status. For example, when the temperature of a certain device is abnormal, the Internet of Things module sends an alarm message to the management system through WebSocket, and the latter pushes the message to the user terminal to achieve a quick response.

[0085] Device Status Monitoring The intelligent management system has the function of real-time monitoring of device status and comprehensively displays the operation status of the devices by integrating data from the dryer equipment group.

[0086] Specifically, the system receives the following data from the Internet of Things module: Temperature and humidity data: Used to analyze the environmental conditions inside the device cavity; Operation status: Including whether the device is turned on, the current running time, the remaining task duration, etc.; Execution result feedback: Such as the execution situation of instructions such as wind speed adjustment and temperature calibration.

[0087] In one possible implementation, the device status monitoring adopts a hierarchical update mechanism: High priority data (such as temperature and humidity) is updated once a second to ensure real-time performance; Low-priority data (such as historical operation records) is synchronized once a minute to reduce system pressure.

[0088] Generally, the visualization of equipment status is mainly based on graphical interfaces. For example, the system presents temperature data in real time in the form of a line graph, and marks the operating areas in different states with colors (such as green for normal and red for abnormal).

[0089] Data processing and analysis The intelligent management system centrally processes and deeply analyzes the data uploaded by the equipment to ensure the stability and efficiency of equipment operation.

[0090] Specifically, data processing includes the following steps: Data cleaning: remove invalid or duplicate data to ensure data integrity; Anomaly detection: Identify abnormal data points, such as temperature outside the set range, based on statistical analysis and rule matching; Trend prediction: Use historical data and machine learning algorithms to predict the future status of equipment, such as temperature change trends.

[0091] As an option, the anomaly detection algorithm can adopt the following formula: Among them, S detected Indicates whether the detection value is abnormal (if it is greater than the threshold, it is considered abnormal); D i is the collected data point; μ is the mean of the historical data of the device; σ is the standard deviation of the historical data.

[0092] In terms of data analysis, the data reports generated by the system include various indicators such as equipment operating efficiency, failure rate, user operation frequency, etc. For example, the system calculates the equipment utilization rate by counting the deviation between the average operating time of a certain equipment in the past week and the expected value, and displays the results in a bar chart.

[0093] Task Scheduling and Optimization The intelligent management system supports dynamic scheduling and parameter optimization of tasks, and allocates tasks based on equipment operation conditions and user needs.

[0094] Specifically: Task scheduling: The system analyzes the status of the equipment and prioritizes assigning new tasks to idle or efficient equipment. For example, when the user needs to dry multiple samples at the same time, the system will automatically assign tasks to multiple devices to shorten the task completion time; Parameter optimization: Adjust equipment parameters based on real-time data and operating environment, such as increasing wind speed to improve drying efficiency when humidity is high.

[0095] In one possible implementation, the task scheduling algorithm uses the following formula: Among them, T assigned Indicates the device that assigns the task; L i Indicates the current load of the i-th device; E i Indicates the current operating efficiency of the equipment; α is the weight parameter, which reflects the impact of efficiency on scheduling.

[0096] In general, task scheduling also supports multi-task parallel mode. Users can select batch task mode in the interface, and the system will automatically allocate devices and generate task execution plans.

[0097] Fault alarm and maintenance management The intelligent management system provides users with fault alarms and maintenance suggestions by integrating multiple data sources.

[0098] Specifically: Fault alarm: When the system detects an abnormality in the equipment (such as excessive temperature or failure of the humidity sensor), it will immediately push an alarm message to the user and provide preliminary fault diagnosis results; Maintenance management: The system records the operating time and maintenance history of each device and regularly reminds users to perform equipment maintenance.

[0099] As an option, the maintenance management module generates maintenance recommendations based on the equipment operating life model. For example, the system calculates the remaining life of the equipment by the ratio of the accumulated operating time to the preset life parameter: Among them, R remaining Represents the remaining life ratio; T life Indicates the design life of the equipment; T used Indicates the accumulated running time of the device.

[0100] The intelligent management system forms a closed-loop control link with other modules in a variety of ways to ensure the efficient operation of the entire system.

[0101] Specifically: With the IoT module: receive device data from the IoT module, process and store it, and send control instructions to the device through the IoT module; With intelligent control terminal: receive control commands input by users and feed back the processed results to the terminal, providing users with intuitive operation experience.

[0102] Generally speaking, intelligent management systems will give priority to high-priority data (such as real-time status updates) to ensure the system's responsiveness and user experience.

[0103] The intelligent management system plays the role of a data center in the present invention, which not only realizes real-time monitoring and intelligent management of equipment, but also provides strong support for the scalability and coordination of the system.

[0104] Environmental sensing and intelligent adjustment module, which is used to monitor the temperature, humidity and air pressure in the cavity in real time, and dynamically adjust the equipment operating parameters according to environmental changes to optimize drying efficiency; The environmental perception and intelligent adjustment module is a key part of the present invention. It is mainly used to monitor the environmental parameters inside the dryer in real time and dynamically adjust the operating status of the equipment according to environmental changes. This module not only ensures the high efficiency of the equipment under different operating conditions, but also achieves the stability and energy consumption optimization of the drying process. The environmental perception and intelligent adjustment module obtains real-time environmental data through the sensor network, and combines the control algorithm to dynamically control the key parameters of the equipment such as airflow and temperature.

[0105] In this embodiment, the specific design and implementation of the environment perception and intelligent adjustment module are as follows: Monitoring and collection of environmental parameters This module collects key environmental parameters in the cavity through a variety of sensors. Specifically, these parameters include temperature, humidity, air pressure and air flow distribution.

[0106] Specifically: Temperature monitoring: Use high-precision temperature sensors to obtain real-time temperature data inside the cavity. The measurement range can reach -10℃ to 300℃, and the accuracy can reach ±0.1℃.

[0107] Humidity monitoring: A capacitive humidity sensor is used to monitor the air humidity in the cavity, supporting a relative humidity range of 0%-100%.

[0108] Air pressure monitoring: The pressure sensor detects changes in air pressure inside the cavity to provide a reference for wind speed and airflow optimization.

[0109] Air flow distribution monitoring: Use micro air flow sensors to obtain the air flow velocity and direction at different locations inside the cavity, and the data is expressed in vector form.

[0110] In one possible implementation, these sensors are installed at different locations in the cavity according to the principle of uniform distribution to ensure comprehensive data collection. For example, temperature and humidity sensors are arranged at the top, middle and bottom of the cavity to detect vertical environmental changes in real time.

[0111] Generally, the sampling frequency of sensor data is set to once per second. When the high-frequency environment changes, the sampling frequency can be increased to once per 0.1 second.

[0112] Data processing and dynamic adjustment After the environmental parameters are collected, they are analyzed and adjusted through the data processing module to provide a decision basis for subsequent control. The processing process includes data cleaning, environmental model construction and adjustment strategy generation.

[0113] Specifically: Data cleaning: Remove abnormal data points caused by sensor errors or short-term fluctuations. The cleaning process uses a sliding average filter algorithm, and the formula is: Among them, D smooth is the data value after filtering, D i is the original data of the ith sampling, and N is the size of the sliding window (usually 5-10).

[0114] Environmental model construction: Combine the collected temperature, humidity and air pressure data to build a thermodynamic model inside the cavity to describe the impact of environmental changes on drying efficiency. For example, the model describes the impact of humidity on drying time through the following formula: Among them, T dry is the drying time, C is the material coefficient of the container, H is the humidity, ΔT is the temperature difference, and V is the air flow velocity.

[0115] Adjustment strategy generation: Adjustment strategies are generated based on environmental model outputs, such as increasing wind speed under high humidity conditions and increasing heating power under low temperature conditions.

[0116] Implementation of intelligent regulation The adjustment strategy is sent from the control unit to the actuator of the equipment to complete the dynamic adjustment of the internal environment of the cavity. Specifically, the adjustment includes the following aspects: Wind speed adjustment: control the fan speed and adjust the airflow intensity and distribution in the cavity.

[0117] The wind speed is adjusted using closed-loop control, and the target wind speed is calculated in real time using the following formula: V target = k·(H current -H target )+V base Among them, V target is the target wind speed, H current and H target are the current humidity and target humidity respectively, V base is the basic wind speed, and k is the control gain coefficient.

[0118] Temperature regulation: Based on the feedback from the temperature sensor, the output power of the heating element is adjusted to ensure that the temperature in the cavity is maintained within the target range. For example, the system calculates the heating power through the PID control algorithm: Where P is the heating power, e is the temperature difference, K p ,K i ,K d is the PID control parameter Airflow direction adjustment: The servo motor changes the angle of the air outlet to achieve uniform airflow coverage in the cavity. As an option, the system can adopt a preset air supply mode, such as local enhancement mode (concentrated air supply to a specified area) or global uniform mode.

[0119] The environmental perception and intelligent adjustment module works together with the Internet of Things module and the intelligent management system to ensure the global optimization of the equipment's operating status.

[0120] Specifically: Environmental parameters are uploaded to the intelligent management system through the Internet of Things module. After system analysis, a global optimization strategy is generated and returned to this module for execution.

[0121] The execution results of the regulation module (such as wind speed and temperature changes) are fed back to the IoT module through sensors to achieve closed-loop control.

[0122] Generally, the operating frequency of the environmental perception and intelligent adjustment module is dynamically adjusted by the intelligent management system. For example, high-frequency data collection and adjustment are performed during the initial operation stage of the equipment, and the frequency is reduced to save resources during the stable operation stage.

[0123] The environmental perception and intelligent adjustment module ensures the stable and efficient operation of the dryer equipment while realizing real-time optimization of the operating parameters, providing strong support for the high performance of the overall system of the present invention.

[0124] Intelligent airflow optimization module, which is used to calculate the airflow distribution based on the airflow model in the cavity, and achieve uniform airflow coverage and energy consumption optimization in the cavity by adjusting the airflow direction and wind speed; The intelligent airflow optimization module is an important part of the present invention, which is used to dynamically optimize the airflow distribution inside the dryer. By calculating the airflow model in the cavity, this module can adjust the airflow direction and wind speed in real time to ensure the uniformity of airflow coverage in the cavity and minimize energy consumption. The intelligent airflow optimization module collaborates with the environmental perception module and the actuator to dynamically generate control strategies and quickly perform adjustments based on real-time monitoring data and optimization algorithms.

[0125] In this embodiment, the specific design and function implementation of the intelligent airflow optimization module are as follows: Airflow distribution modeling In order to optimize the airflow distribution in the cavity, it is first necessary to establish a dynamic distribution model of the airflow. This model is used to describe the relationship between the airflow velocity, pressure and direction in the cavity and predict its impact on the drying efficiency.

[0126] Specifically: Airflow modeling basis: Airflow distribution is described by fluid mechanics equations, and the core equation is: in, is the airflow velocity vector, describing the magnitude and direction of the airflow; p is the airflow pressure; ρ is the air density; μ is the air dynamic viscosity; Represents the gradient operator.

[0127] Boundary conditions: The air flow inlet in the cavity is set with a fixed wind speed and direction, the pressure at the outlet is set to a constant value, and the cavity wall is assumed to have a no-slip boundary condition.

[0128] In a possible implementation, the module divides the cavity into a number of grid cells, calculates the airflow parameters for each cell, and forms a discretized flow field model. The model accuracy is optimized through numerical simulation tools (such as CFD simulation).

[0129] Generally, the time step of airflow modeling is set to 0.01 seconds to ensure that the dynamic characteristics of the airflow can be captured.

[0130] Optimization algorithm design The intelligent airflow optimization module uses an optimization algorithm to dynamically adjust the airflow distribution. The algorithm calculates the optimal control strategy based on real-time airflow data and target conditions.

[0131] Specifically: Objective function: The goal of the optimization process is to minimize the unevenness of airflow coverage while reducing energy consumption. The objective function is defined as: Among them, J is the objective function; is the average velocity of the airflow in the cavity; V is the cavity volume; β is the energy consumption weight; P is the fan power consumption.

[0132] Optimization method: The gradient descent method is used to optimize the objective function, and the optimal control parameters are found through iterative calculation.

[0133] As an option, the system will also combine genetic algorithms in actual operation to quickly find the global optimal solution in complex environments. For example, in an irregular cavity, the genetic algorithm finds a suitable wind speed distribution solution through random mutation and selection iterative optimization.

[0134] Control strategy generation After completing the optimization calculation, the intelligent airflow optimization module generates a specific control strategy and realizes dynamic adjustment of the airflow in the cavity through the actuator.

[0135] Specifically: Wind speed adjustment: Adjust the fan speed to achieve precise control of airflow intensity. The target wind speed is calculated by the following formula: V target =V mean +γ·(v local -v target ) Among them, V target is the target wind speed; V mean is the average wind speed in the cavity; v local is the local wind speed; γ is the adjustment coefficient, which is usually adjusted dynamically according to operational requirements.

[0136] Airflow direction adjustment: The servo motor adjusts the air outlet angle to achieve dynamic changes in airflow direction. For example, the system adjusts the air outlet to a high humidity area to accelerate drying based on real-time data of airflow distribution in the cavity.

[0137] As a possible implementation, the module will update the wind speed and angle settings in real time based on the device's internal sensor feedback to ensure even airflow coverage in each area.

[0138] Real-time monitoring and feedback The control process of the intelligent airflow optimization module adopts a closed-loop feedback mechanism. By monitoring the airflow distribution in real time, the execution results are compared with the target state and the optimization strategy is adjusted.

[0139] Specifically: During the monitoring process, the system collects air flow velocity and direction data at different locations in the cavity and calculates the air flow coverage uniformity index.

[0140] If the monitoring result deviates greatly from the target state, the optimization algorithm is called again to generate a new control strategy.

[0141] Generally, the feedback frequency is once per second, which can be increased to once every 0.5 seconds when the environment changes rapidly, ensuring the timeliness and accuracy of the adjustment process.

[0142] The intelligent airflow optimization module works closely with the environmental perception module and the actuator to form a complete optimization control link.

[0143] Specifically: The environmental perception module provides real-time environmental parameters (such as temperature, humidity, and air flow distribution) as input to the optimization algorithm.

[0144] The actuator adjusts the fan speed and air outlet angle according to the optimization strategy, and feeds the adjustment results back to the optimization module to form a closed-loop control.

[0145] In one possible implementation, the module will also work in conjunction with the intelligent management system to upload the optimization results to the management system for subsequent data analysis and performance evaluation.

[0146] The intelligent airflow optimization module can effectively improve the uniformity of airflow in the cavity and reduce unnecessary energy loss, providing reliable airflow support for the drying process. This module not only ensures the operating efficiency of the equipment, but also improves the intelligence level of the overall system.

[0147] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent airflow dryer, characterized in that: include: The IoT module is used to connect the smart airflow dryer with the cloud platform and user terminals, supports multi-protocol conversion, realizes device communication and data transmission, and has the characteristics of energy saving and low power consumption; The dryer equipment group includes multiple dryer equipment of different types and brands. Each dryer equipment is equipped with corresponding components for real-time observation of the equipment's operating information and status information parameters. At the same time, the equipment is equipped with an actuator for receiving and executing control instructions; Smart control terminal, including a user-operated smart device for remotely monitoring and controlling the dryer equipment through a dedicated application; Intelligent management system, used to record equipment operation data, analyze equipment status, push equipment failure warning information, and interact with other systems; Environmental sensing and intelligent adjustment module, which is used to monitor the temperature, humidity and air pressure in the cavity in real time, and dynamically adjust the equipment operating parameters according to environmental changes to optimize drying efficiency; The intelligent airflow optimization module is used to calculate the airflow distribution based on the airflow model in the cavity, and to achieve uniform airflow coverage and energy consumption optimization in the cavity by adjusting the airflow direction and wind speed.

2. The intelligent airflow dryer according to claim 1, characterized in that: The Internet of Things module includes: Multi-protocol conversion subunit, used to realize conversion between RS485, Modbus, MQTT and other protocols; RF transceiver, integrated into the energy-saving MCU, for wireless data communication; The data processing module is used to convert the format, detect anomalies and correct them for device data to ensure the accuracy and stability of data transmission.

3. The intelligent airflow dryer according to claim 1, characterized in that: The drying machine equipment comprises: A draining table (2), located on the top of the drying device, for placing glassware and collecting liquid remaining during the drying process; An encoding knob (3) is arranged on the front panel of the device and is used to adjust the drying parameters by rotation; A liquid crystal touch screen (4), arranged on the front panel of the device, for displaying the operating status and parameters of the device, and supporting a user touch operation to select a function; A glassware rack (5) is located outside the device and is used to fix glassware of different sizes to prevent the glassware from sliding or tipping over during the drying process; A drying port (1) is arranged on the outside of the glassware placement rack (5) and is used to convey airflow into the glassware for drying; A power interface (6) is arranged on the side of the device and is used to provide power supply to the device.

4. The intelligent airflow dryer according to claim 1, characterized in that: The intelligent control terminal comprises: User operation interface, supports remote control of equipment operation, parameter adjustment and query of equipment historical data; The permission management function sets different operation permissions according to user roles to ensure the security of device management.

5. The intelligent airflow dryer according to claim 1, characterized in that: The intelligent management system comprises: Data analysis and storage module, used to record equipment operating parameters and perform visual analysis of data; The alarm and notification module is used to generate fault alarms according to the equipment operation status and push them to the user terminal; The collaborative work module supports integration with laboratory management systems or enterprise resource planning systems to achieve information sharing and collaboration.

6. The intelligent airflow dryer according to claim 1, characterized in that: The environment perception and intelligent adjustment module includes: Temperature and humidity sensor, used to collect real-time air temperature and humidity data in the cavity; Air pressure sensor, used to monitor the pressure distribution of airflow in the cavity; The regulating mechanism includes a wind speed controller and a temperature regulator, which adjusts the airflow intensity and temperature in real time according to the collected environmental parameters; Remote monitoring and control: Users set equipment operating parameters through smart terminals, the system generates control instructions and sends them to the equipment, and the equipment feeds back the results after execution to achieve closed-loop operation.

7. The intelligent airflow dryer according to claim 1, characterized in that: The intelligent airflow optimization module comprises: The air flow distributor controls the opening degree of the air flow valve through a servo motor to achieve dynamic adjustment of the air flow direction and intensity; The control unit calculates the optimal distribution plan of the airflow in the cavity based on the airflow distribution model and optimization algorithm, and generates control instructions to send to the airflow distributor.

8. The intelligent airflow dryer according to claim 1, characterized in that: The intelligent management system realizes equipment operation control through the following steps: Device initialization: The IoT module reads the basic information of the device, uploads it to the intelligent management system, completes device registration and generates an initialization configuration file; Data collection and upload: Real-time collection of equipment operating parameters and upload to the cloud platform through the Internet of Things module. The data is stored in the database after preliminary processing; Remote monitoring and control: Users set equipment operating parameters through smart terminals, the system generates control instructions and sends them to the equipment, and the equipment feedbacks the results after execution.

9. The intelligent airflow dryer according to claim 1, characterized in that: The intelligent management system supports the generation of multiple data reports, including: Equipment operating efficiency, generate charts based on historical data to intuitively display performance changes; Equipment failure rate, analyzing the main causes of equipment problems based on maintenance records and operating status; User usage, statistics on the operation frequency and parameter adjustments of different users on the device.

10. The intelligent airflow dryer according to claim 1, characterized in that: The device supports multi-user collaborative management, and different users can operate the device according to their permissions, including: Administrator privileges, allowing monitoring and management of all devices; Ordinary user permissions only allow operating specific devices and adjusting related parameters.

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