Remote management control method for electrostatic powder spraying equipment

Abstract

The invention relates to the technical field of industrial coating, and discloses a remote management control method for electrostatic powder spraying equipment, which comprises the following steps: connecting the electrostatic powder spraying equipment to a remote control center, and carrying out initialization setting; a sensor is used for collecting operation data of the equipment in real time and transmitting the data to a remote control center; optimizing spraying parameters according to preset spraying process requirements and data acquired in real time; performing real-time analysis on the equipment operation data, detecting abnormal data, and giving an alarm when an abnormality is found; by adjusting the speed and the pressure of the powder conveying system, the conveying amount of the powder is matched with the spraying task requirement; the equipment is operated and monitored in real time through the remote terminal, and simultaneous operation and authority management of multiple users are supported. By means of the method, efficient management and accurate control over the electrostatic powder spraying equipment can be achieved, the spraying efficiency and quality are improved, and the labor cost and resource waste are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial painting, and particularly to a method for remotely managing and controlling an electrostatic powder spraying device. Background Art

[0002] In the traditional electrostatic powder spraying process, the parameter setting and monitoring of the spraying device mainly rely on manual operation. Operators need to manually adjust parameters such as the voltage, current, and spraying speed of the spray gun according to experience, which is not only inefficient but also prone to unstable spraying quality due to human errors. In addition, the monitoring of the device operation status usually relies on regular inspections, making it difficult to grasp the operation of the device in real time, resulting in delayed fault discovery and handling, increasing the device downtime and maintenance costs.

[0003] In the prior art, although some spraying devices have introduced automated control, most of these systems can only achieve simple parameter setting and monitoring and cannot dynamically adjust spraying parameters according to real-time data. In addition, these systems usually lack intelligent fault diagnosis and early warning functions and cannot predict and handle faults before they occur. This not only affects production efficiency but also may lead to a decline in spraying quality and device damage.

[0004] There are also deficiencies in the control of the powder conveying system in the prior art. Traditional control systems usually can only achieve fixed parameter settings and cannot dynamically adjust the speed and pressure of the powder conveying system according to real-time data. This not only results in a mismatch between the powder conveying volume and the spraying task requirements but also may waste powder materials due to improper parameter settings, increasing production costs.

[0005] Therefore, the present invention proposes a method for remotely managing and controlling an electrostatic powder spraying device. Summary of the Invention

[0006] The purpose of the present invention is to propose a method for remotely managing and controlling an electrostatic powder spraying device to solve the problems of low efficiency of manual operation, lack of real-time monitoring, insufficient dynamic adjustment ability, and insecure data transmission in the prior art.

[0007] To achieve the above purpose, the present invention adopts the following technical solutions: A method for remotely managing and controlling an electrostatic powder spraying device, comprising the following steps: Step S1, connect the electrostatic powder spraying device to the remote control center through an industrial Internet of Things platform and perform initialization settings; Step S2, use sensors to collect the operation data of the device in real time and transmit the data to the remote control center through an encrypted communication protocol; Step S3, optimize the spraying parameters according to the preset spraying process requirements and the real-time collected data through an intelligent algorithm based on machine learning; Step S4, perform real-time analysis on the device operation data, detect abnormal data through dynamic thresholds, and issue an alarm through a multi-level alarm mechanism when an anomaly is detected; Step S5, dynamically adjust the speed and pressure of the powder delivery system through an improved closed-loop control algorithm to achieve the matching of the powder delivery volume with the requirements of the spraying task; Step S6, perform real-time operation and monitoring of the device through a remote terminal. The remote terminal provides a user interface and supports simultaneous operation and permission management for multiple users.

[0008] Furthermore, in step S1, the following sub-steps are also included: S1-1, establish a secure communication link between the electrostatic powder spraying device and the remote control center through an industrial Internet of Things platform, and encrypt the communication link using blockchain technology; S1-2, configure the basic parameters and safety parameters of the device. The basic parameters include the initial voltage, current, and powder flow rate of the spray gun, and the safety parameters include overvoltage protection, overcurrent protection, and temperature protection; S1-3, initialize the operating state of the device, and detect whether the components are working properly through the self-check program of the device. The components include the spray gun, powder delivery system, and electrostatic generator; S1-4, send an initialization instruction to the device through the remote control center. After receiving the instruction, the device executes the initialization process and feeds back the initialization result to the remote control center to prepare for starting the spraying operation.

[0009] Furthermore, in step S2, the following sub-steps are also included: S2-1, monitor the operating state of the device by installing sensors. The sensors include voltage sensors, current sensors, flow sensors, temperature sensors, and humidity sensors; S2-2, perform real-time preprocessing on the collected data. The preprocessing includes data cleaning, noise filtering, and outlier detection; S2-3, encrypt and transmit the data using an encrypted communication protocol, and introduce data compression technology to perform real-time compression on the collected data to reduce the data transmission volume. The encrypted communication protocol includes the Transport Layer Security protocol, Secure Sockets Layer protocol, Advanced Encryption Standard, and Hash Message Authentication Code. The data compression technology includes Huffman coding, arithmetic coding, LZ77 algorithm, LZ78 algorithm, LZW algorithm, and DEFLATE algorithm; S2-4, decrypt and decompress the received data through the remote control center and perform secondary verification.

[0010] Furthermore, in step S3, the following sub-steps are also included: S3-1. Adjust the spraying parameters through a deep reinforcement learning algorithm to achieve the preset spraying process requirements. The deep reinforcement learning algorithm includes Deep Q Network, Double Deep Q Network, Deep Deterministic Policy Gradient, Soft Actor-Critic algorithm, and Proximal Policy Optimization. The spraying parameters include spraying speed, spraying distance, spraying angle, spraying pressure, coating thickness, powder particle size, environmental humidity, and temperature. The spraying process requirements include spraying uniformity, coverage rate, and coating thickness; S3-2. Combine a generative adversarial network to generate adjusted spraying parameter combinations and optimize them through adversarial training of the generator and discriminator; S3-3. Adopt transfer learning technology to transfer existing spraying process knowledge to the spraying task, reducing the learning time and cost of new tasks; S3-4. Through an online learning algorithm, combined with sensor data, update the spraying parameters in real time. The online learning algorithm includes stochastic gradient descent and mini-batch gradient descent. The sensor data includes voltage, current, powder flow rate, temperature, and humidity.

[0011] Furthermore, in step S4, the following sub-steps are also included: S4-1. Collect the historical operation data of the equipment, analyze the historical operation data, and calculate the statistical features of each sensor data. The historical operation data includes sensor data during normal operation and sensor data during faults. The statistical features include mean, standard deviation, minimum value, and maximum value; S4-2. According to the statistical features, set the initial threshold range for each sensor data. The initial threshold range is the mean plus or minus twice the standard deviation; S4-3. Calculate the short-term statistical features and long-term statistical features of the sensor data and compare them to evaluate the change trend of the data. The short-term statistical features include the mean, standard deviation, maximum value, and minimum value within a sliding window. The long-term statistical features include the mean, standard deviation, maximum value, and minimum value over a past period of time. The change trend includes an upward trend and a downward trend; S4-4. According to the change trend of the data, set a dynamically adjusted threshold and regularly re-evaluate and adjust the threshold. The regular period includes every 24 hours, every week, and every month; S4-5. Analyze the equipment operation data in real time, compare it with the dynamic threshold, and detect whether there is abnormal data; S4-6. When abnormal data is detected, issue an alarm through a multi-level alarm mechanism. The multi-level alarm mechanism includes a sound alarm, SMS notification, email notification, and pop-up notification on a remote terminal.

[0012] Furthermore, in step S5, the following sub-steps are also included: S5-1. Set the initial speed and pressure parameters of the powder conveying system, and calculate the required powder conveying volume according to the actual spraying requirements; S5-2. Real-time monitor the output parameters of the powder conveying system through sensors, and the output parameters include powder flow rate, conveying speed and pressure; S5-3. According to the deviation between the actual output parameters and the preset target parameters, use the closed-loop control algorithm to calculate the adjustment amount, and dynamically adjust the speed and pressure of the powder conveying system. The specific formula is: where T represents the adjustment amount, Z represents the deviation, 、 、 are the control coefficients of proportional, integral and differential respectively, represents the small change in time, that is, the time interval, represents the integral of the deviation, that is, the cumulative value of the deviation over time, represents the small change in the deviation, that is, the change amount of the deviation, represents the derivative of the deviation, that is, the change rate of the deviation over time; S5-4: Continuously monitor the adjusted output parameters to achieve the matching of the powder conveying volume and the requirements of the spraying task.

[0013] Furthermore, in step S6, the following sub-steps are also included: S6-1. Integrate the real-time video monitoring function, so that the operator can view the real-time video of the equipment through the remote terminal, understand the operating status of the equipment, and send operation instructions through the remote terminal to control the start, stop and parameter adjustment of the equipment. The remote terminal includes a computer, a tablet computer, a mobile phone and an industrial handheld terminal; S6-2. Provide a user interface through the remote terminal, and the user interface includes a real-time data display interface, a parameter adjustment interface and a fault diagnosis information display interface; S6-3. Provide role-based access control, allowing the system administrator to assign different permissions according to the user's role, so that each user can only access and operate the functions within their permission scope; S6-4. Record the operation logs for auditing and equipment maintenance, and the operation logs include the operation time, operation content and operation result.

[0014] Furthermore, a system for implementing the remote management and control method of an electrostatic powder spraying device includes: A remote control center for centrally managing and coordinating the data flow and control instructions between each module; An industrial Internet of Things module for connecting the electrostatic powder spraying device to the remote control center and performing initialization settings; A data acquisition and transmission module, which is used to collect the operation data of the device in real time through sensors and transmit the data to the remote control center through an encrypted communication protocol; A parameter optimization module, which is used to optimize the spraying parameters through an intelligent algorithm based on machine learning according to the preset spraying process requirements and the real-time collected data; A fault diagnosis module, which is used to analyze the device operation data in real time, detect abnormal data through dynamic thresholds, and issue alarms through a multi-level alarm mechanism when abnormalities are found; A closed-loop control module, which is used to dynamically adjust the speed and pressure of the powder conveying system through an improved closed-loop control algorithm to achieve the matching of the powder conveying volume and the spraying task requirements; A user interaction module, which is used to perform real-time operation and monitoring of the device through a remote terminal, provide a user interface, and support simultaneous operation and permission management of multiple users.

[0015] The beneficial effects brought by the technical solution provided by the present invention at least include: By dynamically adjusting the speed and pressure of the powder conveying system through an improved closed-loop control algorithm, the present invention can optimize the spraying parameters in real time according to real-time data, thereby improving the spraying efficiency and quality and reducing spraying defects caused by improper parameter settings.

[0016] By real-time monitoring the device operation data and using an intelligent algorithm based on machine learning for fault diagnosis and early warning, and at the same time, through a multi-level alarm mechanism, the present invention ensures that the operator can respond in time, further improving the operation stability and reliability of the device.

[0017] Through an encrypted communication protocol and data compression technology, the present invention ensures the security and efficiency of data transmission. At the same time, through role-based access control and a multi-language user interface, it supports simultaneous operation of multiple users, improving the flexibility and internationalization level of the system.

[0018] By an improved closed-loop control algorithm, the present invention dynamically adjusts the speed and pressure of the powder conveying system to ensure the precise matching of the powder conveying volume and the spraying task requirements, not only improving the spraying efficiency, but also reducing the production cost by reducing unnecessary powder waste. Description of the Drawings

[0019] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0020] Figure 1It is the flowchart of the method provided by the embodiment of the present invention; Figure 2 It is the system architecture diagram provided by the embodiment of the present invention. Detailed implementation manners

[0021] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following combines the drawings and preferred embodiments to detail the specific implementation manners, structures, features and effects of a remote management and control method for an electrostatic powder spraying device proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0022] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0023] The following embodiments are for illustrative purposes only and are not intended to limit the scope of the present invention.

[0024] The following specifically describes the specific solution of a remote management and control method for an electrostatic powder spraying device provided by the present invention with reference to the drawings.

[0025] Please refer to Figure 1 , which shows the flowchart of a remote management and control method for an electrostatic powder spraying device provided by an embodiment of the present invention. The method includes the following steps: Step S1, connect the electrostatic powder spraying device to the remote control center through the industrial Internet of Things platform and perform initialization settings; Among them, in step S1, the following sub-steps are further included: S1-1, establish a secure communication link between the electrostatic powder spraying device and the remote control center through the industrial Internet of Things platform, and encrypt the communication link using blockchain technology; S1-2, configure the basic parameters and safety parameters of the device. The basic parameters include the initial voltage, current and powder flow rate of the spray gun, and the safety parameters include overvoltage protection, overcurrent protection and temperature protection; S1-3, initialize the operating state of the device, and detect whether the components are working properly through the self-check program of the device. The components include the spray gun, powder delivery system and electrostatic generator; S1-4, send an initialization instruction to the device through the remote control center. After the device receives the instruction, it executes the initialization process and feeds back the initialization result to the remote control center, and is ready to start the spraying operation.

[0026] It should be noted that the Industrial Internet of Things platform: a platform based on cloud computing and big data technologies, used to connect and manage various industrial devices, provides communication interfaces between devices, enabling devices to exchange data with a remote control center through a network.

[0027] Remote control center: The remote control center is a centralized management system used to manage and monitor multiple electrostatic powder spraying devices, communicates with the devices through the Industrial Internet of Things platform, sends control instructions and receives feedback information from the devices.

[0028] Secure communication link: To ensure the security of data transmission, the communication link needs to be encrypted, using blockchain technology. The distributed ledger feature of the blockchain can ensure the immutability and transparency of data; through blockchain technology, each data transmission will be recorded on the blockchain, and any unauthorized modification will be detected, thus ensuring the security of communication.

[0029] Initial voltage of the spray gun: Voltage is an important parameter affecting the spraying quality. The setting of the initial voltage needs to be adjusted according to the spraying process requirements and workpiece characteristics. For thicker workpieces, a higher initial voltage is required to ensure uniform powder adhesion.

[0030] Initial current of the spray gun: The magnitude of the current directly affects the spraying efficiency of the spray gun and the adhesion of the powder. The setting of the initial current needs to be adjusted according to the voltage of the spray gun and the spraying distance to ensure the spraying effect.

[0031] Powder flow rate: The control of the powder flow rate is crucial for the spraying quality. The setting of the initial powder flow rate needs to be adjusted according to the requirements of the spraying task to ensure uniform powder distribution.

[0032] Overvoltage protection: Set a voltage upper limit. When the voltage of the spray gun exceeds this upper limit, the system will automatically cut off the power supply to prevent equipment damage.

[0033] Overcurrent protection: Set a current upper limit. When the current of the spray gun exceeds this upper limit, the system will automatically cut off the power supply to prevent equipment damage.

[0034] Temperature protection: Set a temperature upper limit. When the temperature of the equipment exceeds this upper limit, the system will automatically start the cooling system or cut off the power supply to prevent equipment overheating damage.

[0035] Initialization of the operating state: When the equipment starts up, the system will perform a series of initialization operations, including checking whether each component of the equipment is in a normal state. The initialization process includes hardware initialization and software initialization to ensure that the equipment can operate normally when starting up.

[0036] Self - checking program: The self - checking program is an automatic detection mechanism inside the device, used to check whether the key components of the device are working properly. The self - checking program will sequentially check the spray gun, powder delivery system, and electrostatic generator components to ensure they are in a normal state before startup.

[0037] Spray gun detection: Check whether the voltage, current, and nozzle of the spray gun are working properly. If the voltage or current of the spray gun is abnormal, or the nozzle is blocked, the self - checking program will issue an alarm.

[0038] Powder delivery system detection: Check whether the pipeline of the powder delivery system is unobstructed and whether the powder flow rate is normal. If the pipeline is blocked or the powder flow rate is abnormal, the self - checking program will issue an alarm.

[0039] Electrostatic generator detection: Check whether the voltage and current of the electrostatic generator are normal. If the voltage or current of the electrostatic generator is abnormal, the self - checking program will issue an alarm.

[0040] Initialization instructions: The initialization instructions sent by the remote control center to the device include the setting of the device's basic parameters and safety parameters, as well as the instruction to start the self - checking program. After receiving these instructions, the device will perform initialization operations according to the instructions.

[0041] Feedback mechanism: After the device completes the initialization operation, it will feedback the initialization result to the remote control center. The feedback information includes the operating status of the device and the self - checking result. The remote control center judges whether the device is ready to start the spraying operation based on the feedback information.

[0042] Step S2: Use sensors to collect the operating data of the device in real - time and transmit the data to the remote control center through an encrypted communication protocol; Among them, in step S2, the following sub - steps are also included: S2 - 1: Monitor the operating status of the device by installing sensors. The sensors include voltage sensors, current sensors, flow sensors, temperature sensors, and humidity sensors; S2 - 2: Perform real - time pre - processing on the collected data. The pre - processing includes data cleaning, noise filtering, and outlier detection; S2 - 3: Use an encrypted communication protocol to encrypt and transmit the data, and introduce data compression technology to compress the collected data in real - time to reduce the data transmission volume. The encrypted communication protocol includes the Transport Layer Security protocol, Secure Sockets Layer protocol, Advanced Encryption Standard, and Hash - based Message Authentication Code. The data compression technology includes Huffman coding, arithmetic coding, LZ77 algorithm, LZ78 algorithm, LZW algorithm, and DEFLATE algorithm; S2 - 4: The remote control center decrypts and decompresses the received data and performs secondary verification.

[0043] Note that the voltage sensor is used to monitor the voltage of the spray gun to ensure that the voltage is within the preset range to guarantee the spraying quality.

[0044] The current sensor is used to monitor the current of the spray gun to ensure that the current is within the preset range to prevent equipment overload.

[0045] The flow sensor is used to monitor the powder flow rate to ensure that the powder delivery volume matches the requirements of the spraying task.

[0046] The temperature sensor is used to monitor the operating temperature of the equipment to ensure that the equipment operates within a safe temperature range.

[0047] The humidity sensor is used to monitor the humidity of the spraying environment to ensure that the environmental humidity is within an appropriate range to prevent powder from being affected by moisture and affecting the spraying effect.

[0048] Data cleaning: Removing invalid or incorrect data from the data to ensure data integrity and accuracy.

[0049] Noise filtering: Removing noise from the data through a filtering algorithm to improve the signal-to-noise ratio of the data.

[0050] Outlier detection: Identifying and handling outliers in the data to ensure data reliability.

[0051] Transport Layer Security (TLS): A widely used encryption protocol for ensuring the security and confidentiality of data during transmission.

[0052] Secure Sockets Layer (SSL): The predecessor of TLS, also used for encrypting data transmission.

[0053] Advanced Encryption Standard (AES): A symmetric encryption algorithm for encrypting data to ensure data security during transmission.

[0054] Hashed Message Authentication Code (HMAC): Used to verify the integrity and origin of data to ensure that the data has not been tampered with.

[0055] Huffman coding: A lossless compression algorithm that achieves data compression by counting the frequency of character occurrences.

[0056] Arithmetic coding: A lossless compression algorithm that achieves data compression through a probability model.

[0057] LZ77 algorithm: A dictionary-based compression algorithm that achieves data compression by finding repeated substrings.

[0058] LZ78 algorithm: Another dictionary-based compression algorithm that achieves data compression by constructing a dictionary.

[0059] LZW algorithm: An improved LZ78 algorithm that achieves efficient compression by dynamically constructing a dictionary.

[0060] DEFLATE algorithm: A compression algorithm that combines LZ77 and Huffman coding and is widely used for data compression.

[0061] Decryption process: After the remote control center receives the encrypted data, it uses the corresponding decryption algorithm to decrypt the data and restore the original data.

[0062] Decompression process: The decrypted data may be compressed. The remote control center uses the corresponding decompression algorithm to decompress the data and restore the original size of the data.

[0063] Secondary verification: To ensure the integrity and security of the data, the remote control center performs secondary verification on the received data. The verification content includes the integrity of the data and the legality of the source.

[0064] Step S3, according to the preset spraying process requirements and the real-time collected data, optimize the spraying parameters through an intelligent algorithm based on machine learning; Among them, in step S3, the following sub-steps are also included: S3-1, adjust the spraying parameters through a deep reinforcement learning algorithm to achieve the preset spraying process requirements. The deep reinforcement learning algorithm includes Deep Q Network, Double Deep Q Network, Deep Deterministic Policy Gradient, Soft Actor-Critic algorithm, and Proximal Policy Optimization. The spraying parameters include spraying speed, spraying distance, spraying angle, spraying pressure, coating thickness, powder particle size, environmental humidity, and temperature. The spraying process requirements include spraying uniformity, coverage rate, and coating thickness; S3-2, combine a generative adversarial network to generate adjusted spraying parameter combinations and optimize them through the adversarial training of the generator and discriminator; S3-3, adopt transfer learning technology to transfer the existing spraying process knowledge to the spraying task, reducing the learning time and cost of the new task; S3-4, through an online learning algorithm, combine sensor data to update the spraying parameters in real time. The online learning algorithm includes stochastic gradient descent and mini-batch gradient descent. The sensor data includes voltage, current, powder flow rate, temperature, and humidity.

[0065] It should be noted that the Deep Q Network (DQN): combines the Q-learning algorithm with a deep neural network to learn the optimal spraying parameter adjustment strategy to achieve the preset spraying process requirements.

[0066] Double Deep Q Network (Double DQN): An improved DQN algorithm that reduces the overestimation problem and improves the stability and performance of the algorithm by separating the estimation and selection of the value function.

[0067] Deep Deterministic Policy Gradient (DDPG): A reinforcement learning algorithm applicable to continuous action spaces, capable of dynamically adjusting spraying parameters to ensure spraying uniformity and coverage.

[0068] Soft Actor-Critic algorithm (SAC): Through maximum entropy reinforcement learning, it balances exploration and exploitation to improve the robustness and adaptability of the algorithm.

[0069] Proximal Policy Optimization (PPO): An improved policy gradient algorithm that improves the stability and convergence speed of the algorithm by restricting the magnitude of policy updates.

[0070] Spraying speed: Controls the moving speed of the spray gun, affecting spraying uniformity and coverage.

[0071] Spraying distance: Controls the distance between the spray gun and the workpiece, affecting spraying uniformity and coating thickness.

[0072] Spraying angle: Controls the spraying angle of the spray gun, affecting spraying uniformity and coverage.

[0073] Spraying pressure: Controls the pressure during spraying, affecting the adhesion of the powder and the coating thickness.

[0074] Coating thickness: Directly reflects the spraying quality and needs to be precisely controlled.

[0075] Powder particle size: Affects spraying uniformity and coating quality.

[0076] Ambient humidity and temperature: Affect the adhesion of the powder and the spraying effect.

[0077] Spraying uniformity: Ensures uniform distribution of the coating on the workpiece surface.

[0078] Coverage rate: Ensures complete coverage of the workpiece surface without omission.

[0079] Coating thickness: Ensures that the coating meets the preset thickness requirements.

[0080] Generative Adversarial Network: A deep learning model used to generate new data samples that are indistinguishable from real data in terms of distribution. The core idea is to achieve data generation through adversarial training of two neural networks, a generator and a discriminator.

[0081] Generator: A neural network whose goal is to generate fake data as close as possible to real data. Starting from a random noise vector (Gaussian distribution), it generates data samples through a series of non-linear transformations. The output of the generator is a vector with the same dimension as the real data.

[0082] Discriminator: The goal is to distinguish between the fake data generated by the generator and the real data. It is also a neural network that receives input data (whether it is the fake data generated by the generator or the real data) and outputs a probability value indicating the probability that the input data is real data.

[0083] Adversarial training: The generator and the discriminator compete with each other. The generator tries to generate better parameter combinations, and the discriminator tries to distinguish the generated parameter combinations from the actual data. Through this adversarial mechanism, the generator can gradually generate parameter combinations closer to the actual requirements.

[0084] Transfer learning: Utilize the existing knowledge of the spraying process (historical data, pre-trained models) and transfer it to a new spraying task, which can be achieved through fine-tuning of the pre-trained model and feature extraction methods.

[0085] Reduce learning time and cost: Through transfer learning, the new task can quickly adapt by leveraging the existing knowledge, reducing the time and computing resources required to learn from scratch.

[0086] Stochastic Gradient Descent (SGD): Only use one data point each time to update the model parameters, with high computational efficiency and suitable for processing large-scale datasets.

[0087] Mini-batch Gradient Descent (Mini-batch GD): Use a small batch of data each time to update the model parameters, combining the efficiency of SGD and the stability of batch gradient descent.

[0088] Voltage: Monitor the voltage of the spray gun to ensure that the voltage is within the preset range.

[0089] Current: Monitor the current of the spray gun to ensure that the current is within the preset range.

[0090] Powder flow rate: Monitor the powder delivery volume to ensure that the powder flow rate matches the requirements of the spraying task.

[0091] Temperature: Monitor the operating temperature of the equipment to ensure that the equipment operates within a safe temperature range.

[0092] Humidity: Monitor the humidity of the spraying environment to ensure that the environmental humidity is within an appropriate range.

[0093] Step S4, perform real-time analysis on the equipment operation data, detect abnormal data through dynamic threshold, and issue an alarm through a multi-level alarm mechanism when an abnormality is found; Among them, in step S4, the following sub-steps are also included: S4-1. Collect the historical operation data of the device, analyze the historical operation data, and calculate the statistical characteristics of each sensor data. The historical operation data includes the sensor data during normal operation and the sensor data during faults. The statistical characteristics include the mean, standard deviation, minimum value, and maximum value. S4-2. Set the initial threshold range for each sensor data according to the statistical characteristics. The initial threshold range is the mean plus or minus twice the standard deviation. S4-3. Calculate the short-term statistical characteristics and long-term statistical characteristics of the sensor data, and compare them to evaluate the change trend of the data. The short-term statistical characteristics include the mean, standard deviation, maximum value, and minimum value within the sliding window. The long-term statistical characteristics include the mean, standard deviation, maximum value, and minimum value over a past period of time. The change trend includes an upward trend and a downward trend. S4-4. Set the dynamically adjusted threshold according to the change trend of the data, and regularly re-evaluate and adjust the threshold. Regularly includes every 24 hours, every week, and every month. S4-5. Analyze the device operation data in real time, compare it with the dynamic threshold, and detect whether there is abnormal data. S4-6. When abnormal data is detected, send an alarm through a multi-level alarm mechanism. The multi-level alarm mechanism includes a sound alarm, a text message notification, an email notification, and a pop-up notification on the remote terminal.

[0094] It should be noted that the historical operation data: collect the sensor data of the device in normal operation and fault states. These data are used for subsequent analysis and threshold setting.

[0095] Statistical characteristics: Mean: The average value of the data, reflecting the central tendency of the data.

[0096] Standard deviation: The degree of dispersion of the data, reflecting the fluctuation of the data.

[0097] Minimum value and maximum value: The range of the data, reflecting the extreme conditions of the data.

[0098] Initial threshold range: Set the initial threshold range according to the statistical characteristics, usually the mean plus or minus twice the standard deviation. This method assumes that the data follows a normal distribution, and 95% of the data points will fall within this range.

[0099] Short-term statistical characteristics: Calculate the short-term mean, standard deviation, maximum value, and minimum value through a sliding window, reflecting the change of the data in the short term.

[0100] Long-term statistical characteristics: Calculate the mean, standard deviation, maximum value, and minimum value over a past period of time, reflecting the change of the data in the long term.

[0101] Trend: By comparing short-term and long-term statistical features, evaluate the trend of the data, including upward and downward trends. If the short-term mean is significantly higher than the long-term mean, it indicates an upward trend in the data; conversely, if the short-term mean is significantly lower than the long-term mean, it indicates a downward trend in the data.

[0102] Dynamic threshold adjustment: According to the trend of the data, dynamically adjust the threshold. If the data has an upward trend and exceeds the current threshold multiple times in a row, but the device is operating normally, it indicates that the threshold may be set too low and needs to be appropriately increased; if the data has a downward trend and exceeds the current threshold multiple times in a row, but the device is operating normally, it indicates that the threshold may be set too high and needs to be appropriately decreased. Regular re-evaluation and adjustment of the threshold: Regularly (every 24 hours, weekly, and monthly) re-evaluate and adjust the threshold to ensure that the threshold can adapt to the actual operating conditions of the device.

[0103] Real-time analysis: The system monitors the operating data of the device in real time and obtains real-time data through sensors.

[0104] Anomaly detection: Compare the real-time data with the dynamic threshold to detect whether there is abnormal data. If the real-time data exceeds the dynamic threshold range, it is considered that there is abnormal data.

[0105] Multi-level alarm mechanism: When abnormal data is detected, the system issues an alarm in multiple ways to ensure that the operator can receive the notification in a timely manner.

[0106] Sound alarm: Issue a sound alarm through the device to remind on-site operators.

[0107] SMS notification: Send the alarm information to relevant personnel via SMS.

[0108] Email notification: Send the alarm information to relevant personnel via email.

[0109] Pop-up notification on the remote terminal: Pop up an alarm notification through the remote terminal (mobile APP, computer) to remind the operator.

[0110] Step S5, dynamically adjust the speed and pressure of the powder conveying system through an improved closed-loop control algorithm to achieve the matching of the powder conveying volume and the spraying task requirements; Among them, in step S5, the following sub-steps are also included: S5-1, set the initial speed and pressure parameters of the powder conveying system, and calculate the required powder conveying volume according to the actual spraying requirements; S5-2, real-time monitor the output parameters of the powder conveying system through sensors, and the output parameters include powder flow rate, conveying speed, and pressure; S5-3. Calculate the adjustment amount based on the deviation between the actual output parameters and the preset target parameters, and dynamically adjust the speed and pressure of the powder conveying system. The specific formula is as follows: Where, T represents the adjustment amount, and Z represents the deviation. 、 、 are the control coefficients of proportional, integral, and derivative respectively. represents the small change in time, that is, the time interval. represents the integral of the deviation, that is, the cumulative value of the deviation over time. represents the small change in the deviation, that is, the change amount of the deviation. represents the derivative of the deviation, that is, the rate of change of the deviation over time. S5-4: Continuously monitor the adjusted output parameters to achieve the matching of the powder conveying volume and the requirements of the spraying task.

[0111] It should be noted that the initial speed and pressure parameters: Before the spraying operation starts, the initial speed and pressure parameters of the powder conveying system need to be set, and they are initially configured according to the specifications of the equipment and historical experience.

[0112] Calculate the powder conveying volume: According to the requirements of the actual spraying task, calculate the required powder conveying volume, which can be determined by analyzing the shape, size, and coating thickness requirements of the workpiece. For larger workpieces or spraying tasks that require thicker coatings, a higher powder conveying volume is needed.

[0113] Deviation calculation: Calculate the deviation between the actual output parameters (powder flow rate, conveying speed, and pressure) and the preset target parameters. The deviation is the difference between the actual value and the target value.

[0114] Closed-loop control algorithm: Use the PID (Proportional-Integral-Derivative) control algorithm to calculate the adjustment amount. The PID algorithm is a commonly used closed-loop control algorithm that adjusts the control amount through three parts: proportional, integral, and derivative.

[0115] Proportional part: Directly adjust the control amount according to the magnitude of the deviation. The proportional coefficient determines the intensity of the adjustment.

[0116] Integral part: Adjust the control amount according to the cumulative value of the deviation. The integral coefficient helps to eliminate the steady-state error.

[0117] Derivative part: Adjust the control amount according to the rate of change of the deviation. The derivative coefficient helps to reduce the overshoot and oscillation of the system.

[0118] Dynamic adjustment: According to the calculated adjustment amount T, dynamically adjust the speed and pressure of the powder conveying system to make the actual output parameters close to the preset target parameters.

[0119] Continuous monitoring: The system continuously monitors the adjusted output parameters to ensure that the operating status of the powder conveying system meets the preset target.

[0120] Demand matching: By dynamically adjusting the speed and pressure, ensure that the powder delivery volume precisely matches the requirements of the spraying task, which not only improves the spraying efficiency, but also reduces powder waste and lowers production costs.

[0121] Step S6, perform real-time operation and monitoring of the device through a remote terminal. The remote terminal provides a user interface and supports simultaneous operation by multiple users and permission management; Among them, in step S6, the following sub-steps are also included: S6-1, integrate the real-time video monitoring function, enabling operators to view the real-time video of the device through the remote terminal, understand the operating status of the device, and send operation instructions through the remote terminal to control the startup, stop, and parameter adjustment of the device. The remote terminal includes computers, tablets, mobile phones, and industrial handheld terminals; S6-2, provide a user interface through the remote terminal. The user interface includes a real-time data display interface, a parameter adjustment interface, and a fault diagnosis information display interface; S6-3, provide role-based access control, allowing the system administrator to assign different permissions according to the user's role, so that each user can only access and operate the functions within their permission scope; S6-4, record operation logs for auditing and device maintenance. The operation logs include operation time, operation content, and operation results.

[0122] It should be noted that for real-time video monitoring: The system integrates the video monitoring function, captures the operating status of the device in real time through the camera, and transmits the video stream to the remote terminal. Operators can view these videos through the remote terminal to intuitively understand the operating conditions of the device.

[0123] Remote control: Operators can send operation instructions through the remote terminal to control the startup, stop, and parameter adjustment of the device. The instructions are transmitted through the network to the remote control center, and the device executes corresponding operations according to the received instructions.

[0124] User interface: The remote terminal provides an intuitive user interface through which operators can conveniently view videos and send instructions.

[0125] Computer (PC): Provides the most comprehensive functions, including real-time data display, parameter adjustment, fault diagnosis information display, and video monitoring, suitable for scenarios that require complex operations and detailed monitoring.

[0126] Tablet: Offers portability and flexibility, suitable for use in workshops or on-site. It has a touchscreen interface, making operations intuitive and convenient.

[0127] Smartphone: Provides a high degree of portability, suitable for monitoring and operation anytime and anywhere. It connects to the system through a mobile application (App).

[0128] Industrial Handheld Device: Has higher durability and anti-interference ability, suitable for use in harsh industrial environments. It offers functions similar to those of a tablet but is more rugged and durable.

[0129] Real-time data display interface: The user interface provides a real-time data display area that shows the key operating data of the device, including powder flow rate, conveying speed, and pressure. These data are collected by sensors and transmitted to the remote terminal in real time.

[0130] Parameter adjustment interface: The user interface provides a parameter adjustment area where operators can manually adjust the operating parameters of the device, including the voltage, current, and spraying speed of the spray gun.

[0131] Fault diagnosis information display interface: The user interface provides a fault diagnosis information display area that shows the fault status and diagnosis information of the device, helping operators quickly understand the health status of the device and take corresponding measures.

[0132] Role-based access control (RBAC): The system implements a role-based access control mechanism. The system administrator can assign different permissions according to the responsibilities and roles of users. Ordinary operators may only be able to view the device status and send basic operation instructions, while senior operators or administrators can perform parameter adjustment and system configuration.

[0133] Permission management: The system provides a permission management function that allows administrators to flexibly configure and manage user permissions. Permissions include viewing data, sending instructions, adjusting parameters, and configuring the system.

[0134] Operation log: The system records all operations performed by users through the remote terminal, including operation time, operation content, and operation results. The log information is stored in the system database and can be queried and analyzed at any time.

[0135] Auditing and Maintenance: The operation logs are used to audit the operation behaviors of users to ensure the security and compliance of the system. The logs are also used for the maintenance and troubleshooting of devices, helping maintenance personnel quickly locate problems and take measures.

[0136] Please refer to Figure 2 , which shows the system architecture diagram of a system provided by an embodiment of the present invention for implementing the remote management and control method of an electrostatic powder spraying device, including: A remote control center, which is used to centrally manage and coordinate the data flow and control instructions between various modules; It should be noted that the remote control center is a centralized management unit, which is connected to each distributed module and can monitor, operate and manage these modules to achieve centralized control and coordination of the entire system.

[0137] Instruction Generation: The remote control center generates control instructions according to the system requirements and rules. The instructions may be direct commands based on user input or may be automatically generated according to the data analysis results.

[0138] Instruction Distribution: The generated control instructions are sent to each module through the network. The control center needs to ensure that the instructions can reach the target module accurately and in a timely manner.

[0139] Instruction Execution and Feedback: After each module receives the control instructions, it executes the corresponding operations and feeds back the execution results to the control center. The control center further adjusts the control strategy according to the feedback information.

[0140] An industrial Internet of Things module, which is used to connect the electrostatic powder spraying device to the remote control center and perform initialization settings; It should be noted that for connecting the device: Through the industrial Internet of Things platform, a communication connection is established between the electrostatic powder spraying device and the remote control center, including network configuration, device registration and authentication.

[0141] Initialization Settings: Include the basic parameter configuration of the device (initial voltage, current and powder flow rate of the spray gun), safety parameter settings (overvoltage protection, overcurrent protection and temperature protection), and initialization of the device operation status (self-check program and sending of initialization instructions).

[0142] A data acquisition and transmission module, which is used to collect the operation data of the device in real time through sensors and transmit the data to the remote control center through an encrypted communication protocol; It should be noted that sensors: The sensors installed on the device are used to monitor the operation status in real time, including voltage sensors, current sensors, flow sensors, temperature sensors and humidity sensors.

[0143] Data preprocessing: Clean, filter noise, and detect outliers in the collected data to ensure data accuracy and reliability.

[0144] Encrypted communication: Use encrypted communication protocols (TLS, SSL, AES) to encrypt data during transmission to ensure data security and confidentiality during the transmission process.

[0145] Data compression: Introduce data compression technology to compress the collected data in real time, reduce the data transmission volume, and improve transmission efficiency.

[0146] Parameter optimization module, which is used to optimize spraying parameters through intelligent algorithms based on machine learning according to preset spraying process requirements and real-time collected data; It should be noted that machine learning algorithms include deep reinforcement learning algorithms (such as DQN, Double DQN, DDPG, SAC, PPO), generative adversarial networks (GAN), and transfer learning techniques.

[0147] Spraying parameters: The optimized parameters include spraying speed, spraying distance, spraying angle, spraying pressure, coating thickness, powder particle size, environmental humidity, and temperature.

[0148] Spraying process requirements: The preset process requirements include spraying uniformity, coverage rate, and coating thickness.

[0149] Real-time optimization: Dynamically adjust spraying parameters according to real-time data to ensure that the spraying process meets the preset process requirements.

[0150] Fault diagnosis module, which is used to perform real-time analysis on equipment operation data, detect abnormal data through dynamic thresholds, and issue alarms through a multi-level alarm mechanism when abnormalities are found; It should be noted that the dynamic threshold: Dynamically adjusts the determination threshold of abnormal data according to the historical operation data and real-time operation status of the equipment.

[0151] Real-time analysis: Real-time monitor equipment operation data, compare it with the dynamic threshold, and detect whether there is abnormal data.

[0152] Multi-level alarm mechanism: When abnormal data is detected, issue alarms through sound alarms, SMS notifications, email notifications, and pop-up notifications on remote terminals.

[0153] Closed-loop control module, which is used to dynamically adjust the speed and pressure of the powder delivery system through an improved closed-loop control algorithm to achieve the matching of the powder delivery volume and the spraying task requirements; It should be noted that initial parameter setting: Set the initial speed and pressure parameters of the powder delivery system, and calculate the required powder delivery volume according to actual spraying requirements.

[0154] Real-time monitoring: The output parameters of the powder conveying system are monitored in real time through sensors, including powder flow rate, conveying speed, and pressure.

[0155] Dynamic adjustment: Based on the deviation between the actual output parameters and the preset target parameters, the adjustment amount is calculated using a closed-loop control algorithm (PID control algorithm), and the speed and pressure of the powder conveying system are dynamically adjusted.

[0156] Continuous monitoring: Continuously monitor the adjusted output parameters to ensure that the powder delivery volume precisely matches the requirements of the spraying task.

[0157] User interaction module, used to perform real-time operation and monitoring of the device through a remote terminal, provides a user interface, and supports multi-user simultaneous operation and permission management.

[0158] It should be noted that the remote terminal: includes computers, tablets, smartphones, and industrial handheld terminals, providing flexible access methods.

[0159] User interface: Provides an intuitive user interface, including a real-time data display interface, a parameter adjustment interface, and a fault diagnosis information display interface.

[0160] Multi-user support: Supports multi-user simultaneous operation, and each user can perform corresponding operations according to their permissions.

[0161] Permission management: Provides role-based access control, allowing the system administrator to assign different permissions according to the user's role.

[0162] Operation log: Records operation logs, including operation time, operation content, and operation results, for auditing and equipment maintenance.

[0163] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A remote management and control method for electrostatic powder spraying equipment, characterized in that: The method includes: Step S1, connecting the electrostatic powder spraying equipment to the remote control center through the industrial Internet of Things platform and performing initialization settings; Step S2, using sensors to collect equipment operation data in real time, and transmitting the data to a remote control center through an encrypted communication protocol; Step S3, optimizing the spraying parameters through an intelligent algorithm based on machine learning according to preset spraying process requirements and real-time collected data; Step S4, real-time analysis of equipment operation data, detection of abnormal data through dynamic thresholds, and issuance of alarms through a multi-level alarm mechanism when an abnormality is found; Step S5, dynamically adjusting the speed and pressure of the powder conveying system through an improved closed-loop control algorithm to achieve matching of the powder conveying volume with the spraying task requirements; Step S6, real-time operation and monitoring of the device is performed through a remote terminal, which provides a user interface and supports simultaneous multi-user operation and authority management.

2. A remote management and control method for electrostatic powder spraying equipment according to claim 1, characterized in that: Wherein step S1 also includes the following sub-steps: S1-1, establish a secure communication link between the electrostatic powder spraying equipment and the remote control center through the industrial Internet of Things platform, and use blockchain technology to encrypt the communication link; S1-2, configure basic parameters and safety parameters of the equipment, the basic parameters include the initial voltage, current and powder flow rate of the spray gun, and the safety parameters include overvoltage protection, overcurrent protection and temperature protection; S1-3, initializing the operating state of the equipment, and detecting whether the components are working normally through the self-test program of the equipment, the components including the spray gun, the powder delivery system and the electrostatic generator; S1-4, sending an initialization command to the device through the remote control center. After receiving the command, the device executes the initialization process and feeds back the initialization result to the remote control center, preparing to start the spraying operation.

3. A remote management and control method for electrostatic powder spraying equipment according to claim 1, characterized in that: Wherein step S2 also includes the following sub-steps: S2-1, monitoring the operating status of the equipment by installing sensors, wherein the sensors include a voltage sensor, a current sensor, a flow sensor, a temperature sensor and a humidity sensor; S2-2, performing real-time preprocessing on the collected data, wherein the preprocessing includes data cleaning, noise filtering and outlier detection; S2-3, using an encrypted communication protocol to encrypt data for transmission, and introducing data compression technology to compress the collected data in real time to reduce the amount of data transmission. The encrypted communication protocol includes the Transport Layer Security Protocol, the Secure Sockets Layer Protocol, the Advanced Encryption Standard and the Hash Message Authentication Code. The data compression technology includes Huffman coding, arithmetic coding, LZ77 algorithm, LZ78 algorithm, LZW algorithm and DEFLATE algorithm; S2-4, decrypting and decompressing the received data through the remote control center, and performing secondary verification.

4. A remote management and control method for electrostatic powder spraying equipment according to claim 1, characterized in that: Wherein step S3 also includes the following sub-steps: S3-1, adjusting the spraying parameters through a deep reinforcement learning algorithm to achieve the preset spraying process requirements, the deep reinforcement learning algorithm includes a deep Q network, a dual deep Q network, a deep deterministic policy gradient, a soft actor-critic algorithm and a proximal policy optimization, the spraying parameters include spraying speed, spraying distance, spraying angle, spraying pressure, coating thickness, powder particle size, ambient humidity and temperature, and the spraying process requirements include spraying uniformity, coverage and coating thickness; S3-2, generate the adjusted spray parameter combination by combining the generative adversarial network, and optimize it through adversarial training of the generator and the discriminator; S3-3, using transfer learning technology to transfer existing spraying process knowledge to spraying tasks, reducing the learning time and cost of new tasks; S3-4, updating the spraying parameters in real time through an online learning algorithm combined with sensor data, wherein the online learning algorithm includes stochastic gradient descent and small batch gradient descent, and the sensor data includes voltage, current, powder flow, temperature and humidity.

5. The remote management and control method for electrostatic powder spraying equipment according to claim 1, characterized in that: Wherein step S4 also includes the following sub-steps: S4-1, collecting historical operation data of the equipment, analyzing the historical operation data, and calculating statistical features of each sensor data, wherein the historical operation data includes sensor data during normal operation and sensor data during failure, and the statistical features include mean, standard deviation, minimum value, and maximum value; S4-2, according to the statistical characteristics, setting an initial threshold range for each sensor data, wherein the initial threshold range is the mean plus or minus two times the standard deviation; S4-3, calculating the short-term statistical features and long-term statistical features of the sensor data, and comparing them to evaluate the change trend of the data, wherein the short-term statistical features include the mean, standard deviation, maximum value and minimum value within the sliding window, and the long-term statistical features include the mean, standard deviation, maximum value and minimum value within the past period of time; the change trend includes an upward trend and a downward trend; S4-4, set dynamic adjustment thresholds according to the changing trend of data, and re-evaluate and adjust the thresholds regularly, including every 24 hours, every week and every month; S4-5, analyze the equipment operation data in real time, compare it with the dynamic threshold, and detect whether there is abnormal data; S4-6, when abnormal data is detected, an alarm is issued through a multi-level alarm mechanism, and the multi-level alarm mechanism includes a sound alarm, a text message notification, an email notification, and a pop-up window notification of a remote terminal.

6. A remote management and control method for electrostatic powder spraying equipment according to claim 1, characterized in that: Wherein, in step S5, the following sub-steps are also included: S5-1, set the initial speed and pressure parameters of the powder delivery system, and calculate the required powder delivery amount according to the actual spraying requirements; S5-2, monitoring the output parameters of the powder conveying system in real time through sensors, wherein the output parameters include powder flow rate, conveying speed and pressure; S5-3, according to the deviation between the actual output parameter and the preset target parameter, the closed-loop control algorithm is used to calculate the adjustment amount, and the speed and pressure of the powder conveying system are dynamically adjusted. The specific formula is: Among them, T represents the adjustment amount, Z represents the deviation, , , are the proportional, integral and differential control coefficients respectively, Indicates small changes in time, i.e. time intervals, represents the integral of the deviation, that is, the cumulative value of the deviation over time, Indicates a small change in the deviation, that is, the amount of change in the deviation, represents the derivative of the deviation, that is, the rate of change of the deviation over time; S5-4: Continuously monitor the adjusted output parameters to match the powder delivery volume with the requirements of the spraying task.

7. The remote management and control method of electrostatic powder spraying equipment according to claim 1, characterized in that: Wherein, in step S6, the following sub-steps are also included: S6-1, integrated with real-time video monitoring function, enables operators to view real-time video of the equipment through remote terminals, understand the operating status of the equipment, and send operating instructions through remote terminals to control the start, stop and parameter adjustment of the equipment. The remote terminals include computers, tablets, mobile phones and industrial-grade handheld terminals; S6-2, providing a user interface through a remote terminal, wherein the user interface includes a real-time data display interface, a parameter adjustment interface, and a fault diagnosis information display interface; S6-3 provides role-based access control, allowing system administrators to assign different permissions based on user roles, so that each user can only access and operate functions within their permissions; S6-4, record the operation log for auditing and equipment maintenance, the operation log includes the operation time, operation content, and operation result.

8. A system for implementing the remote management and control method of electrostatic powder spraying equipment as claimed in claim 1, characterized in that: include: Remote control center, used to centrally manage and coordinate data flows and control instructions between various modules; Industrial IoT module, used to connect electrostatic powder spraying equipment to a remote control center and perform initialization settings; Data collection and transmission module, used to collect equipment operation data in real time through sensors and transmit the data to the remote control center through encrypted communication protocols; Parameter optimization module, which is used to optimize spraying parameters through intelligent algorithms based on machine learning according to preset spraying process requirements and real-time collected data; Fault diagnosis module, which is used to analyze the equipment operation data in real time, detect abnormal data through dynamic thresholds, and issue alarms through a multi-level alarm mechanism when an abnormality is found; Closed-loop control module, used to dynamically adjust the speed and pressure of the powder delivery system through an improved closed-loop control algorithm to match the powder delivery volume with the spraying task requirements; The user interaction module is used to operate and monitor the device in real time through a remote terminal, provide a user interface, and support multi-user simultaneous operation and authority management.

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