Remote control system and control method for spraying coating machine

Abstract

The invention discloses a remote control system and a remote control method for a spraying coating machine. The remote control system comprises a data acquisition module, a central processing module, a remote communication module, a remote monitoring terminal, an execution control module, an equipment state monitoring module, a fault diagnosis module and a process parameter optimization module, according to the remote control system provided by the invention, a plurality of functional modules are integrated, comprehensive monitoring and control on the spraying coating machine can be realized, and the reliability and the stability of the equipment are improved. And through the remote communication module, an operator can monitor the state of equipment anytime and anywhere and adjust process parameters in time, so that the production efficiency and the coating quality are improved. And the fault diagnosis module can quickly and accurately diagnose equipment faults, so that the fault shutdown time is shortened, and the maintenance cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of spray coating machine control, and in particular to a remote control system and a control method for a spray coating machine. Background Art

[0002] Spray coating machines are widely used in industrial production to form thin films with specific functions on the surfaces of various workpieces. With the development of industrial automation and intelligentization, the demand for remote control of spray coating machines is increasing. Traditional spray coating machine control systems usually adopt local control methods. Operators need to monitor and operate the equipment on site, and remote real-time monitoring and control cannot be achieved. This leads to low production efficiency and the inability to respond to equipment failures and process parameter adjustments in a timely manner. In addition, the module composition of traditional systems is relatively simple, the collection and analysis of equipment operating status is not comprehensive, the optimization of process parameters relies on manual experience, and lacks scientific algorithm support, making it difficult to achieve high-precision and high-efficiency coating production. Summary of the Invention

[0003] The object of the present invention is to provide a remote control system and control method for a spray coating machine to solve the problems raised in the above background technology.

[0004] To achieve the above-mentioned object, the present invention provides the following technical solutions: a remote control system for a spray coating machine, comprising a data acquisition module, a central processing module, a remote communication module, a remote monitoring terminal, an execution control module, an equipment status monitoring module, a fault diagnosis module and a process parameter optimization module;

[0005] The data acquisition module is used to obtain the operating status information of the spray coating machine; it integrates a temperature sensor, a pressure sensor, a flow sensor, a displacement sensor, a speed sensor and an image sensor;

[0006] The central processing module is responsible for processing, analyzing and making decisions on the digital signals input by the data acquisition module;

[0007] The remote communication module is used to realize data transmission and communication between the central processing module and the remote monitoring terminal and the cloud server;

[0008] The remote monitoring terminal is connected to the central processing module via the remote communication module, and displays the operating status, process parameters, and equipment failure information of the spray coating machine in real time;

[0009] The execution control module controls the execution mechanism of the spray coating machine according to the control instructions sent by the central processing module;

[0010] The equipment status monitoring module is used to monitor the operating status of each component of the spray coating machine in real time, determine whether the equipment is operating normally, and promptly detect equipment failures and abnormal conditions;

[0011] The fault diagnosis module performs detailed diagnosis and location of the fault after the equipment status monitoring module detects an abnormality;

[0012] The process parameter optimization module optimizes the coating process parameters according to the coating quality requirements and the equipment operating status, thereby improving the coating quality and production efficiency.

[0013] Preferably, the temperature sensor in the data acquisition module adopts a thermocouple sensor to measure the temperature of the key parts of the coating chamber and the spray gun. Its principle is based on the Seebeck effect. Two conductors of different materials form a closed loop. When the temperatures at the two contacts are different, a thermoelectric potential will be generated in the loop. The temperature change can be known by measuring the thermoelectric potential. The pressure sensor adopts a piezoresistive sensor, which is installed in the coating chamber and the gas supply pipeline to monitor the internal pressure. Its working principle is to use pressure on the silicon diaphragm to deform the diaphragm, thereby causing the resistance value diffused on the diaphragm to change. By measuring the resistance value, the temperature change can be known. The flow sensor uses an electromagnetic flowmeter to measure the flow of liquid or gas. Based on Faraday's law of electromagnetic induction, when a conductive liquid cuts magnetic lines of force in a magnetic field, an induced electromotive force is generated in the liquid. The magnitude of the induced electromotive force is proportional to the flow rate. The displacement sensor and speed sensor are used to monitor the position and movement speed of the spray gun. Linear displacement sensors and encoders are used to convert mechanical displacement and speed into electrical signals respectively. The image sensor is installed inside the coating chamber to capture the coating image of the workpiece surface. A charge-coupled device (CCD) is used to convert optical signals into electrical signals.

[0014] The above-mentioned sensors collect various operating data of the spray coating machine in real time, including temperature, pressure, flow, spray gun position, movement speed, and workpiece surface image, and transmit the collected analog signals to the signal conditioning circuit; the signal conditioning circuit amplifies, filters, and isolates the analog signals to improve the quality and stability of the signals, and then converts the analog signals into digital signals through the analog-to-digital converter ADC and inputs them into the central processing module.

[0015] Preferably, the central processing module adopts a high-performance microprocessor or industrial control computer. The central processing module first pre-processes the collected data, including data filtering, data calibration, data normalization, removing noise and interference, and improving the accuracy and reliability of the data; then, the pre-processed data is analyzed in real time, and the operating status of the spray coating machine is judged through the established mathematical model and algorithm, such as whether it is operating normally and whether there are hidden faults; in terms of process parameter control, the central processing module calculates appropriate control parameters such as the flow rate, pressure, moving speed, temperature, etc. of the spray gun according to the set coating process requirements and the real-time collected operating data, and sends the control instructions to the execution control module; at the same time, the central processing module is also responsible for communicating with the remote monitoring terminal and the cloud server, uploading the equipment operation data and status information to the remote monitoring terminal and the cloud server, and receiving the control instructions and process parameter adjustment commands sent by the remote monitoring terminal.

[0016] Preferably, the remote communication module supports multiple communication protocols, including Ethernet, Wi-Fi, 4G / 5G, Bluetooth, etc., and can select appropriate communication methods according to different network environments to ensure stable data transmission; when communicating with the remote monitoring terminal, the remote communication module packages the equipment operation data and status information processed by the central processing module and sends them to the remote monitoring terminal, and at the same time receives the control instructions and parameter adjustment commands sent by the remote monitoring terminal, and transmits them to the central processing module; when communicating with the cloud server, the remote communication module uploads the equipment operation data and historical data to the cloud server, and stores them in the cloud database for data analysis and mining; at the same time, the cloud server can send updated control algorithms and process parameter template information to the system to realize remote upgrade and optimization of the system.

[0017] Preferably, the remote monitoring terminal is an interface for the operator to interact with the system, and the remote monitoring terminal includes a computer, a tablet, and a mobile phone; the operator can set the coating process parameters on the remote monitoring terminal, such as coating materials, coating thickness, spraying speed, temperature, pressure, etc., and send control instructions, such as starting, stopping, pausing equipment operation, adjusting the position and angle of the spray gun, etc.; in addition, the remote monitoring terminal also provides data query and analysis functions, and the operator can query the historical operation data and coating quality data of the equipment, and analyze them in the form of charts and curves to better understand the operation status of the equipment and the changing trend of the coating quality.

[0018] Preferably, the executive mechanism in the execution control module includes a spray gun, a motor, a valve, a heater, and a cooler; for the control of the spray gun, the execution control module adjusts the flow valve and pressure valve of the spray gun to control the spraying amount and pressure of the spraying material, and at the same time controls the movement and angle adjustment of the motor-driven spray gun to achieve precise spraying position and spraying trajectory; for the control of the heater and cooler, the execution control module adjusts the heating power and cooling flow according to the set temperature parameters to keep the temperature of the coating chamber and related components within an appropriate range; the execution control module adopts a programmable logic controller PLC or a distributed control system DCS, which has high reliability and real-time performance, and can accurately execute the control instructions of the central processing module.

[0019] Preferably, the equipment status monitoring module evaluates the status of the equipment by analyzing the sensor data collected by the data acquisition module, combining the historical operation data and fault feature library of the equipment; determines whether the motor is overloaded, overheated or has a bearing failure by monitoring the current, voltage and temperature parameters of the motor; determines whether the valve is leaking or stuck by monitoring the switch status and pressure changes of the valve; when an abnormal equipment status is detected, the equipment status monitoring module immediately sends an alarm signal to the central processing module, and the central processing module takes corresponding measures according to the preset fault handling strategy, such as stopping the equipment operation and issuing an alarm to notify the operator.

[0020] Preferably, the fault diagnosis module includes a rule-based diagnostic algorithm, a neural network diagnostic algorithm, and a support vector machine diagnostic algorithm; the rule-based diagnostic algorithm matches and infers sensor data according to pre-set fault rules and logic to determine the type and cause of the fault; the neural network diagnostic algorithm learns the characteristic data of the equipment under normal operation and fault conditions by training the neural network model to achieve intelligent diagnosis of the fault; the support vector machine diagnostic algorithm uses statistical learning theory to find the optimal classification hyperplane in high-dimensional space to classify and identify the fault; in the fault diagnosis process, the fault diagnosis module first extracts features from the collected fault data to extract characteristic parameters that can reflect the nature of the fault, such as the frequency characteristics of the vibration signal, the harmonic characteristics of the current signal, etc.; then, the characteristic parameters are input into the diagnostic algorithm, and the specific location and cause of the fault are determined through calculation and reasoning of the algorithm, and a fault diagnosis report is generated; the fault diagnosis report includes the fault type, cause of the fault, time and location of the fault, and recommended maintenance measures, and is sent to the remote monitoring terminal so that the operator can perform repairs and processing in a timely manner.

[0021] Preferably, the process parameter optimization module adopts a particle swarm optimization algorithm. During the process parameter optimization, the optimization target is first defined, such as coating thickness uniformity, film hardness, deposition rate, etc., and an objective function is established; then, the optimized process parameter variables are determined, such as spray flow rate, spray pressure, spray gun movement speed, coating chamber temperature, vacuum degree, etc.;

[0022] In the particle swarm optimization algorithm, each particle represents a set of process parameter solutions, the particle's position indicates the value of the process parameter, and the particle's speed indicates the update direction and step size of the process parameter. Through continuous iteration, the particle searches in the solution space, adjusts its speed and position according to its own historical optimal position and the global optimal position of the swarm, and ultimately finds the optimal process parameter combination that minimizes or maximizes the objective function. During the optimization process, the process parameter optimization module also considers the equipment's constraints, such as the maximum flow rate and pressure of the spray gun, the temperature and vacuum range of the coating chamber, etc., to ensure that the optimized process parameters are within the equipment's operable range.

[0023] A control method for a remote control system of a spray coating machine, comprising the following steps:

[0024] Step 1, data acquisition and preprocessing: The data acquisition module collects the operating data of the spray coating machine in real time through various sensors, including temperature, pressure, flow, spray gun position, movement speed, and workpiece surface image; the collected analog signals are processed by the signal conditioning circuit and converted into digital signals and input into the central processing module; the central processing module preprocesses the digital signals, including data filtering, calibration and normalization, to remove noise and interference and improve data quality;

[0025] Step 2: Equipment status monitoring and fault diagnosis: The equipment status monitoring module monitors the operating status of each equipment component in real time based on preprocessed data. By comparing it with historical data and a fault signature database, it determines whether the equipment is operating normally. When an anomaly is detected, the fault diagnosis module uses the corresponding fault diagnosis algorithm to conduct a detailed diagnosis of the fault, determine the type, cause, and location of the fault, and generate a fault diagnosis report that is sent to the remote monitoring terminal.

[0026] Step 3, process parameter optimization and control: Based on the set coating quality requirements and equipment operating status, the process parameter optimization module uses the particle swarm optimization algorithm to optimize the process parameters and establish the objective function:

[0027] F(x)=w1×f1(x)+w2×f2(x)+…+w n ×f n (x)

[0028] Among them, F(x) is the objective function, x is the process parameter vector, f1(x),f2(x),…,f n(x) is the optimization objective function, such as the coating thickness uniformity function, deposition rate function, etc., w1, w2, ..., w n The weight coefficients of each objective function are set according to actual needs. The optimal combination of process parameters is found through algorithm iteration. The central processing module sends the optimized process parameters to the execution control module. The execution control module controls the actuators of the spray gun, motor, valve, heater, and cooler, adjusts the operating status of the spray coating machine, and realizes precise control of the process parameters.

[0029] Step 4, remote monitoring and interaction: The remote monitoring terminal is connected to the central processing module through the remote communication module to display the equipment operating status, process parameters, and fault information in real time; the operator can set process parameters and send control instructions on the remote monitoring terminal to achieve remote monitoring and operation of the spray coating machine; at the same time, the system uploads the equipment operation data and historical data to the cloud server for data analysis and mining, and realizes remote upgrade and optimization of the system.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] The remote control system provided by the present invention integrates multiple functional modules, which can realize comprehensive monitoring and control of the spray coating machine, and improve the reliability and stability of the equipment. Through the remote communication module, the operator can monitor the equipment status anytime and anywhere, adjust the process parameters in time, and improve production efficiency and coating quality. The fault diagnosis module can quickly and accurately diagnose equipment failures, reduce fault downtime, and reduce maintenance costs. The process parameter optimization module adopts advanced optimization algorithms, which can automatically adjust the process parameters according to the coating quality requirements and equipment status, and improve the consistency and stability of the coating. The remote control system of the present invention also supports communication with cloud servers, realizes remote storage and analysis of data, and provides strong support for intelligent management and optimization of equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a system principle diagram of the present invention;

[0033] Figure 2 It is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0034] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0035] See also Figure 1-2 , the present invention provides a remote control system for a spray coating machine, comprising a data acquisition module, a central processing module, a remote communication module, a remote monitoring terminal, an execution control module, an equipment status monitoring module, a fault diagnosis module and a process parameter optimization module;

[0036] The data acquisition module is used to obtain the operating status information of the spray coating machine; it integrates temperature sensors, pressure sensors, flow sensors, displacement sensors, speed sensors and image sensors;

[0037] The central processing module is responsible for processing, analyzing and making decisions on the digital signals input by the data acquisition module;

[0038] The remote communication module is used to realize data transmission and communication between the central processing module and the remote monitoring terminal and the cloud server;

[0039] The remote monitoring terminal is connected to the central processing module through the remote communication module to display the operating status, process parameters and equipment failure information of the spray coating machine in real time;

[0040] The execution control module controls the execution mechanism of the spray coating machine according to the control instructions sent by the central processing module;

[0041] The equipment status monitoring module is used to monitor the operating status of each component of the spray coating machine in real time, determine whether the equipment is operating normally, and promptly detect equipment failures and abnormal conditions;

[0042] The fault diagnosis module performs detailed diagnosis and location of the fault after the equipment status monitoring module detects an abnormality;

[0043] The process parameter optimization module optimizes the coating process parameters according to the coating quality requirements and equipment operating status to improve the coating quality and production efficiency.

[0044] The temperature sensor in the data acquisition module uses a thermocouple sensor to measure the temperature of key parts of the coating chamber and spray gun. Its principle is based on the Seebeck effect. Two conductors of different materials form a closed loop. When the temperatures at the two contacts are different, a thermoelectric potential will be generated in the loop. The temperature change can be known by measuring the thermoelectric potential. The pressure sensor uses a piezoresistive sensor, which is installed in the coating chamber and the gas supply pipeline to monitor the internal pressure. Its working principle is to use pressure to act on the silicon diaphragm to deform the diaphragm, thereby causing the resistance value diffused on the diaphragm to change. The change in resistance value is measured to obtain the temperature. Reflects the magnitude of pressure; the flow sensor uses an electromagnetic flowmeter to measure the flow of liquid or gas. Based on Faraday's law of electromagnetic induction, when a conductive liquid cuts magnetic lines of force in a magnetic field, an induced electromotive force is generated in the liquid. The magnitude of the induced electromotive force is proportional to the flow rate; the displacement sensor and speed sensor are used to monitor the position and movement speed of the spray gun. A linear displacement sensor and an encoder are used to convert mechanical displacement and speed into electrical signals respectively; the image sensor is installed inside the coating chamber to collect the coating image of the workpiece surface. A charge-coupled device (CCD) is used to convert the optical signal into an electrical signal.

[0045] The above-mentioned sensors collect various operating data of the spray coating machine in real time, including temperature, pressure, flow, spray gun position, movement speed, and workpiece surface image, and transmit the collected analog signals to the signal conditioning circuit; the signal conditioning circuit amplifies, filters, and isolates the analog signals to improve the quality and stability of the signals, and then converts the analog signals into digital signals through the analog-to-digital converter ADC and inputs them into the central processing module.

[0046] The central processing module adopts a high-performance microprocessor or industrial control computer. The central processing module first pre-processes the collected data, including data filtering, data calibration, data normalization, removes noise and interference, and improves the accuracy and reliability of the data; then, the pre-processed data is analyzed in real time, and the operating status of the spray coating machine is judged through the established mathematical model and algorithm, such as whether it is operating normally and whether there are hidden faults; in terms of process parameter control, the central processing module calculates the appropriate control parameters, such as the flow rate, pressure, movement speed, temperature, etc. of the spray gun according to the set coating process requirements and the real-time collected operating data, and sends the control instructions to the execution control module; at the same time, the central processing module is also responsible for communicating with the remote monitoring terminal and the cloud server, uploading the equipment operation data and status information to the remote monitoring terminal and the cloud server, and receiving the control instructions and process parameter adjustment commands sent by the remote monitoring terminal.

[0047] The remote communication module supports multiple communication protocols, including Ethernet, Wi-Fi, 4G / 5G, Bluetooth, etc., and can select appropriate communication methods according to different network environments to ensure stable data transmission; when communicating with the remote monitoring terminal, the remote communication module packages the equipment operation data and status information processed by the central processing module and sends them to the remote monitoring terminal, and at the same time receives the control instructions and parameter adjustment commands sent by the remote monitoring terminal, and transmits them to the central processing module; when communicating with the cloud server, the remote communication module uploads the equipment operation data and historical data to the cloud server and stores them in the cloud database for data analysis and mining; at the same time, the cloud server can send updated control algorithms and process parameter template information to the system to realize remote upgrade and optimization of the system.

[0048] The remote monitoring terminal is the interface for operators to interact with the system. The remote monitoring terminal includes computers, tablets, and mobile phones. Operators can set coating process parameters on the remote monitoring terminal, such as coating materials, coating thickness, spraying speed, temperature, pressure, etc., and send control instructions, such as starting, stopping, and pausing equipment operation, adjusting the position and angle of the spray gun, etc. In addition, the remote monitoring terminal also provides data query and analysis functions. Operators can query the equipment's historical operating data and coating quality data, and analyze them in the form of charts and curves to better understand the equipment's operating conditions and changing trends in coating quality.

[0049] The executive mechanisms in the execution control module include spray guns, motors, valves, heaters, and coolers. For the control of the spray gun, the execution control module adjusts the flow valve and pressure valve of the spray gun to control the spraying amount and pressure of the spraying material, and at the same time controls the movement and angle adjustment of the motor-driven spray gun to achieve precise spraying position and spraying trajectory. For the control of the heater and cooler, the execution control module adjusts the heating power and cooling flow according to the set temperature parameters to keep the temperature of the coating chamber and related components within an appropriate range. The execution control module adopts a programmable logic controller PLC or a distributed control system DCS, which has high reliability and real-time performance and can accurately execute the control instructions of the central processing module.

[0050] The equipment status monitoring module evaluates the equipment status by analyzing the sensor data collected by the data acquisition module, combining it with the equipment's historical operating data and fault feature library; by monitoring the motor's current, voltage, and temperature parameters, it determines whether the motor is overloaded, overheated, or has a bearing failure; by monitoring the valve's switch status and pressure changes, it determines whether the valve is leaking or stuck; when an abnormal equipment status is detected, the equipment status monitoring module immediately sends an alarm signal to the central processing module, which takes corresponding measures according to the preset fault handling strategy, such as stopping the equipment operation and issuing an alarm to notify the operator.

[0051] The fault diagnosis module includes rule-based diagnostic algorithms, neural network diagnostic algorithms, and support vector machine diagnostic algorithms. The rule-based diagnostic algorithm matches and infers sensor data based on pre-set fault rules and logic to determine the type and cause of the fault. The neural network diagnostic algorithm trains a neural network model to learn the characteristic data of the equipment under normal operation and fault conditions, realizing intelligent fault diagnosis. The support vector machine diagnostic algorithm uses statistical learning theory to find the optimal classification hyperplane in high-dimensional space to classify and identify faults. During the fault diagnosis process, the fault diagnosis module first extracts features from the collected fault data, extracting characteristic parameters that can reflect the nature of the fault, such as the frequency characteristics of the vibration signal and the harmonic characteristics of the current signal. The characteristic parameters are then input into the diagnostic algorithm. Through the algorithm's calculation and inference, the specific location and cause of the fault are determined, and a fault diagnosis report is generated. The fault diagnosis report includes the fault type, cause, time and location of the fault, and recommended maintenance measures, and is sent to the remote monitoring terminal so that operators can carry out repairs and treatment in a timely manner.

[0052] The process parameter optimization module uses a particle swarm optimization algorithm. During the process parameter optimization, the optimization objectives are first defined, such as coating thickness uniformity, film hardness, deposition rate, etc., and the objective function is established. Then, the optimized process parameter variables are determined, such as spray flow rate, spray pressure, spray gun movement speed, coating chamber temperature, vacuum degree, etc.

[0053] In the particle swarm optimization algorithm, each particle represents a set of process parameter solutions, the particle's position indicates the value of the process parameter, and the particle's speed indicates the update direction and step size of the process parameter. Through continuous iteration, the particle searches in the solution space, adjusts its speed and position according to its own historical optimal position and the global optimal position of the swarm, and ultimately finds the optimal process parameter combination that minimizes or maximizes the objective function. During the optimization process, the process parameter optimization module also considers the equipment's constraints, such as the maximum flow rate and pressure of the spray gun, the temperature and vacuum range of the coating chamber, etc., to ensure that the optimized process parameters are within the equipment's operable range.

[0054] A control method for a remote control system of a spray coating machine, comprising the following steps:

[0055] Step 1, data acquisition and preprocessing: The data acquisition module collects the operating data of the spray coating machine in real time through various sensors, including temperature, pressure, flow, spray gun position, movement speed, and workpiece surface image; the collected analog signals are processed by the signal conditioning circuit and converted into digital signals and input into the central processing module; the central processing module preprocesses the digital signals, including data filtering, calibration and normalization, to remove noise and interference and improve data quality;

[0056] Step 2: Equipment status monitoring and fault diagnosis: The equipment status monitoring module monitors the operating status of each equipment component in real time based on preprocessed data. By comparing it with historical data and a fault signature database, it determines whether the equipment is operating normally. When an anomaly is detected, the fault diagnosis module uses the corresponding fault diagnosis algorithm to conduct a detailed diagnosis of the fault, determine the type, cause, and location of the fault, and generate a fault diagnosis report that is sent to the remote monitoring terminal.

[0057] Step 3, process parameter optimization and control: Based on the set coating quality requirements and equipment operating status, the process parameter optimization module uses the particle swarm optimization algorithm to optimize the process parameters and establish the objective function:

[0058] F(x)=w1×f1(x)+w2×f2(x)+…+w n ×f n (x)

[0059] Among them, F(x) is the objective function, x is the process parameter vector, f1(x),f2(x),…,f n (x) is the optimization objective function, such as the coating thickness uniformity function, deposition rate function, etc., w1, w2, ..., w n The weight coefficients of each objective function are set according to actual needs. The optimal combination of process parameters is found through algorithm iteration. The central processing module sends the optimized process parameters to the execution control module. The execution control module controls the actuators of the spray gun, motor, valve, heater, and cooler, adjusts the operating status of the spray coating machine, and realizes precise control of the process parameters.

[0060] Step 4, remote monitoring and interaction: The remote monitoring terminal is connected to the central processing module through the remote communication module to display the equipment operating status, process parameters, and fault information in real time; the operator can set process parameters and send control instructions on the remote monitoring terminal to achieve remote monitoring and operation of the spray coating machine; at the same time, the system uploads the equipment operation data and historical data to the cloud server for data analysis and mining, and realizes remote upgrade and optimization of the system.

[0061] Example:

[0062] The data acquisition module, which includes temperature, pressure, and flow sensors installed at key locations within the spray coating machine, collects operational data in real time. After signal conditioning and analog-to-digital conversion, it is input into the central processing module. The central processing module processes and analyzes the data, transmitting it to the remote monitoring terminal and cloud server via the remote communication module, while also receiving control commands from the remote monitoring terminal.

[0063] When coating process parameter optimization is required, the operator sets the optimization target and constraints on the remote monitoring terminal. The process parameter optimization module uses the particle swarm optimization algorithm to optimize the process parameters. Assuming that the optimization target is the coating thickness uniformity and deposition rate, the objective function is:

[0064]

[0065] Where σ is the standard deviation of the coating thickness, reflecting thickness uniformity; smaller σ indicates better uniformity; v is the deposition rate, expressed in μm / min. In the particle swarm optimization algorithm, the particle position vector x = [q, p, s, T, V], representing spray flow rate, spray pressure, gun speed, coating chamber temperature, and vacuum level, respectively. Through iterative calculations, the process parameter combination that maximizes the objective function F(x) is found.

[0066] When the equipment status monitoring module detects an abnormally high motor temperature, it immediately sends an alarm signal to the central processing module, which then stops the equipment and notifies the fault diagnosis module to perform fault diagnosis. The fault diagnosis module analyzes motor current, voltage, temperature, and other data, and, using a neural network diagnostic model, determines that the motor may have a bearing failure. It then generates a fault diagnosis report and sends it to the operator, who then performs repairs based on the report.

[0067] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A remote control system for a spray coating machine, characterized in that: It includes data acquisition module, central processing module, remote communication module, remote monitoring terminal, execution control module, equipment status monitoring module, fault diagnosis module and process parameter optimization module; The data acquisition module is used to obtain the operating status information of the spray coating machine; it integrates a temperature sensor, a pressure sensor, a flow sensor, a displacement sensor, a speed sensor and an image sensor; The central processing module is responsible for processing, analyzing and making decisions on the digital signals input by the data acquisition module; The remote communication module is used to realize data transmission and communication between the central processing module and the remote monitoring terminal and the cloud server; The remote monitoring terminal is connected to the central processing module via the remote communication module, and displays the operating status, process parameters, and equipment failure information of the spray coating machine in real time; The execution control module controls the execution mechanism of the spray coating machine according to the control instructions sent by the central processing module; The equipment status monitoring module is used to monitor the operating status of each component of the spray coating machine in real time, determine whether the equipment is operating normally, and promptly detect equipment failures and abnormal conditions; The fault diagnosis module performs detailed diagnosis and location of the fault after the equipment status monitoring module detects an abnormality; The process parameter optimization module optimizes the coating process parameters according to the coating quality requirements and the equipment operating status, thereby improving the coating quality and production efficiency.

2. A remote control system for a spray coating machine according to claim 1, characterized in that: The temperature sensor in the data acquisition module adopts a thermocouple sensor to measure the temperature of key parts of the coating chamber and the spray gun; the pressure sensor adopts a piezoresistive sensor, which is installed on the coating chamber and the gas supply pipeline to monitor the internal pressure; the flow sensor adopts an electromagnetic flowmeter to measure the flow of liquid or gas; the displacement sensor and speed sensor are used to monitor the position and movement speed of the spray gun, and adopt a linear displacement sensor and an encoder; the image sensor is installed inside the coating chamber to capture the coating image of the workpiece surface; The above-mentioned sensors collect various operating data of the spray coating machine in real time, including temperature, pressure, flow, spray gun position, movement speed, and workpiece surface image, and transmit the collected analog signals to the signal conditioning circuit; the signal conditioning circuit amplifies, filters, and isolates the analog signals to improve the quality and stability of the signals, and then converts the analog signals into digital signals through the analog-to-digital converter ADC and inputs them into the central processing module.

3. A remote control system for a spray coating machine according to claim 1, characterized in that: The central processing module adopts a high-performance microprocessor or industrial control computer. The central processing module first pre-processes the collected data, including data filtering, data calibration, and data normalization; then, the pre-processed data is analyzed in real time, and the operating status of the spray coating machine is judged through the established mathematical model and algorithm; in terms of process parameter control, the central processing module calculates the appropriate control parameters according to the set coating process requirements and the real-time collected operating data, and sends the control instructions to the execution control module; at the same time, the central processing module is also responsible for communicating with the remote monitoring terminal and the cloud server, uploading the equipment operation data and status information to the remote monitoring terminal and the cloud server, and receiving the control instructions and process parameter adjustment commands sent by the remote monitoring terminal.

4. A remote control system for a spray coating machine according to claim 1, characterized in that: The remote communication module supports multiple communication protocols, including Ethernet, Wi-Fi, 4G / 5G, Bluetooth, etc., and can select appropriate communication methods according to different network environments to ensure stable data transmission; when communicating with the remote monitoring terminal, the remote communication module packages the equipment operation data and status information processed by the central processing module and sends them to the remote monitoring terminal, and at the same time receives the control instructions and parameter adjustment commands sent by the remote monitoring terminal, and transmits them to the central processing module; when communicating with the cloud server, the remote communication module uploads the equipment operation data and historical data to the cloud server, and stores them in the cloud database for data analysis and mining; at the same time, the cloud server can send updated control algorithms and process parameter template information to the system to realize remote upgrade and optimization of the system.

5. The remote control system for a spray coating machine according to claim 1, characterized in that: The remote monitoring terminal is the interface for operators to interact with the system. The remote monitoring terminal includes a computer, tablet, and mobile phone. The operator can set coating process parameters and send control instructions on the remote monitoring terminal. In addition, the remote monitoring terminal also provides data query and analysis functions. The operator can query the historical operating data and coating quality data of the equipment and analyze them in the form of charts and curves.

6. A remote control system for a spray coating machine according to claim 1, characterized in that: The executive mechanism in the execution control module includes a spray gun, a motor, a valve, a heater, and a cooler; for the control of the spray gun, the execution control module adjusts the flow valve and pressure valve of the spray gun to control the spraying amount and pressure of the spraying material, and at the same time controls the movement and angle adjustment of the motor-driven spray gun to achieve precise spraying position and spraying trajectory; for the control of the heater and cooler, the execution control module adjusts the heating power and cooling flow according to the set temperature parameters to keep the temperature of the coating chamber and related components within an appropriate range; the execution control module adopts a programmable logic controller PLC or a distributed control system DCS.

7. The remote control system for a spray coating machine according to claim 1, characterized in that: The equipment status monitoring module evaluates the equipment status by analyzing the sensor data collected by the data acquisition module, combining the equipment's historical operation data and fault feature library; by monitoring the motor's current, voltage, and temperature parameters, it determines whether the motor is overloaded, overheated, or has a bearing failure; by monitoring the valve's switch status and pressure changes, it determines whether the valve is leaking or stuck; when an abnormal equipment status is detected, the equipment status monitoring module immediately sends an alarm signal to the central processing module, and the central processing module takes corresponding measures according to the preset fault handling strategy.

8. The remote control system for a spray coating machine according to claim 1, characterized in that: The fault diagnosis module includes a rule-based diagnosis algorithm, a neural network diagnosis algorithm, and a support vector machine diagnosis algorithm; the rule-based diagnosis algorithm matches and infers sensor data according to pre-set fault rules and logic to determine the type and cause of the fault; the neural network diagnosis algorithm learns the characteristic data of the equipment under normal operation and fault conditions by training the neural network model to achieve intelligent diagnosis of faults; the support vector machine diagnosis algorithm uses statistical learning theory to find the optimal classification hyperplane in high-dimensional space to classify and identify faults; in the fault diagnosis process, the fault diagnosis module first extracts features from the collected fault data and extracts characteristic parameters that can reflect the nature of the fault; then, the characteristic parameters are input into the diagnosis algorithm, and through the calculation and reasoning of the algorithm, the specific location and cause of the fault are determined, and a fault diagnosis report is generated; the fault diagnosis report includes the fault type, cause of the fault, time and location of the fault, and recommended maintenance measures, and is sent to the remote monitoring terminal so that the operator can perform repairs and processing in a timely manner.

9. The remote control system for a spray coating machine according to claim 1, characterized in that: The process parameter optimization module adopts the particle swarm optimization algorithm. During the process of process parameter optimization, the optimization target is first defined and the objective function is established; then, the optimized process parameter variables are determined; In the particle swarm optimization algorithm, each particle represents a set of process parameter solutions, the particle's position indicates the value of the process parameter, and the particle's speed indicates the update direction and step size of the process parameter. Through continuous iteration, the particle searches in the solution space, adjusts its speed and position according to its own historical optimal position and the global optimal position of the swarm, and ultimately finds the optimal process parameter combination that minimizes or maximizes the objective function. During the optimization process, the process parameter optimization module also considers the equipment constraints to ensure that the optimized process parameters are within the equipment's operable range.

10. A control method for a remote control system of a spray coating machine according to any one of claims 1 to 9, characterized in that: The following steps are involved: Step 1, data acquisition and preprocessing: The data acquisition module collects the operating data of the spray coating machine in real time through various sensors, including temperature, pressure, flow, spray gun position, movement speed, and workpiece surface image; the collected analog signals are processed by the signal conditioning circuit and converted into digital signals and input into the central processing module; the central processing module preprocesses the digital signals, including data filtering, calibration and normalization, to remove noise and interference and improve data quality; Step 2: Equipment status monitoring and fault diagnosis: The equipment status monitoring module monitors the operating status of each equipment component in real time based on preprocessed data. By comparing it with historical data and a fault signature database, it determines whether the equipment is operating normally. When an anomaly is detected, the fault diagnosis module uses the corresponding fault diagnosis algorithm to conduct a detailed diagnosis of the fault, determine the type, cause, and location of the fault, and generate a fault diagnosis report that is sent to the remote monitoring terminal. Step 3, process parameter optimization and control: Based on the set coating quality requirements and equipment operating status, the process parameter optimization module uses the particle swarm optimization algorithm to optimize the process parameters and establish the objective function: F(x)=w1×f1(x)+w2×f2(x)+…+w n ×f n (x) Among them, F(x) is the objective function, x is the process parameter vector, f1(x),f2(x),…,f n (x) is the optimization objective function, w1,w2,…,w n The weight coefficients of each objective function are set according to actual needs. The optimal combination of process parameters is found through algorithm iteration. The central processing module sends the optimized process parameters to the execution control module. The execution control module controls the actuators of the spray gun, motor, valve, heater, and cooler, adjusts the operating status of the spray coating machine, and realizes precise control of the process parameters. Step 4, remote monitoring and interaction: The remote monitoring terminal is connected to the central processing module through the remote communication module to display the equipment operating status, process parameters, and fault information in real time; the operator can set process parameters and send control instructions on the remote monitoring terminal to achieve remote monitoring and operation of the spray coating machine; at the same time, the system uploads the equipment operation data and historical data to the cloud server for data analysis and mining, and realizes remote upgrade and optimization of the system.

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