A pickling machine multi-thread synchronization and accurate feedback remote interaction control method

Abstract

The application discloses a pickling machine multi-thread synchronization and accurate feedback remote interaction control method, and belongs to the technical field of industrial automation control. The application realizes remote safe, efficient and accurate control of pickling equipment by constructing a three-layer modular collaborative architecture of a perception layer, a control layer and an interaction layer, combining special interaction logic design, process optimization algorithm and accurate feedback mechanism. The interaction logic design for the special process scene of pickling equipment adopts scene-based modularization, operation process simplification and interface equivalent mapping to ensure consistent operation experience with the on-site touch screen. The process optimization algorithm improves operation response efficiency through instruction classification priority sorting, lightweight packaging, parallel processing and simplified feedback. The accurate feedback mechanism realizes 100ms periodic collection of equipment state and millisecond-level synchronization of interface based on multi-thread timing collection, three-level data verification and dynamic synchronization.

Description

Technical Field

[0001] This invention relates to the field of industrial automation control technology, specifically to a remote interactive control method and system for pickling equipment. Background Technology

[0002] Pickling equipment is widely used in industries such as metal processing, automobile manufacturing, and aerospace to remove oxides and impurities from workpiece surfaces. Traditional control methods rely on touchscreen terminals installed in the pickling chamber, requiring operators to be physically present to operate the equipment, set parameters, and perform debugging. However, the pickling chamber environment typically contains corrosive and harmful substances such as acid and alkali mists. Long-term exposure can easily lead to respiratory illnesses, skin damage, and other occupational health problems, seriously threatening operator safety. Furthermore, physical space limitations make remote collaborative management difficult, hindering production efficiency and intelligent upgrades.

[0003] Existing remote control solutions (such as VPN-based remote access) attempt to address the above problems, but they have significant drawbacks: 1. High communication latency: Traditional VPN solutions typically have a latency of ≥500ms, which is difficult to meet the real-time control requirements of pickling equipment (such as precise positioning of cranes and rapid valve opening and closing), resulting in delayed command execution and increased operational risks.

[0004] 2. Poor synchronization between interface and device status: Due to the high packet loss rate of data transmission, the remote interface cannot reflect the actual status of the device in real time, which can easily lead to erroneous operations, such as valves being opened or closed by mistake or temperature settings being deviated.

[0005] 3. Weak system adaptability: The general remote solution is not optimized for the dedicated control logic of pickling equipment, resulting in high operational complexity, high learning cost, and significant differences from the on-site touch screen experience.

[0006] 4. Inadequate feedback mechanism: Status feedback relies on a polling mechanism, which has high synchronization latency and cannot accurately verify the results of instruction execution, resulting in slow response in emergency handling. Summary of the Invention

[0007] The purpose of this invention is to provide a multi-threaded synchronous and precise feedback remote interactive control method for pickling machines, which solves the aforementioned problems. The technical solution is based on a three-layer modular architecture, combined with a dedicated algorithm design, to achieve an end-to-end remote control closed loop. The overall system data flow demonstrates the complete process from the issuance of commands from the interaction layer to the control layer, to the data acquisition and feedback from the perception layer.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a method for multi-threaded synchronization and precise feedback remote interactive control of a pickling machine, which realizes remote control through a three-layer modular architecture of a perception layer, a control layer and an interaction layer; The sensing layer is used to collect device status data and transmit control commands. The control layer is used to perform instruction parsing and feedback verification; The interaction layer is used to provide the user interface and run the interaction logic; The method also includes a multi-threaded timed synchronization mechanism to achieve millisecond-level synchronization between device status and interface display.

[0009] Preferably, the interaction layer adopts a dedicated interaction logic design for pickling machines, which includes dividing the operation into a crane control module, a valve control module, and a heating setting module according to the process scenario, and achieving an operation experience consistent with the on-site touch screen through interface equivalent mapping.

[0010] Preferably, it also includes a process optimization algorithm, the algorithm comprising: User commands are categorized, identified, and prioritized. Commands are lightweightly encapsulated to reduce data transmission volume. Multithreading technology is used to achieve parallel processing of command transmission and status acquisition, and core status information is prioritized for feedback after execution.

[0011] Preferably, the instruction classification and recognition includes distinguishing between driving control, valve control and temperature setting instructions, with emergency operation instructions having the highest priority; The lightweight packaging includes using binary format for Boolean instructions and compressed encoding for numeric instructions.

[0012] Preferably, the precise feedback mechanism includes: PLC parameters are collected periodically by multi-threading, and the device status is read at 100ms intervals. The interface is updated through data verification and dynamic synchronization, with a synchronization error of less than 30ms.

[0013] Preferably, the feedback mechanism adopts a dual refresh mode of triggering and timed refresh, wherein the TimerCallback_comRead() method reads parameters in batches in an asynchronous loop, and the Timer control updates interface elements at a period of 200ms.

[0014] A remote control system for a pickling machine, comprising: Perception layer, control layer, and interaction layer; The sensing layer includes an industrial-grade high-power DIN rail wireless router and an Omron NX1-1200 PLC, which communicate via TCP / IP protocol. The control layer includes a PLC collaborative logic module for state machine management, instruction parsing, and feedback verification. The interaction layer includes client software, which integrates an interaction logic core module, a process optimization algorithm module, and a multi-threaded synchronous feedback module.

[0015] Preferably, the client software is developed based on the C# language and includes a modular window management module, which is used to calculate the optimal display position of the window according to the screen size, so as to realize the flexible calling of the driving positioning interface and the heating setting interface.

[0016] Preferably, the system has a packet loss rate of less than 0.05%, a signal strength of not less than -70dBm, and establishes a connection with the PLC through an IP address and port number.

[0017] Compared with the prior art, the beneficial effects of the present invention are: This invention fundamentally improves safety performance. Through the "human-machine physical isolation" design, operators do not need to enter the pickling room, completely eliminating the risk of exposure to acid mist and alkali mist. Industrial-grade routers are optimized for deployment, resulting in stable signal strength of ≥-70dBm and a packet loss rate of <0.05%. The multi-threaded synchronization mechanism achieves a response time of <100ms and an interface synchronization error of <30ms, making the user experience completely equivalent to that of a live touchscreen.

[0018] The process algorithm reduces instruction processing time by 40%, and after eliminating redundant steps, the average time per operation is reduced from 500ms to <50ms. The modular interface design reduces the learning curve.

[0019] The precise feedback mechanism ensures data integrity through multi-level verification, 100% consistency of device status synchronization, and emergency response time of less than 20ms, far exceeding traditional solutions. Attached Figure Description

[0020] Figure 1 This is a diagram illustrating the data flow of the present invention.

[0021] Figure 2 This is a flowchart of the debugging process for the device of the present invention.

[0022] Figure 3 This is the homepage interface for the on-site touchscreen.

[0023] Figure 4 This is the homepage interface of the client software.

[0024] Figure 5 The on-site touchscreen vehicle positioning interface.

[0025] Figure 6 This is the vehicle location interface for the client software.

[0026] Figure 7 The interface for setting up heating on the on-site touchscreen.

[0027] Figure 8 The interface for heating settings in the client software.

[0028] Figure 9This is a field touchscreen valve control interface.

[0029] Figure 10 This is the valve control interface for the client software. Detailed Implementation

[0030] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0031] Please refer to Figures 1 to 3 The present invention provides a technical solution: a method for multi-threaded synchronous and precise feedback remote interactive control of a pickling machine, which realizes remote control through a three-layer modular architecture of perception layer, control layer and interaction layer; The sensing layer is used to collect device status data and transmit control commands. The control layer is used to perform instruction parsing and feedback verification; The interaction layer is used to provide the user interface and run the interaction logic; The method also includes a multi-threaded timed synchronization mechanism to achieve millisecond-level synchronization between device status and interface display.

[0032] The system adopts a three-layer modular architecture: perception layer, control layer, and interaction layer. An industrial-grade high-power DIN rail wireless router serves as the communication core, extending the antenna to the optimal signal location via a low-loss RF adapter cable. The router operates at a frequency of 5.2GHz to 5.8GHz with an output power of 20dBm. In the pickling room, the router is mounted on a DIN rail within the control cabinet, ensuring a signal strength ≥ -70dBm. An Omron NX1-1200 PLC, equipped with digital input modules, analog input modules, and digital output modules, connects to the router via an Ethernet interface. The PLC collaborative logic module in the control layer uses ladder diagram programming with a scan cycle of ≤5ms. The state machine management unit defines four device operating states: standby state (0), running state (1), emergency stop state (2), and fault state (3). The instruction parsing unit uses a lookup table method to map the opcode to the corresponding execution function. The opcode format is 1 byte, the target address is 2 bytes, the parameter is 4 bytes, and the checksum is 2 bytes. The interaction layer includes remote client software, integrating core interaction logic modules, process optimization algorithm modules, etc., and provides a user interface. It is developed using the Microsoft Visual Studio 2022 development environment, employing the C# language and the .NET Framework 4.8 framework. A multi-threaded timed synchronization mechanism initializes the PLC connection through the Start_COM() method. The status acquisition thread reads device parameters at 100ms intervals, and the interface update thread refreshes the displayed content at 200ms intervals. Thread synchronization uses a ReaderWriterLockSlim read-write lock mechanism to ensure data consistency.

[0033] The interaction layer adopts a dedicated interaction logic design for pickling machines, which includes dividing the operation into a crane control module, a valve control module, and a heating setting module according to the process scenario, and achieving an operation experience consistent with the on-site touch screen through interface equivalence mapping.

[0034] Vehicle control module: It supports three control modes: jog control, automatic control, and manual control. In jog control mode, users can precisely move the trolley using directional buttons, with 10 adjustable speed levels. In automatic control mode, the system automatically schedules the trolley according to a preset process route, supporting path planning for up to 50 slots. Manual control mode is used for equipment debugging, providing real-time position feedback and torque monitoring. The one-click slot positioning function is implemented through a pre-stored coordinate mapping table; after the user selects the target slot, the system automatically calculates the optimal movement path.

[0035] Valve control module: It supports three operation modes: single valve control, batch valve control, and sequence control. Single valve control provides an independent operation interface for each valve, displaying the valve's open / closed status in real time. Batch valve control supports simultaneous operation of up to 32 valves, employing a group management strategy that allows valves to be grouped by tank area. Sequence control automatically executes valve operations according to a preset process sequence, supporting conditional judgments and loop logic.

[0036] Heating setting module: Temperature setting supports both absolute temperature setting and relative temperature adjustment, with a setting range of 0℃ to 100℃ and an accuracy of 0.1℃. PID parameter tuning offers both automatic and manual modes. Automatic tuning uses the Ziegler-Nichols method, while manual tuning supports independent setting of three parameters: Kp, Ki, and Kd. The temperature curve management function can save 100 historical temperature curves, supporting curve comparison analysis and trend prediction.

[0037] Interface equivalent mapping: The interface layout adopts the same control arrangement as the on-site touchscreen, with a key control position error of less than 5 pixels. Operation logic is implemented through an event mapping mechanism, ensuring a one-to-one correspondence between remote operation events and on-site operation events. Status display synchronization employs two-way data binding technology to ensure real-time synchronization between displayed content and device status.

[0038] It also includes process optimization algorithms, which include: User commands are categorized, identified, and prioritized. Commands are lightweightly encapsulated to reduce data transmission volume. Multithreading technology is used to achieve parallel processing of command transmission and status acquisition, and core status information is prioritized for feedback after execution.

[0039] Instruction preprocessing stage: A machine learning-based instruction classification algorithm was employed, with feature extraction dimensions including 10 dimensions such as instruction length, operation object type, and number of parameters. The classifier used a support vector machine algorithm, with 5000 training samples and a classification accuracy of 99.5%. Priority calculation adopted a weighted scoring method, considering three factors: instruction type weight, urgency weight, and impact scope weight.

[0040] Lightweight instruction encapsulation: The protocol header compression uses field merging and bit-field techniques to compress the original 32-byte protocol header to 16 bytes. Data compression uses the LZ4 algorithm. Batch transmission uses packet aggregation technology to merge multiple small data packets into one large data packet for transmission, reducing protocol overhead.

[0041] The thread pool size is dynamically adjusted based on the number of CPU cores in the system, with the maximum number of threads set to twice the number of CPU cores. Task scheduling uses a work-stealing algorithm; each thread maintains a local task queue, and steals tasks from other threads' queues when its local queue is empty. Resource management uses reference counting to ensure timely resource release.

[0042] Results feedback: Incremental updates employ a version number mechanism, with each data item carrying a version number; only data items whose version numbers have changed are transmitted. Predictive feedback uses an ARIMA model built upon historical data to predict state changes at the next five time points. The cache design employs an LRU eviction policy, with the cache size dynamically adjusted and a maximum cache capacity of 1GB.

[0043] The instruction classification and recognition includes distinguishing between vehicle control, valve control, and temperature setting instructions, with emergency operation instructions having the highest priority. The lightweight packaging includes using binary format for Boolean instructions and compressed encoding for numeric instructions.

[0044] Instruction signature library: The feature dimensions include 12 dimensions such as instruction length, operation object type, number of parameters, and operation type. Feature extraction adopts an automated process, calculating the feature vector of each instruction in real time.

[0045] Priority management strategy: Emergency stop commands are automatically assigned the highest priority and processed directly without entering a queue. Device start / stop commands have a priority level of 7, and parameter setting commands have a priority level of 5. The priority queue is implemented using a heap structure to ensure that high-priority commands are always dequeued first.

[0046] The precise feedback mechanism includes: PLC parameters are collected periodically by multi-threading, and the device status is read at 100ms intervals. The interface is updated through data verification and dynamic synchronization, with a synchronization error of less than 30ms.

[0047] Multi-threaded timed data collection solution: The data acquisition thread uses a timer-triggered method with a timing accuracy of ±1ms. The active acquisition cycle is 100ms, and the acquired data includes device status, operating parameters, fault information, and other data items. Passive notification uses an interrupt-driven method, immediately reporting important status changes. Data acquisition coverage is 100%, ensuring no data omissions.

[0048] Dynamic synchronization mechanism: The publish-subscribe pattern supports multiple subscribers, allowing a single data update to notify multiple subscribers. State synchronization employs a vector clock algorithm to address data consistency issues in distributed systems. Conflict detection is based on a timestamp mechanism; when a data conflict is detected, the latest timestamp is used.

[0049] The feedback mechanism adopts a dual refresh mode of triggering and timed refresh. The TimerCallback_comRead() method reads parameters in batches in an asynchronous loop, and the Timer control updates the interface elements at a period of 200ms.

[0050] Triggered refresh: Significant state changes trigger an immediate UI update with a response time of less than 10ms. Change detection employs a comparison algorithm, comparing new data with cached data field by field, and triggering a refresh immediately upon detecting a change. Event notifications utilize the observer pattern, supporting one-to-many notifications.

[0051] Detailed parameters for timed refresh: The refresh cycle is 200ms, and a high-precision system timer with an error of <1ms is used. The refresh content includes all display data to ensure display integrity. The refresh strategy alternates between incremental and full updates to balance performance and visual appeal.

[0052] Triggered refresh ensures timeliness, guaranteeing that important status changes are displayed immediately. Scheduled refresh ensures completeness, guaranteeing that all data is updated periodically. The coordination mechanism is implemented through priority scheduling, with triggered refresh taking precedence over scheduled refresh.

[0053] A remote control system for a pickling machine, comprising: Perception layer, control layer, and interaction layer; The sensing layer includes an industrial-grade high-power DIN rail wireless router and an Omron NX1-1200 PLC, which communicate via TCP / IP protocol. The control layer includes a PLC collaborative logic module for state machine management, instruction parsing, and feedback verification. The interaction layer includes client software, which integrates an interaction logic core module, a process optimization algorithm module, and a multi-threaded synchronous feedback module.

[0054] Sensing layer device selection and configuration: The industrial-grade router selected is the Siemens SCALANCE W788-1, which supports the IEEE 802.11ac standard and has a maximum transmission rate of 300Mbps. The RF adapter cable is the LMR-400 type, with an attenuation of 0.22dB / m (@2.4GHz). The PLC selected is the Omron NX1-1200 type, with 16 digital input points and 4 analog input channels.

[0055] Control layer logic design: The state machine management unit adopts a finite state machine model, containing 5 states and 10 state transition conditions. The instruction parsing unit supports 50 operation instructions with a parsing time of <1ms. The feedback verification unit uses CRC16 verification with a verification time of <0.5ms.

[0056] Interaction layer software architecture: The system employs the MVVM design pattern, with the Model layer responsible for data storage and retrieval, the View layer for user interface display, and the ViewModel layer for business logic. This modular design divides the system into 10 functional modules, supporting independent development and testing.

[0057] The client software is developed based on the C# language and includes a modular window management module, which is used to calculate the optimal display position of the window according to the screen size, so as to realize the flexible calling of the driving positioning interface and the heating setting interface.

[0058] The development environment consists of Visual Studio 2022 version 17.0, .NET Framework 4.8, and C# language version 9.0. Third-party libraries referenced include MVVM Light Toolkit, Unity container, and NLog logging component.

[0059] WPF Interface Development: The interface layout is defined using XAML, supporting data binding and style templates. Resolution adaptation is achieved using the ViewBox control, supporting resolutions ranging from 1024×768 to 3840×2160. Animation effects are implemented using Storyboard.

[0060] The system has a packet loss rate of less than 0.05%, a signal strength of not less than -70dBm, and establishes a connection with the PLC through an IP address and port number.

[0061] Example 1: Implementation of Vehicle Positioning Control A crane positioning control system was implemented in the pickling workshop. The hardware configuration included a Siemens SCALANCE W788-1 router, an Omron NX1-1200 PLC, and an absolute encoder. The software was developed in C#, and the positioning algorithm used PID control, with parameters obtained through automatic tuning. Actual testing showed that the positioning accuracy reached ±0.1mm, and the response time was <100ms.

[0062] Example 2: Implementation of Valve Control System The valve control system employs pneumatic actuators, equipped with position sensors and torque limiters. The control software enables valve sequence management, supporting batch operations and conditional judgments. In actual production, the valve operation success rate reaches 99.9%, with a response time of <50ms.

[0063] Example 3: Implementation of a temperature control system The temperature control system uses a PT100 sensor, a heater power of 18kW, and a control cycle of 1s. PID parameters are tuned using the Ziegler-Nichols method, achieving an actual control accuracy of ±0.5℃. The system supports temperature profile programming and can store 100 process profiles.

[0064] Based on the above, the safety performance of this invention is fundamentally improved. Through a "human-machine physical isolation" design, operators do not need to enter the pickling room, completely eliminating the risk of exposure to acid and alkali mists. Optimized deployment of industrial-grade routers ensures a stable signal strength of ≥-70dBm and a communication packet loss rate of <0.05%. A multi-threaded synchronization mechanism achieves a response time of <100ms and an interface synchronization error of <30ms, providing an operating experience completely equivalent to a live touchscreen. The process algorithm reduces instruction processing time by 40%, and after eliminating redundant steps, the average time for a single operation is reduced from 500ms to <50ms. The modular interface design reduces the learning curve. A precise feedback mechanism ensures data integrity through multi-level verification, 100% consistency in device status synchronization, and an emergency response time of <20ms, far exceeding traditional solutions.

[0065] As is known from common technical knowledge, this invention can be implemented through other embodiments that do not depart from its spirit or essential characteristics. Therefore, the disclosed embodiments described above are merely illustrative and not exhaustive. All modifications within the scope of this invention or its equivalents are included in this invention.

Claims

1. A method for multi-threaded synchronous and precise feedback remote interactive control of a pickling machine, characterized in that: Remote control is achieved through a three-layer modular architecture consisting of a perception layer, a control layer, and an interaction layer. The sensing layer is used to collect device status data and transmit control commands. The control layer is used to perform instruction parsing and feedback verification; The interaction layer is used to provide the user interface and run the interaction logic; The method also includes a multi-threaded timed synchronization mechanism to achieve millisecond-level synchronization between device status and interface display.

2. The method for multi-threaded synchronous and precise feedback remote interactive control of a pickling machine according to claim 1, characterized in that: The interaction layer adopts a dedicated interaction logic design for pickling machines, which includes dividing the operation into a crane control module, a valve control module, and a heating setting module according to the process scenario, and achieving an operation experience consistent with the on-site touch screen through interface equivalence mapping.

3. The method for multi-threaded synchronous and precise feedback remote interactive control of a pickling machine according to claim 1, characterized in that: It also includes process optimization algorithms, which include: User commands are categorized, identified, and prioritized. Commands are lightweightly encapsulated to reduce data transmission volume. Multithreading technology is used to achieve parallel processing of command transmission and status acquisition, and core status information is prioritized for feedback after execution.

4. The method for multi-threaded synchronous and precise feedback remote interactive control of a pickling machine according to claim 3, characterized in that: The instruction classification and recognition includes distinguishing between vehicle control, valve control, and temperature setting instructions, with emergency operation instructions having the highest priority. The lightweight packaging includes using binary format for Boolean instructions and compressed encoding for numeric instructions.

5. The method for multi-threaded synchronous and precise feedback remote interactive control of a pickling machine according to claim 1, characterized in that: The precise feedback mechanism includes: PLC parameters are collected periodically by multi-threading, and the device status is read at 100ms intervals. The interface is updated through data verification and dynamic synchronization, with a synchronization error of less than 30ms.

6. The method for multi-threaded synchronous and precise feedback remote interactive control of a pickling machine according to claim 5, characterized in that: The feedback mechanism adopts a dual refresh mode of triggering and timed refresh. The TimerCallback_comRead() method reads parameters in batches in an asynchronous loop, and the Timer control updates the interface elements at a period of 200ms.

7. A remote control system for a pickling machine, used to implement the method according to any one of claims 1-6, characterized in that: include: Perception layer, control layer, and interaction layer; The sensing layer includes an industrial-grade high-power DIN rail wireless router and an Omron NX1-1200 PLC, which communicate via TCP / IP protocol. The control layer includes a PLC collaborative logic module for state machine management, instruction parsing, and feedback verification. The interaction layer includes client software, which integrates an interaction logic core module, a process optimization algorithm module, and a multi-threaded synchronous feedback module.

8. The remote control system for a pickling machine according to claim 7, characterized in that: The client software is developed based on the C# language and includes a modular window management module, which is used to calculate the optimal display position of the window according to the screen size, so as to realize the flexible calling of the driving positioning interface and the heating setting interface.

9. The remote control system for a pickling machine according to claim 7, characterized in that: The system has a packet loss rate of less than 0.05%, a signal strength of not less than -70dBm, and establishes a connection with the PLC through an IP address and port number.

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