Automatic protocol adaptation method for real-time access system of multi-source equipment

Abstract

The invention relates to an automatic protocol adaptation method for a real-time access system of multi-source equipment. The data acquisition layer receives original protocol data sent by equipment and transmits the original protocol data to the protocol adaptation layer. And the protocol metadata analysis module extracts, analyzes, compares and matches the data, and automatically identifies the protocol type of the equipment. The rule engine converts original protocol data into a system unified internal data format according to a conversion rule and then transmits the original protocol data to the data processing layer, and after cleaning, integration, analysis and other operations are carried out, the original protocol data are transmitted to the application interface layer to be called by an upper-layer application system. And when new protocol equipment is accessed, the hot plug function allows the system to dynamically load the new protocol adapter module in a state of not stopping running. According to the method, automatic adaptation of a new protocol is achieved through rapid deployment of the containerized micro-service architecture in combination with newly added protocol rules and metadata of the protocol management module, the whole process does not need to compile and publish the system again, and efficient and stable operation of the multi-source equipment real-time access system is guaranteed.

Description

Technical Field

[0001] The invention relates to a protocol automatic adaptation method for a multi-source equipment real-time access system, belonging to the technical field of industrial equipment control. Background Art

[0002] In the era of the deep integration of Industry 4.0, smart manufacturing, and the Internet of Things, real-time multi-source equipment access systems have become core infrastructure for the digital transformation of various industries. Within the industrial sector, within factories like automotive manufacturing and electronics assembly, CNC machine tools, industrial robots, and smart sensors of different brands utilize protocols such as Modbus, Profinet, and OPC UA, requiring real-time data exchange and collaborative control between devices. In the energy sector, smart grid construction involves distributed power sources, smart meters, and other devices, adhering to protocols such as IEC 61850 and DNP3. Efficient adaptation is required to ensure stable power system operation. In scenarios like smart homes and smart transportation, a large number of terminal devices, such as smart door locks and traffic lights, utilize MQTT and CoAP protocols, necessitating solutions for protocol adaptation to build a complete smart ecosystem. These application scenarios place higher demands on the protocol adaptability of multi-source equipment access systems, making technological innovation imperative.

[0003] Currently, protocol adaptation technologies for multi-source equipment access systems at home and abroad generally use pre-set protocol conversion plug-ins or modules, which can only support limited adaptation of common protocols. Once a new protocol or protocol version is updated, developers need to rewrite the access code, debug the program, compile the system, and re-release it. This process is not only time-consuming and labor-intensive, but also prone to introducing new errors, significantly increasing enterprise development costs and project cycles. In addition, existing technologies have significant performance bottlenecks when dealing with high-concurrency, large-scale data access from multi-source equipment, making it difficult to meet the stringent real-time and stability requirements of scenarios such as industrial automation and the Internet of Things, and unable to achieve dynamic and efficient adaptation of protocols.

[0004] Some domestic companies and research institutions have explored protocol adaptation technologies, and some domestic industrial internet platforms have achieved basic support for common industrial protocols by developing specific protocol conversion plug-ins. However, these technologies are often limited to specific application scenarios and struggle to automatically adapt to complex and changing protocol requirements. When new industrial equipment or IoT terminals utilize entirely new protocols for access, significant secondary development efforts are still required. Furthermore, in high-concurrency, multi-protocol scenarios, the system's stability and scalability are insufficient, making it unable to meet the demands of rapid intelligent upgrades for domestic industry.

[0005] Developed countries like Europe and the United States developed early in the field of protocol adaptation technology. Some internationally renowned companies have launched industrial gateways and IoT platforms equipped with extensive protocol libraries and advanced adaptive algorithms. These products hold a significant share of the global market, but are subject to high prices and difficulty in customization, making them prohibitively expensive for domestic small and medium-sized enterprises. Furthermore, given the complex and diverse industrial environments and specialized device protocols in China, the comprehensiveness and stability of their automatic adaptation remain insufficient, making it difficult to achieve deep integration with domestic application scenarios and unable to fully meet the actual needs of my country's industrial development. Summary of the Invention

[0006] The purpose of the present invention is to address the problems faced by multi-source equipment access systems in the context of rapid development of Industry 4.0 and the Internet of Things, such as complex and diverse protocols and difficult adaptation. A protocol automatic adaptation method for real-time access systems of multi-source equipment is proposed. This method uses an innovative automatic adaptation mechanism and a layered architecture to achieve protocol adaptation without rewriting access code, compiling, and publishing, thereby promoting the interconnection and interoperability of multi-source equipment and providing technical support for industrial intelligence, Internet of Things applications, etc.

[0007] To achieve this object, the present invention adopts the following technical solutions: The present invention is a protocol automatic adaptation method for a multi-source equipment real-time access system, which is characterized by comprising the following steps: Step 1, Equipment Access Phase: In a real-world industrial automation production workshop, there are numerous different types of industrial equipment, such as CNC machine tools (following Fanuc's custom protocol) and smart sensors (following the Modbus protocol). When these devices are connected to the system, the various data collectors deployed in the data acquisition layer quickly start up and, according to pre-defined collection rules, collect the raw protocol data sent by these devices, such as CNC machine tools and smart sensors, and transmit this data to the protocol adaptation layer via a high-speed data transmission link. Step 2, protocol identification phase: The protocol metadata analysis module of the protocol adaptation layer begins to work. For the Fanuc custom protocol data received from the CNC machine tool, it extracts metadata features such as the machine tool control instruction format and coordinate data format, and carefully compares them with the Fanuc protocol metadata stored in the protocol management module, thereby accurately identifying that the device uses the Fanuc custom protocol. For the Modbus protocol data of the smart sensor, it extracts metadata such as function codes and register addresses, and also matches them with the Modbus protocol metadata in the protocol management module to complete protocol identification. Step 3, protocol conversion phase: After identifying the protocol type, the rule engine converts the original protocol data of the CNC machine tool according to the conversion rules for the Fanuc custom protocol to the system's internal data format in the protocol management module. For example, the machine tool motion instructions in the Fanuc protocol are converted into a standard motion control instruction format that the system can understand; for the Modbus protocol data of the smart sensor, the temperature, pressure and other data in the register are converted into a unified data structure within the system according to the conversion rules. In this process, the configurable access component flexibly adapts the data conversion process according to the pre-set parameters for the Fanuc protocol and the Modbus protocol, without the need to write any new code; Step 4, data processing and output stage: The converted internal data is transmitted to the data processing layer, which cleans the data, removes noise data, and then integrates and analyzes it according to the needs of the production management system, such as statistically analyzing the temperature data change trend collected by the smart sensor over a period of time. The processed data is passed to the upper-level production management system through the application interface layer. The production management system uses this data to achieve real-time monitoring and precise control of the production process, such as adjusting production process parameters based on the operating data of CNC machine tools. Step 5, new protocol access phase: Assume that a new type of intelligent logistics equipment has been introduced into the workshop, which adopts a new private communication protocol. After the system detects the access of the new equipment, the hot-swap function takes effect immediately. Without affecting the normal operation of other parts of the system, the adaptation module for the new intelligent logistics equipment protocol is dynamically loaded from the pre-prepared new protocol adaptation module library. This module is quickly deployed through the containerized microservice architecture, and then combined with the newly added rules and metadata about the new protocol in the protocol management module, it quickly realizes automatic adaptation to the new protocol, so that the new intelligent logistics equipment can be smoothly connected to the system and work with other equipment. The entire process does not require recompilation and release of the system. Furthermore, the data described in step 1 is the original protocol data sent by multi-source equipment, which is diverse and heterogeneous. From the format point of view, different equipment follows their own protocol standards. For example, the data of smart sensors that follow the Modbus protocol are composed of specific function codes, register addresses and data values. The data format is regular and has a check bit; while the CNC machine tool data that follows the Fanuc custom protocol includes machine tool control instruction format, coordinate data format, etc., which may be presented in a specific binary code or custom character format. In terms of content, the data covers equipment operating parameters, status information, etc., such as temperature and pressure data collected by sensors, and machine tool position, speed and other instruction data. These raw data are received by the data acquisition layer through multiple communication links. The data flow is from the equipment to the data acquisition layer, and the data is in an unprocessed original state, retaining all the characteristics of the equipment's own protocol; Furthermore, the data described in step 2 is protocol metadata extracted from the original protocol data, and its core characteristics are identification and specificity. Protocol metadata contains key identification information of the protocol type, such as the function code and Modbus address of the Modbus protocol, the instruction format identifier of the Fanuc protocol, etc. These metadata are like the "fingerprint" of the protocol, which is used to match the data in the protocol management module. The data format is relatively concise, focusing on the protocol characteristic parameters, and the data flows from the original data to the protocol metadata analysis module. By analyzing and processing the metadata, the protocol type of the equipment can be quickly determined, providing a basis for subsequent conversion. At this time, the core role of the data is to identify and determine the protocol type; Furthermore, the data extracted in step 3 is the internal unified data format after the original protocol data is converted, which is standardized and universal. The original protocol data is converted into a unified format that can be processed by the system based on the conversion rules of the protocol management module. For example, the device parameter data of different protocols are unified into JSON format data containing device ID, parameter name, parameter value, and timestamp. The data content is reorganized and mapped to remove redundant parts of the original protocol that are not related to system processing, and at the same time, the metadata required by the system is supplemented. The configurable access component regulates the conversion process according to preset parameters to ensure the accuracy and flexibility of data conversion. The data flows from the protocol adaptation layer to the data processing layer. The converted data eliminates the heterogeneity of the original protocol and lays the foundation for internal processing of the system; Furthermore, the data described in step 4 is the converted internal data, showing the characteristics of processability and purpose. The data is cleaned to remove noise and erroneous data; the integration summarizes the scattered similar data; the analysis mines the information behind the data, such as trend analysis, anomaly detection, etc. The processed data format may be further optimized to meet the needs of upper-level applications, such as converting statistical analysis results into chart data format. The data flows from the data processing layer to the application interface layer, and the final output data has a clear application orientation, such as providing equipment operation status monitoring data for the production management system, providing data analysis reports for the decision-making system, etc. The value of the data is fully mined and reflected; Furthermore, the data described in step 5 includes the original protocol data of the new device and the newly added protocol rules and metadata in the protocol management module. The original protocol data is unknown and unique, and is new protocol format data that has not yet been processed by the system. The newly added protocol rules and metadata are supplementary information for adapting to the new protocol, which is targeted and timely. The data flow is from the original data of the new device to the new protocol adaptation module. The new protocol adaptation module processes the original data in combination with the newly added rules and metadata to achieve automatic protocol adaptation. In this process, the interaction and processing of data ensure that the new protocol device can be quickly integrated into the system, and the data characteristics reflect the system's dynamic adaptability to the new protocol.

[0008] Compared with the prior art, the present invention has the following significant advantages: (1) The present invention achieves fully automatic protocol adaptation, significantly reducing labor costs. In the case of new protocols or protocol version updates, existing technologies require developers to rewrite access code, debug, compile, and release the system, which is time-consuming, labor-intensive, and error-prone. The present invention, however, constructs an automatic adaptation mechanism driven by a rule engine and metadata. The protocol metadata analysis module automatically identifies the device protocol type, and the rule engine completes protocol conversion based on preset rules. Configurable access components are flexibly adapted, eliminating the need for manual code writing throughout the process. This reduces enterprise development costs by approximately 60%-80%, significantly improving development efficiency.

[0009] (2) The present invention supports dynamic expansion during system operation to ensure business continuity. Traditional technologies often require system shutdown and redeployment when adding new protocol equipment, which affects business continuity. The present invention adopts hot-swap functionality and a containerized microservice architecture. New protocol adapter modules can be dynamically loaded during system operation. Combined with the new rules and metadata added by the protocol management module, new protocols can be automatically adapted without recompiling and releasing the system. This ensures the stable operation of the multi-source equipment real-time access system and avoids business interruptions caused by protocol changes.

[0010] (3) The present invention has strong compatibility and scalability, and is adaptable to complex scenarios. Existing technologies are mostly limited to specific application scenarios or common protocols, and are difficult to cope with complex and changing protocol requirements. The present invention adopts a layered architecture design, covering the data acquisition layer, protocol adaptation layer, data processing layer, and application interface layer, and each layer works together; at the same time, the protocol management module supports the dynamic update of protocol rules and metadata, enabling the system to adapt to complex protocol environments in multiple fields such as industry, energy, and the Internet of Things, and easily cope with the access of new protocol equipment, with good compatibility and scalability.

[0011] (4) The present invention has efficient and stable performance, meeting high concurrency requirements. Existing technologies have performance bottlenecks when processing multi-source equipment access with high concurrency and large data volumes, and cannot meet real-time and stability requirements. The present invention improves system processing capabilities by optimizing data processing processes and adopting parallel processing technologies. It can efficiently process real-time data from multi-source equipment and ensure accurate data transmission and rapid processing in high-concurrency scenarios, meeting the stringent system performance requirements of scenarios such as industrial automation and the Internet of Things. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 This is a flow chart of the automatic protocol adaptation method for a multi-source equipment real-time access system according to the present invention; Figure 2 This is an activity diagram of the automatic protocol adaptation method for a multi-source equipment real-time access system according to the present invention. DETAILED DESCRIPTION

[0013] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0014] Example 1, reference Figure 1 -2. A protocol automatic adaptation method and tool for real-time access of multi-source equipment to a system, comprising the following steps: Step 1: Equipment access and data collection. The detailed processing steps are as follows: (1) Device connection detection: The system continuously monitors the status of access ports, whether they are wired ports such as Ethernet interfaces and serial ports, or wireless signal bands such as Wi-Fi, Bluetooth, and ZigBee. Once a signal change caused by a new device connection is detected, the access process is immediately triggered. For example, when a new industrial sensor is connected to the serial port via the Modbus RTU protocol, the serial port monitoring program quickly captures the signal; (2) Initial information acquisition: For newly connected devices detected, the device identification program of the data acquisition layer attempts to read the basic information of the device, such as device type, manufacturer ID, device serial number, etc. For devices that follow standard protocols, the basic information can be directly obtained through the instructions specified by the protocol. For example, network devices that support the SNMP protocol can obtain basic device information by sending specific query instructions. For some custom protocol devices, it may be necessary to obtain the information through specific handshake signals or initialization communication processes according to the access instructions provided by the device manufacturer. (3) Data collection configuration: Based on the acquired device information, the system automatically matches the preset data collection rules. If it is a known device type, directly call the existing collection template and set the collection frequency, data transmission format and other parameters. For example, for common smart temperature sensors, set the temperature data to be collected every 5 seconds and encapsulated and transmitted in JSON format; if it is a new or unidentified device, the system enters the manual assisted configuration mode. The operator can manually set the collection-related parameters according to the device manual through the management interface. After the configuration is completed, the system will store the device information and collection rules for subsequent rapid identification and collection; (4) Real-time data acquisition. After completing the above configuration, the data acquisition device begins to collect device data in real time according to the set acquisition frequency and rules. For analog data, such as temperature and pressure values ​​collected by sensors, the analog signal is converted into a digital signal through the analog-to-digital conversion module, and calibration and filtering are performed. For digital data, such as the switch status of the device and alarm signals, it is directly read and data verification is performed. The collected data is transmitted to the protocol adaptation layer in real time via the internal data bus or high-speed communication link to ensure the timeliness and accuracy of the data.

[0015] Step 2: Protocol identification and analysis. The detailed processing steps are as follows: (1) Data preprocessing: After receiving the raw data, the protocol adaptation layer first performs data preprocessing. This includes removing noise generated during data transmission, such as checking and correcting data bit errors through parity check and CRC check; performing frame synchronization processing on the data, splitting the continuous data stream according to the frame format specified by the protocol, and extracting complete data frames to provide an accurate data basis for subsequent metadata analysis; (2) Metadata extraction: The protocol metadata analysis module extracts protocol metadata from each pre-processed data frame using specific algorithms and rules. For common protocols, such as the Modbus protocol, metadata such as function codes (used to indicate read, write, diagnostic, and other operation types), register addresses (specify data storage locations), and data lengths are extracted. For complex custom protocols, key information that can identify protocol types and characteristics, such as specific protocol identification strings and data format markers, is extracted by analyzing the data frame header and tail feature fields and data structures. (3) Protocol library matching, comparing the extracted metadata with a large number of known protocol metadata templates stored in the protocol management module. The matching process uses efficient search algorithms, such as hash table search, binary search tree matching, etc., to quickly locate possible matching protocol types. If a completely matching protocol template is found, the protocol type of the device is directly determined; if there is a partial match or fuzzy match, the detailed features of the metadata, such as the value range of the data field, the order of data arrangement, etc., are further analyzed, and combined with the context information of the protocol, secondary matching and screening are performed until the protocol type is accurately identified. If no match is found in the local protocol library, the system automatically triggers the protocol update process and attempts to download the latest protocol template from the cloud protocol library, or enters the manual assisted identification mode, and professionals determine the protocol type based on the metadata features and enter the new protocol information into the system.

[0016] Step 3: Protocol conversion and adaptation. The detailed processing steps are as follows: (1) Rule retrieval: After determining the device protocol type, the rule engine immediately retrieves the conversion rules corresponding to the protocol from the protocol management module. These rules are stored in a predefined format, including protocol data format mapping, data conversion algorithms, data verification rules, etc. For example, when converting the register data of the Modbus protocol to the unified data format within the system, the rules define how to map the Modbus address to the device parameter ID of the system, and how to convert the Modbus data type (such as 16-bit integer, 32-bit floating point number) to the data type used by the system; (2) Data conversion: convert the original protocol data frame by frame according to the conversion rules. For data format conversion, data is reorganized and mapped according to the rules, such as converting the complex data structure represented by multiple register combinations in the Modbus protocol into a simple and unified structure format within the system; for data value conversion, calculation and adjustment are performed based on the conversion algorithm, such as converting the data value represented by a specific scaling factor in certain protocols into the standard physical value specified by the system. During the conversion process, the configurable access component dynamically adjusts its own parameters, such as data parsing depth, data cache size, etc., according to the protocol characteristics and conversion requirements to ensure the efficiency and accuracy of the conversion process; (3) Post-conversion verification: After completing the data conversion, the system verifies the integrity and accuracy of the converted data. By calculating the checksum and comparing key data fields, it verifies whether the converted data is consistent with the original data in terms of semantics and numerical values. If the verification fails, the system records the error information and attempts to re-convert, or triggers the corresponding error handling mechanism based on the error type, such as sending an alert to the administrator to indicate that there may be a problem with the protocol conversion. At the same time, the original data and the converted data are backed up for subsequent analysis.

[0017] Step 4: Data processing and application. The detailed processing steps are as follows: (1) Data cleaning: After the data processing layer receives the converted internal data, it first performs data cleaning operations. Using data cleaning algorithms, it identifies and removes noise points, outliers, and duplicate data in the data. For example, for temperature sensor data, if there are data points that are beyond the reasonable range (such as the temperature value exceeds the working limit of the equipment), they will be judged as outliers and removed; for a small amount of duplicate data generated by network transmission jitter, it will be cleaned up through a data deduplication algorithm to ensure that subsequent data analysis is based on accurate and clean data; (2) Data integration: Integrate cleaned data based on the business attributes and application requirements of the data. Associate and aggregate data from different devices and different types but related to form a meaningful data set. For example, in industrial production scenarios, the operating data of each device on the production line (such as equipment status, output, energy consumption, etc.) are integrated together to conduct a comprehensive analysis of the operating status of the entire production line; in smart home scenarios, the data of smart door locks, smart cameras, smart appliances and other devices are integrated to provide users with comprehensive information services such as home safety and comfort; (3) Data analysis: Use a variety of data analysis techniques to conduct in-depth mining of the integrated data. Statistical analysis methods are used to calculate statistical quantities such as the mean, variance, maximum, and minimum values ​​of the data to understand the overall distribution and trend of the data. Machine learning algorithms, such as anomaly detection algorithms and prediction algorithms, are used to monitor and predict the operating status of the equipment and detect potential failure risks in advance. For example, by analyzing the historical operating data of the equipment, an equipment failure prediction model is established. When the model predicts that the equipment may fail, an early warning message is issued in a timely manner to remind maintenance personnel to perform preventive maintenance. (4) Data output and application: The processed and analyzed data is output to the upper-level application system through the application interface layer. According to the needs of the application system, the data is converted into a suitable format, such as JSON, XML, etc., and transmitted through communication protocols such as HTTP and MQTT. After receiving the data, the upper-level application system (such as industrial production management system, smart home control app, etc.) uses it to implement functions such as equipment monitoring, intelligent control, and decision support. For example, the industrial production management system adjusts production plans and process parameters in real time based on the data analysis results to improve production efficiency and product quality; the smart home control app uses the data analysis results to automatically control home appliances according to the scenario rules set by the user, improving the convenience and comfort of the user's life.

[0018] Step 5: New protocol integration and dynamic expansion. The detailed processing steps are as follows: (1) New protocol detection: During the device access or protocol identification process, if the system determines that the access device uses an unidentified new protocol, the new protocol access process will be immediately triggered. The characteristics and existence of the new protocol can be further confirmed by continuously monitoring and analyzing the initial communication data of the device; (2) Cloud update request: The system automatically sends a request for new protocol information to the cloud server, including basic device information (such as device type, manufacturer, etc.), initially extracted protocol metadata features, etc. After receiving the request, the cloud server searches and matches in its huge protocol database and update library to find out whether there is an adaptation solution or update information for the new protocol; (3) Local module loading: The cloud server has a corresponding adaptation solution, which is transmitted to the local system in the form of a new protocol adaptation module through a secure network channel. The local system uses the hot-swap function to dynamically load the new protocol adaptation module without stopping the system. During the loading process, the system performs integrity verification and security checks on the module to ensure that the module can operate normally and does not pose a security risk to the system; (4) Protocol management update: After the new protocol adapter module is loaded, the system will update the protocol management module synchronously. The metadata information, conversion rules, adapter module related information of the new protocol will be stored in the protocol management module so that the subsequent access and processing of the protocol device can be carried out quickly and accurately. At the same time, the system will initialize and configure the new protocol adapter module so that it can work with the existing system architecture and other modules; (5) Testing and Optimization. After completing the above steps, the system conducts preliminary testing on the newly connected protocol device, sending a small amount of test data to verify the accuracy of protocol conversion and data processing. If any problems are found, the system automatically records the error information and makes corresponding optimization adjustments based on the error type, such as reconfiguring the adapter module parameters and updating the conversion rules, to ensure that the new protocol device can be stably and efficiently connected to the system and work normally.

Claims

1. A protocol automatic adaptation method for a multi-source equipment real-time access system, characterized in that: The following steps are involved: Step 1, Equipment Access Phase: In industrial automation production workshops, there are a large number of different types of industrial equipment. When connected to the system, various data collectors deployed in the data acquisition layer are quickly activated. According to pre-set collection rules, they collect the raw protocol data sent by CNC machine tools, smart sensors, or other devices in the workshop scene and transmit the data to the protocol adaptation layer via a high-speed data transmission link. Step 2, protocol identification phase: The protocol metadata analysis module of the protocol adaptation layer begins to work. For the Fanuc custom protocol data received from the CNC machine tool, it extracts the control instruction format and coordinate data format metadata features, and carefully compares them with the Fanuc protocol metadata stored in the protocol management module, thereby accurately identifying that the device uses the Fanuc custom protocol. For the Modbus protocol data of the smart sensor, the function code and register address metadata are extracted and matched with the Modbus protocol metadata in the protocol management module to complete the protocol identification. Step 3, protocol conversion phase: After identifying the protocol type, the rule engine converts the CNC machine tool's raw protocol data according to the conversion rules in the protocol management module for the Fanuc custom protocol to the system's internal data format. The machine tool motion instructions in the Fanuc protocol are converted into a standard motion control instruction format that the system can understand. For the Modbus protocol data of the smart sensor, the temperature and pressure data in the register are converted into a unified data structure within the system according to the conversion rules. During this process, the configurable access component flexibly adapts the data conversion process based on pre-set parameters for the Fanuc and Modbus protocols, without the need to write any new code. Step 4, data processing and output stage: The converted internal data is transmitted to the data processing layer, which cleans the data, removes noise data, and then integrates and analyzes it according to the needs of the production management system. The processed data is passed to the upper-level production management system through the application interface layer. The production management system uses this data to achieve real-time monitoring and precise control of the production process; Step 5, new protocol access phase: When a new type of intelligent logistics equipment is introduced into the workshop, it adopts a new private communication protocol; after the system detects the access of the new equipment, the hot-swap function takes effect immediately. Without affecting the normal operation of other parts of the system, the adaptation module for the new intelligent logistics equipment protocol is dynamically loaded from the pre-prepared new protocol adaptation module library; this module is quickly deployed through the containerized microservice architecture, and then combined with the newly added rules and metadata about the new protocol in the protocol management module, it quickly realizes automatic adaptation to the new protocol, allowing the new intelligent logistics equipment to be smoothly connected to the system and work in collaboration with other equipment. The entire process does not require recompilation and release of the system.

2. The method for automatic protocol adaptation for a multi-source equipment real-time access system according to claim 1, characterized in that: The data in step 1 is the original protocol data sent by multi-source equipment, which is diverse and heterogeneous. In terms of format, different equipment follows their own protocol standards. The smart sensor data that follows the Modbus protocol consists of specific function codes, register addresses and data values. The data format is regular and has a check bit. The CNC machine tool data that follows the Fanuc custom protocol includes the machine tool control instruction format and coordinate data format, which may be presented in a specific binary code or custom character format. In terms of content, the data covers equipment operating parameters and status information, including temperature and pressure data collected by sensors, and machine tool position and speed command data. These original data are received by the data acquisition layer through multiple communication links. The data flow is from the equipment to the data acquisition layer, and the data is in an unprocessed original state, retaining all the characteristics of the equipment's own protocol.

3. The method for automatic protocol adaptation for a multi-source equipment real-time access system according to claim 1, characterized in that: The data in step 2 is protocol metadata extracted from the original protocol data, whose core characteristics are identification and specificity; the protocol metadata contains key identification information of the protocol type, including the function code and Modbus address of the Modbus protocol, and the instruction format identifier of the Fanuc protocol; Focusing on the protocol characteristic parameters, the data flows from the original data to the protocol metadata analysis module; through the analysis and processing of the metadata, the protocol type of the equipment can be quickly determined to provide a basis for subsequent conversion. At this time, the core role of the data is to identify and determine the protocol type.

4. The method for automatic protocol adaptation for a multi-source equipment real-time access system according to claim 1, characterized in that: The data in step 3 is the internal unified data format after the original protocol data is converted, which is standardized and universal; the original protocol data is converted into a unified format that can be processed by the system according to the conversion rules of the protocol management module, including unifying the device parameter data of different protocols into JSON format data containing device ID, parameter name, parameter value, and timestamp; Data content is reorganized and mapped, eliminating redundant portions of the original protocol irrelevant to system processing while supplementing the metadata required by the system. Configurable access components regulate the conversion process according to preset parameters, ensuring accuracy and flexibility in data conversion. Data flows from the protocol adaptation layer to the data processing layer. The converted data eliminates the heterogeneity of the original protocol, laying the foundation for internal system processing.

5. The method for automatic protocol adaptation for a multi-source equipment real-time access system according to claim 1, characterized in that: The data in step 4 is the converted internal data, showing the characteristics of processability and purpose. The data is cleaned to remove noise and erroneous data; the scattered similar data are integrated and summarized; Analysis mines the information behind the data, such as trend analysis and anomaly detection; The processed data format may be further optimized to meet the needs of upper-level applications, such as converting statistical analysis results into chart data format; The data flows from the data processing layer to the application interface layer, and the final output data has a clear application orientation, such as providing equipment operation status monitoring data for the production management system and providing data analysis reports for the decision-making system. The value of the data is fully mined and reflected.

6. The method and tool for automatic protocol adaptation of a multi-source equipment real-time access system according to claim 1, characterized in that: The data in step 5 includes the original protocol data of the new device and the newly added protocol rules and metadata in the protocol management module; the original protocol data is unknown and unique, and is new protocol format data that has not been processed by the system; the newly added protocol rules and metadata are supplementary information for adapting to the new protocol, which is targeted and timely; the data flow is from the original data of the new device to the new protocol adaptation module, and the new protocol adaptation module processes the original data in combination with the newly added rules and metadata to achieve automatic protocol adaptation; in this process, the interaction and processing of data ensure that the new protocol device can be quickly integrated into the system, and the data characteristics reflect the system's dynamic adaptability to the new protocol.

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