A method and system for automatic identification and data acquisition of sensors in coal mines

Abstract

This invention relates to the field of Industrial Internet of Things (IIoT) technology, and in particular to a method and system for automatic identification and data acquisition of coal mine sensors. The method for automatic identification and data acquisition of coal mine sensors of this invention automatically discovers sensor devices in the network through a broadcast query protocol and a physical layer identification mechanism, parses their self-describing metadata, and generates device identification results and register read instruction sets. Through conflict detection and dynamic addressing algorithms, it automatically assigns and configures conflict-free Modbus slave addresses for the sensors. Based on the register read instruction set, it acquires data from the sensors and automatically verifies the acquired data based on the range and timing information in the self-describing metadata and the built-in multi-level verification mechanism to generate valid data. This constructs a multi-layered, intelligent data quality assurance system, significantly improving data reliability and greatly enhancing deployment and maintenance efficiency.

Description

Technical Field

[0001] This invention relates to the field of industrial Internet of Things (IoT) technology, and in particular to a method and system for automatic sensor identification and data acquisition in coal mines. Background Technology

[0002] As a new type of infrastructure that deeply integrates next-generation information and communication technologies with the industrial economy, the Industrial Internet of Things (IIoT) comprehensively connects people, machines, things, and systems, constructing a new manufacturing and service ecosystem covering the entire industrial and value chains. It is a key path to promote the digital, networked, and intelligent transformation of industry. In the high-risk industrial sector of coal mining, efficient and accurate identification and data collection of production equipment and its sensors are the cornerstone for building the perception layer and achieving safe production and intelligent management. IIoT technology plays an irreplaceable role in this regard.

[0003] Due to its openness, simplicity, and broad device support, the Modbus protocol has become one of the de facto standard protocols for communication between sensors and controllers in industrial settings, particularly in the coal mining industry. However, its static configuration characteristics fundamentally contradict the dynamic and complex industrial environment of coal mining sites. Traditional Modbus-based data acquisition solutions suffer from the following significant drawbacks: deployment and configuration are highly dependent on manual processes, resulting in low efficiency and low fault tolerance; they lack automatic identification and plug-and-play capabilities; maintenance costs are high; data quality assurance mechanisms are weak; reliability is insufficient; and system expansion and integration flexibility is poor.

[0004] Therefore, there is an urgent need for an innovative method and device that can achieve automatic identification, intelligent addressing, and highly reliable data acquisition of Modbus sensor devices in order to solve the above problems. Summary of the Invention

[0005] Therefore, the technical problem to be solved by the present invention is to overcome the problems of low efficiency and low fault tolerance in the prior art.

[0006] To address the aforementioned technical problems, this invention provides a method for automatic identification and data acquisition of sensors in coal mines, comprising: Based on the device self-description metadata pre-installed in the sensors, the sensor devices in the network are automatically discovered through a broadcast query protocol and physical layer identification mechanism, and their self-description metadata is parsed to generate device identification results and register read instruction sets. Based on the unique device identifier in the device's self-description metadata and the address pool maintained by the central controller, the sensor is automatically assigned and configured with conflict-free Modbus slave addresses through conflict detection and dynamic addressing algorithms. Based on the register read instruction set, data is acquired from the sensor, and the acquired data is automatically verified based on the range, timing information and built-in multi-level verification mechanism in the self-describing metadata to generate valid data.

[0007] Preferably, the automatic discovery of sensor devices in the network based on pre-installed device self-description metadata in the sensor, through a broadcast query protocol and physical layer identification mechanism, and the parsing of their self-description metadata to generate device identification results and register read instruction sets includes: When the Modbus bus is idle, the central controller sends a broadcast signal containing a query frame; after receiving a query frame that matches its own unique device identifier, the sensor responds with a self-description frame containing the device type, serial number and protocol version. The register mapping table in the self-describing frame is parsed, and the corresponding Modbus read instruction set is dynamically generated according to the function codes supported by the sensor. Verify the rationality of the data types, units, and ranges in the register mapping table.

[0008] Preferably, the automatic allocation and configuration of conflict-free Modbus slave addresses for sensors based on the unique device identifier in the device's self-description metadata and the address pool maintained by the central controller, through conflict detection and dynamic addressing algorithms, includes: A hash algorithm is used to map the sensor's unique device identifier to an initial address suggestion value; An address probe frame is sent to the initial address suggestion value. If a conflict response is received, a secondary hash calculation is initiated to generate a new address suggestion value until a conflict-free address is obtained. The conflict-free address is sent to the sensor via a configuration frame. After receiving and confirming the address, the sensor writes it into its own non-volatile memory.

[0009] Preferably, the multi-level verification mechanism includes: Cyclic redundancy check is performed on data transmission at the Modbus protocol frame level; Based on the range information in the self-describing metadata, a hard range check is performed on the collected sensor values, and data that exceeds the range is marked as invalid and an alarm is triggered. By comparing the timestamps of data frames with the expected acquisition sequence of the system, the continuity of data acquisition is verified, and data with deviations exceeding the threshold are judged as timing anomalies. Based on the statistical characteristics of continuously collected data calculated using a sliding window, an alarm for abnormal data fluctuation is triggered when the standard deviation or rate of change of the data exceeds a preset threshold.

[0010] Preferably, it further includes: at the edge nodes, performing local preprocessing on the self-verified valid data, including data cleaning, aggregation, and preliminary anomaly detection.

[0011] This invention also provides an automatic identification and data acquisition system for coal mine sensors, comprising: The central controller integrates a Modbus master module and an intelligent algorithm engine to perform automatic device identification and metadata acquisition steps, dynamic addressing and address configuration steps, and coordinate the data acquisition process. The edge node is equipped with a protocol conversion unit and a local verification unit, which are used to connect to the central controller and perform verification functions and edge preprocessing. The intelligent sensor has a built-in non-volatile memory for storing self-describing metadata, a dynamic configuration module, and a communication module that supports responding to broadcast queries.

[0012] Preferably, the self-describing metadata includes: a unique device identifier, supported Modbus protocol versions, a list of readable registers, data type and range information of each register, and a verification algorithm identifier.

[0013] Preferably, the central controller maintains a dynamically allocable Modbus slave address pool and runs a dynamic addressing module based on an improved conflict avoidance algorithm.

[0014] Preferably, the dynamic configuration module in the smart sensor is used to receive address configuration frames from the central controller; Update the Modbus slave address contained in the configuration frame to the local working register; The updated Modbus slave address is persistently stored in the non-volatile memory to ensure that the address remains unchanged after the device restarts.

[0015] Preferably, the local verification unit of the edge node is used to generate an anomaly alarm record and store it locally when an anomaly is detected; The pre-processed and verified valid data and abnormal records are uploaded to the central controller.

[0016] The technical solution of the present invention has the following advantages compared with the prior art: This invention discloses an automatic sensor identification and data acquisition method and system for coal mines. Through an innovative device self-description mechanism and broadcast automatic identification protocol, the system can automatically complete device discovery and identification within seconds after compliant sensors are connected to the network, without manual intervention. Combined with a dynamic addressing algorithm, the system can automatically allocate conflict-free slave addresses, completely avoiding configuration failures caused by address conflicts in traditional methods. A multi-layered, intelligent data quality assurance system is constructed, significantly improving data reliability. The system's reliance on professional human resources is reduced, saving on total lifecycle costs. The system's dynamic addressing and conflict resolution capabilities support hot-swapping of devices, ensuring that changes in network topology or device replacement do not affect the continuity of overall data acquisition. Local verification and preprocessing functions at edge nodes reduce reliance on the central controller and network transmission load, improving the system's resilience to localized failures, enhancing its adaptability and reliability, and ensuring production continuity. Attached Figure Description

[0017] To make the content of this invention easier to understand, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings, wherein: Figure 1 This is a flowchart of an automatic identification and data acquisition method for coal mine sensors provided by the present invention; Figure 2 This is a structural diagram of an automatic identification and data acquisition system for coal mine sensors provided by the present invention. Detailed Implementation

[0018] The core of this invention is to provide a method and system for automatic identification and data acquisition of coal mine sensors. Through the design of protocol extension, dynamic addressing and multi-level verification, the sensor equipment can be used plug and play, which enhances the system's adaptability and reliability and ensures production continuity.

[0019] To enable those skilled in the art to better understand the present invention, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Please refer to Figure 1. Figure 1 The logical relationship diagram of the automatic identification and data acquisition method for coal mine sensors provided by the present invention is shown below; the specific operation steps are as follows: Step S101: Based on the device self-description metadata pre-installed in the sensor, the sensor devices in the network are automatically discovered through the broadcast query protocol and physical layer identification mechanism, and their self-description metadata is parsed to generate device identification results and register read instruction set; Step S102: Based on the unique device identifier in the device self-description metadata and the address pool maintained by the central controller, a conflict-free Modbus slave address is automatically allocated and configured for the sensor through a conflict detection and dynamic addressing algorithm. Step S103: Based on the register read instruction set, data is collected from the sensor, and the collected data is automatically verified based on the range, timing information and built-in multi-level verification mechanism in the self-describing metadata to generate valid data. Based on the above embodiments, this embodiment will provide a detailed description of step S101: In one embodiment, the central controller sends a broadcast signal containing a query frame when the Modbus bus is idle; after receiving a query frame that matches its own unique device identifier, the sensor responds with a self-description frame containing the device type, serial number and protocol version. The register mapping table in the self-describing frame is parsed, and the corresponding Modbus read instruction set is dynamically generated according to the function codes supported by the sensor. Verify the rationality of the data types, units, and ranges in the register mapping table.

[0021] Specifically, the automatic identification mechanism comprises three progressive levels: Physical layer identification: An improved Carrier Sense Multiple Access (CSMA) algorithm is employed, with the central controller sending a UID query frame when the 485 bus is idle. Upon receiving a query frame matching its own UID, the sensor immediately responds with a self-description frame containing the device type, serial number, and protocol version. This mechanism achieves device discovery in 0.5 seconds, an 80% speedup compared to traditional scanning methods.

[0022] Protocol layer parsing: The central controller parses the register mapping table in the self-description frame and automatically generates a set of read instructions that conform to the device characteristics. For example, for sensors that support function code 03, it dynamically generates commands to read holding registers; for devices that support function code 04, it automatically configures the input register read path.

[0023] Semantic layer verification: An ontology-based semantic verification module is introduced to verify the rationality of register data type, unit, and range. For example, if the temperature sensor data exceeds 150℃ or falls below -50℃, the system automatically triggers an abnormal alarm and records a timestamp.

[0024] Based on the above embodiments, this embodiment will provide a detailed description of step S102: In one embodiment, a hash algorithm is used to map the sensor’s unique device identifier to an initial address suggestion value; An address probe frame is sent to the initial address suggestion value. If a conflict response is received, a secondary hash calculation is initiated to generate a new address suggestion value until a conflict-free address is obtained. The conflict-free address is sent to the sensor via a configuration frame. After receiving and confirming the address, the sensor writes it into its own non-volatile memory.

[0025] Specifically, the dynamic addressing algorithm is based on an improved conflict avoidance algorithm to achieve automatic slave address allocation and conflict resolution. The algorithm flow is as follows: Initial address pool: The central controller maintains an allocatable address pool (1-247), using a hash algorithm to map UIDs to initial address suggestions.

[0026] Collision detection: Bus responses are detected by sending address probe frames. If a collision response is received, a secondary hash calculation is initiated to generate a new address suggestion value. The calculation formula is as follows:

[0027] in: For input data (arbitrary degree), For hash functions, The output hash value (fixed degree, such as 128 or 56 bits); Address allocation: The central controller sends a configuration frame containing the new address to the device, and the device updates the slave address stored locally after confirmation.

[0028] Persistent storage: After an address change, the device writes the new address to non-volatile memory to ensure that the address is retained after a restart.

[0029] This algorithm achieves address allocation time of less than 2 seconds and a conflict rate of less than 0.1%. It is 20 times more efficient than traditional manual configuration and reduces the address error rate to zero.

[0030] The dynamic formula is as follows:

[0031] in, For dynamic addressing results, For sensor displacement identification, To dynamically allocate address pool factors, iterative updates are performed. The algorithm can detect the optimal address allocation strategy for sensors.

[0032] Based on the above embodiments, this embodiment will provide a detailed description of step S103: In one embodiment, the multi-level verification mechanism includes: Cyclic redundancy check is performed on data transmission at the Modbus protocol frame level; Based on the range information in the self-describing metadata, a hard range check is performed on the collected sensor values, and data that exceeds the range is marked as invalid and an alarm is triggered. By comparing the timestamps of data frames with the expected acquisition sequence of the system, the continuity of data acquisition is verified, and data with deviations exceeding the threshold are judged as timing anomalies. Based on the statistical characteristics of continuously collected data calculated using a sliding window, an alarm for abnormal data fluctuation is triggered when the standard deviation or rate of change of the data exceeds a preset threshold.

[0033] At the edge nodes, the valid data that has undergone self-verification is preprocessed locally, including data cleaning, aggregation, and preliminary anomaly detection.

[0034] Specifically, the data self-verification includes a three-tiered verification system: CRC-16 checksum: At the Modbus frame level, the standard CRC-16 algorithm is used to verify the integrity of data transmission. The receiver recalculates the CRC and compares it with the frame end checksum to ensure that the transmission error rate is less than 10^-6.

[0035] Range verification: Based on the range information in the device's self-describing metadata, a hard range check is performed on the collected data. For example, if the methane sensor data exceeds 100% LEL, the system automatically marks it as invalid data and triggers an alarm.

[0036] Timing verification: The continuity of data acquisition timing is verified through a timestamp comparison algorithm. The system maintains a sliding window to record the times of the last 10 acquisitions. If the current data timestamp deviates from the expected time by more than ±5ms, it is determined to be a timing anomaly.

[0037] Statistical verification: A sliding window-based statistical verification module is introduced to calculate statistical quantities such as the mean, standard deviation, and rate of change of the data. For example, for a temperature sensor, if the standard deviation of three consecutive data points exceeds 2°C, an alarm for abnormal data fluctuation is triggered.

[0038] This embodiment provides an automatic sensor identification and data acquisition method for coal mines. Through an innovative device self-description mechanism and a broadcast automatic identification protocol, the system can automatically complete device discovery and identification within seconds after compliant sensors are connected to the network, without manual intervention. Combined with a dynamic addressing algorithm, the system can automatically allocate conflict-free slave addresses, completely avoiding configuration failures caused by address conflicts in traditional methods. A multi-layered, intelligent data quality assurance system is constructed, significantly improving data reliability. The system's reliance on professional human resources is reduced, saving on total lifecycle costs. The system's dynamic addressing and conflict resolution capabilities support hot-swapping of devices; changes in network topology or device replacement do not affect the continuity of overall data acquisition. Local verification and preprocessing functions at edge nodes reduce reliance on the central controller and network transmission load, improve the system's resilience to local failures, enhance its adaptability and reliability, and ensure production continuity.

[0039] like Figure 2 As shown, Figure 2 The logical relationship diagram of the automatic identification and data acquisition system for coal mine sensors provided by the present invention is as follows: The central controller integrates a Modbus master module and an intelligent algorithm engine to perform automatic device identification and metadata acquisition steps, dynamic addressing and address configuration steps, and coordinate the data acquisition process. The central controller maintains a dynamically allocable Modbus slave address pool and runs a dynamic addressing module based on an improved conflict avoidance algorithm.

[0040] Specifically, the central controller is the brain of the system, typically deployed in a ground-based control center or data center. It integrates software and hardware modules, including: Modbus Master Module: As the logical master station of the entire system, it is responsible for scheduling all communication tasks and issuing unified acquisition commands to edge nodes.

[0041] Intelligent Algorithm Engine: This is the core software for achieving automation, containing multiple functional sub-modules: Device discovery and identification engine: Periodically or upon receiving a new device access signal, the engine sends broadcast UID query frames to the bus via edge nodes. The engine parses the sensor responses (self-describing frames), automatically completes device registration, and dynamically generates the optimal data acquisition command sequence for the device based on the register mapping table.

[0042] Dynamic Addressing Management Module: This module maintains a global, dynamically allocated Modbus slave address pool. When a new device is discovered, the module invokes an improved collision avoidance algorithm: First, a suggested address is calculated using a hash function based on the device's UID. Then, an address probe frame is sent to verify if the address is already occupied. If a collision occurs, a second hash calculation is performed until a free address is found. Finally, an address configuration frame is sent to the device via an edge node to complete the automatic address allocation and fixation.

[0043] Semantic Verification and Alarm Center: Receives verification results and raw data from edge nodes. It centrally manages and pushes alarms for anomalies reported by edge nodes (such as over-range errors and timing errors). Simultaneously, it can perform more complex semantic verification and data analysis requiring global information.

[0044] The edge node is equipped with a protocol conversion unit and a local verification unit, which are used to connect to the central controller and perform verification functions and edge preprocessing. Specifically, edge nodes are deployed in areas close to sensor clusters (such as underground substations and tunnel junctions) to serve as hubs for local data processing and protocol adaptation. Each edge node contains: Protocol Conversion Unit: Responsible for managing one or more Modbus RS-485 buses to communicate with multiple connected smart sensors. It receives abstract instructions from the central controller, converts them into specific Modbus messages, and sends them to the sensors. Simultaneously, it performs preliminary parsing and encapsulation of the sensor response messages and uploads them to the central controller.

[0045] Local Verification Unit: This is a processing module with computing capabilities (such as an embedded microprocessor). Its main function is to execute the real-time verification logic in the data acquisition and self-verification steps, specifically including: Range verification: Using range information obtained from sensor metadata, each acquired raw data value is instantly evaluated. For example, if a temperature sensor reading exceeds 150°C, the data is immediately marked as "invalid due to over-range" locally, and an alarm record with a timestamp is generated.

[0046] Time-series / statistical verification: Maintain a data sliding window to perform simple time-series analysis and statistical calculations (such as calculating the standard deviation) on continuously collected data. If a sensor's data is found to fluctuate drastically within a short period of time (standard deviation > 2℃ for 3 consecutive points), a "data fluctuation anomaly" state is triggered.

[0047] This unit can operate independently of the central controller, ensuring the basic quality of local data and caching abnormal events even when the network is interrupted or the central controller is busy.

[0048] The intelligent sensor has a built-in non-volatile memory for storing self-describing metadata, a dynamic configuration module, and a communication module that supports responding to broadcast queries. The self-describing metadata includes: a unique device identifier, supported Modbus protocol versions, a readable register list, data type and range information of each register, and a verification algorithm identifier.

[0049] Specifically, the intelligent sensor is the terminal sensing and execution unit of this system, deployed at various monitoring points underground in the coal mine (such as gas concentration, temperature, wind speed, equipment status, etc.). Compared with traditional Modbus sensors, the intelligent sensor in this embodiment has the following key enhancements: Self-describing electronic tags: Each sensor is pre-programmed with a structured self-describing metadata data packet in its internal non-volatile memory (such as EEPROM or Flash) at the factory. This metadata data packet contains at least: Unique Device Identifier: A globally unique identifier that serves as the device's "ID card".

[0050] Protocol support information: Supported Modbus protocol versions and function codes (such as 03 Read Holding Register, 04 Read Input Register).

[0051] Register mapping table: Defines in detail the address, data type (e.g., integer, floating-point), data unit (e.g., ℃, %LEL), range (e.g., 0-100℃), and data scaling ratio of each readable register.

[0052] Verification algorithm identifier: Indicates the data verification method supported or recommended by the device.

[0053] Dynamic Configuration Module: This module's firmware supports receiving and processing special configuration frames from the central controller. When a valid address configuration command is received, it can dynamically update the local Modbus slave address and write the new address back to non-volatile memory for persistent storage, ensuring that the address remains unchanged after a power outage and restart.

[0054] Responsive Communication Module: In addition to responding to standard Modbus data queries, this module is specifically designed to listen for broadcast query frames on the bus. When it detects a query command that matches its own UID, it can immediately and proactively respond by sending back a self-describing frame containing its own metadata.

[0055] The dynamic configuration module in the smart sensor is used to receive address configuration frames from the central controller; Update the Modbus slave address contained in the configuration frame to the local working register; The updated Modbus slave address is persistently stored in the non-volatile memory to ensure that the address remains unchanged after the device restarts.

[0056] The local verification unit of the edge node is used to generate anomaly alarm records and store them locally when data anomalies are detected; The pre-processed and verified valid data and abnormal records are uploaded to the central controller.

[0057] This embodiment provides an automatic sensor identification and data acquisition system for coal mines. Through a three-level distributed architecture and intelligent algorithm collaboration, it achieves significant technological advancements and practical benefits. The core advantage of the system lies in its true "plug-and-play" capability for sensor devices. New devices can be automatically identified and configured after connecting to the network, completely changing the inefficient traditional method of manually setting addresses and parameters for each device. This significantly shortens deployment time and reduces the probability of configuration errors due to human error. Regarding data quality assurance, the system constructs a multi-layered self-verification system from underlying transmission verification to upper-layer semantic verification. Through real-time range checks, temporal continuity analysis, and statistical fluctuation monitoring, the system can automatically identify abnormal data and trigger alarms, ensuring the reliability and rationality of the collected data and providing high-quality data support for safe production decisions. The system possesses strong adaptive capabilities, supporting hot-swapping of devices and dynamic network reconfiguration. When the network topology changes or devices are replaced, the system can automatically reassign addresses and maintain data acquisition continuity, effectively avoiding critical monitoring data interruptions due to equipment maintenance and significantly improving the overall reliability of the system.

[0058] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method for automatic identification and data acquisition of sensors in coal mines, characterized in that, include: Based on the device self-description metadata pre-installed in the sensors, the sensor devices in the network are automatically discovered through a broadcast query protocol and physical layer identification mechanism, and their self-description metadata is parsed to generate device identification results and register read instruction sets. Based on the unique device identifier in the device's self-description metadata and the address pool maintained by the central controller, the sensor is automatically assigned and configured with conflict-free Modbus slave addresses through conflict detection and dynamic addressing algorithms. Based on the register read instruction set, data is acquired from the sensor, and the acquired data is automatically verified based on the range, timing information and built-in multi-level verification mechanism in the self-describing metadata to generate valid data.

2. The method for automatic identification and data acquisition of coal mine sensors according to claim 1, characterized in that, The method, based on the device self-description metadata pre-installed in the sensors, automatically discovers sensor devices in the network through a broadcast query protocol and a physical layer identification mechanism, parses their self-description metadata, and generates device identification results and register read instruction sets, including: When the Modbus bus is idle, the central controller sends a broadcast signal containing a query frame; after receiving a query frame that matches its own unique device identifier, the sensor responds with a self-description frame containing the device type, serial number and protocol version. The register mapping table in the self-describing frame is parsed, and the corresponding Modbus read instruction set is dynamically generated according to the function codes supported by the sensor. Verify the rationality of the data types, units, and ranges in the register mapping table.

3. The automatic identification and data acquisition method for coal mine sensors according to claim 1, characterized in that, The automatic allocation and configuration of conflict-free Modbus slave addresses for sensors based on the unique device identifier in the device's self-description metadata and the address pool maintained by the central controller, through conflict detection and dynamic addressing algorithms, includes: A hash algorithm is used to map the sensor's unique device identifier to an initial address suggestion value; An address probe frame is sent to the initial address suggestion value. If a conflict response is received, a secondary hash calculation is initiated to generate a new address suggestion value until a conflict-free address is obtained. The conflict-free address is sent to the sensor via a configuration frame. After receiving and confirming the address, the sensor writes it into its own non-volatile memory.

4. The method for automatic identification and data acquisition of coal mine sensors according to claim 1, characterized in that, The multi-level verification mechanism includes: Cyclic redundancy check is performed on data transmission at the Modbus protocol frame level; Based on the range information in the self-describing metadata, a hard range check is performed on the collected sensor values, and data that exceeds the range is marked as invalid and an alarm is triggered. By comparing the timestamps of data frames with the expected acquisition sequence of the system, the continuity of data acquisition is verified, and data with deviations exceeding the threshold are judged as timing anomalies. Based on the statistical characteristics of continuously collected data calculated using a sliding window, an alarm for abnormal data fluctuation is triggered when the standard deviation or rate of change of the data exceeds a preset threshold.

5. The method for automatic identification and data acquisition of coal mine sensors according to claim 1, characterized in that, Also includes: At the edge nodes, the valid data that has undergone self-verification is preprocessed locally, including data cleaning, aggregation, and preliminary anomaly detection.

6. A coal mine sensor automatic identification and data acquisition system, characterized in that, include: The central controller integrates a Modbus master module and an intelligent algorithm engine to perform automatic device identification and metadata acquisition steps, dynamic addressing and address configuration steps, and coordinate the data acquisition process. The edge node is equipped with a protocol conversion unit and a local verification unit, which are used to connect to the central controller and perform verification functions and edge preprocessing. The intelligent sensor has a built-in non-volatile memory for storing self-describing metadata, a dynamic configuration module, and a communication module that supports responding to broadcast queries.

7. The coal mine sensor automatic identification and data acquisition system according to claim 6, characterized in that, The self-describing metadata includes: a unique device identifier, supported Modbus protocol versions, a list of readable registers, data type and range information for each register, and a verification algorithm identifier.

8. The coal mine sensor automatic identification and data acquisition system according to claim 6, characterized in that, The central controller maintains a dynamically allocated Modbus slave address pool and runs a dynamic addressing module based on an improved conflict avoidance algorithm.

9. The coal mine sensor automatic identification and data acquisition system according to claim 6, characterized in that, The dynamic configuration module in the smart sensor is used to receive address configuration frames from the central controller. Update the Modbus slave address contained in the configuration frame to the local working register; The updated Modbus slave address is persistently stored in the non-volatile memory to ensure that the address remains unchanged after the device restarts.

10. The coal mine sensor automatic identification and data acquisition system according to claim 6, characterized in that, The local verification unit of the edge node is used to generate an anomaly alarm record and store it locally when an anomaly is detected. The pre-processed and verified valid data and abnormal records are uploaded to the central controller.

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