A register address positioning method, device and medium for device display data

Abstract

The present application discloses a register address location method, device, and medium for device display data, relating to the field of industrial control communication technology. The method comprises: receiving visual display data obtained by a user from a device display module through a human-computer interaction interface, and collecting raw binary data from the device register through the MODBUS protocol; determining the data type of the visual display data, and based on the data type, performing binary conversion on the visual display data to obtain visual conversion data; matching a preset positioning algorithm to be applied based on the data type of the visual conversion data; if the data type of the visual conversion data is integer data, executing an exact matching algorithm; if the data type of the visual conversion data is non-integer data, executing an approximate matching algorithm to determine the source data corresponding to the visual conversion data in the raw binary data; and outputting structured information of the source data; wherein the structured information includes a point address, a data type, and a storage format.

Description

Technical Field

[0001] The present application relates to the field of industrial control communication technology, and in particular to a method, device, and medium for locating a register address of device display data. Background Art

[0002] In the industrial control field, data communication technology based on the MODBUS protocol has been widely used for device networking and data exchange. Existing technologies typically rely on predefined point address tables and fixed data formatting rules to parse register data. This allows for stable data collection when the protocol configuration is known. However, this approach has fundamental limitations: in scenarios where legacy equipment lacks detailed point address tables, engineers can only visually obtain data values ​​from the device's LCD screen, but are unable to quickly determine the corresponding register address, data type, and byte storage rules (such as big-endian / little-endian order and word swapping).

[0003] Current solutions rely primarily on manual, address-by-address testing, repeatedly modifying register addresses and observing changes in values ​​to infer data storage locations. This process is time-consuming, often requiring hours to locate a single data point, and is prone to address mismatches due to human error. Furthermore, devices from different manufacturers utilize varying endian combinations (such as 16 endian transformation modes) and floating-point encoding rules, making it difficult for manual testing to cover all possible storage variants, significantly reducing the success rate of cross-device data parsing.

[0004] Furthermore, existing tools lack automated comparison mechanisms, requiring manual comparison of visually input values ​​with the original register data. While an exact match can be attempted for integer data, floating-point data can suffer from precision errors (such as rounding issues under the IEEE 754 standard), making it difficult to manually determine the valid matching range. This further renders data traceability unreliable, making it difficult to verify the authenticity of the data source during troubleshooting.

[0005] Therefore, how to quickly and accurately locate register addresses without detailed bitmaps, while adaptively and compatible with the byte order rules and data type variants of devices from multiple manufacturers, has become a technical problem that technicians in this field urgently need to solve. Summary of the Invention

[0006] The embodiments of the present application provide a register address locating method, device, and medium for device display data, which are used to solve the following technical problems: how to quickly and accurately locate register addresses without detailed bitmaps, while adaptively and being compatible with the byte order rules and data type variants of devices from multiple manufacturers.

[0007] In a first aspect, an embodiment of the present application provides a register address locating method for device display data, the method comprising: receiving visual display data obtained by a user from a device display module through a human-computer interaction interface, and collecting original binary data of the device register through a MODBUS protocol; determining the data type of the visual display data, and based on the data type, performing binary conversion on the visual display data to obtain visual conversion data; matching a preset positioning algorithm to be applied based on the data type of the visual conversion data; wherein the data types include: integer data and non-integer data; the positioning algorithms to be applied include: exact matching algorithm and approximate matching algorithm; if the data type of the visual conversion data is integer data, executing the exact matching algorithm; if the data type of the visual conversion data is non-integer data, executing the approximate matching algorithm to determine the source data corresponding to the visual conversion data in the original binary data; outputting structured information of the source data; wherein the structured information includes point address, data type and storage format.

[0008] In one embodiment of the present application, raw binary data of a device register is collected through the MODBUS protocol, specifically including: establishing a MODBUS-TCP communication connection with a target device; traversing a preset register address range and reading the raw binary data stream in the register in address order; caching the raw binary data stream into a memory buffer in register address order, and marking the starting address offset of each data block.

[0009] In one embodiment of the present application, determining the data type of visually displayed data specifically includes: detecting whether the visually displayed data contains a decimal point or an exponential symbol; if a decimal point or an exponential symbol is detected, determining that the visually displayed data is non-integer data; if no decimal point or exponential symbol is detected, determining that the visually displayed data is integer data.

[0010] In one embodiment of the present application, based on the data type, the visual display data is binary converted to obtain visual conversion data, specifically including: if the data type of the visual display data is integer data, determining the numerical range of the visual display data, and selecting a matching digital integer conversion rule based on the numerical range to perform signed or unsigned binary conversion; wherein the digital integer conversion rules include: 8-bit integer conversion rules, 16-bit integer conversion rules, 32-bit integer conversion rules, and 64-bit integer conversion rules; if the data type of the visual display data is non-integer data, using the floating-point format standard to perform 32-bit or 64-bit binary conversion.

[0011] In one embodiment of the present application, after performing binary conversion on the visual display data based on the data type to obtain visual conversion data, the method further includes: performing a byte order conversion operation on the visual conversion data to generate a visual conversion data set including both big endian and little endian formats.

[0012] In one embodiment of the present application, if the data type of the visual conversion data is integer data, an accurate matching algorithm is executed, specifically including: decomposing the visual conversion data into a multidimensional feature vector; wherein the multidimensional feature vector includes a sign bit feature, a value bit feature and a bit width feature; dynamically generating a feature matching mask according to the value range of the visual conversion data, and the feature matching mask differentially configures the matching weights of the sign bit and the value bit; dividing the device register address range into multiple parallel computing partitions, and performing fast screening on each partition based on the feature matching mask to generate a set of candidate addresses; performing a full feature comparison on each address in the candidate address set, and calculating the Hamming distance between the visual conversion data and the register binary data; when the comprehensive index of the sign bit matching, the value bit matching and the byte order matching reaches a preset threshold, it is determined to be an accurate match address.

[0013] In one embodiment of the present application, if the data type of the visual conversion data is non-integer data, an approximate matching algorithm is executed, specifically including: decomposing the visual conversion data into sign bit features, exponent bit features and mantissa bit features according to the IEEE754 standard, and calculating the number of significant digits; generating a parsing pattern set including 16 byte order transformation modes and 8 exponent offset adjustment modes; performing full pattern parsing in the parsing pattern set for each register address through a multi-threaded parallel engine; mapping the parsing results to the IEEE754 feature space, and synchronously calculating the three-dimensional error vectors of absolute error, relative error and engineering error; dynamically adjusting the error threshold based on the order of magnitude of the visual conversion data, and screening the Pareto optimal matching address from the three-dimensional error space.

[0014] In one embodiment of the present application, outputting structured information of source data specifically includes: generating a structured report including point address, data type, byte order conversion mode and register storage format; marking the sign bit identifier, numerical bit length and word exchange method of the source data in the structured report; storing the structured report in a local database with a timestamp name and generating a unique traceability identification code; and displaying the matching results and the storage path of the structured report through a human-computer interaction interface.

[0015] In a second aspect, an embodiment of the present application also provides a register address locating device for device display data, the device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a register address locating method for device display data such as any one of the above items.

[0016] In a third aspect, an embodiment of the present application further provides a non-volatile computer storage medium storing computer executable instructions. When the computer executable instructions are executed, a register address locating method for displaying data of a device as described above is implemented.

[0017] The present invention provides a method, device, and medium for locating register addresses for device display data, which have the following beneficial effects: An innovative mechanism, driven by visual data input and an algorithm for automatically locating register addresses, completely resolves the data collection challenges associated with the lack of point tables for legacy industrial equipment. Technically, the system dynamically selects a matching algorithm based on user-input visual display data (using eigenvector decomposition and Hamming distance for precise matching, and multi-mode parsing and Pareto-optimal error screening for non-integer data). This not only enables rapid register address location (millisecond-level response), but also seamlessly compatibility with device protocols from different manufacturers through byte order conversion and adaptive parsing in word swap mode (covering 16 byte order combinations and 8 exponent offset adjustments). Structured output results (including point addresses, data types, byte order identifiers, and storage formats) significantly enhance data traceability. Engineers can directly locate device anomalies based on reports, reducing traditional manual testing, which takes hours, to minutes. This significantly reduces cross-device adaptation costs and operational errors, providing high-precision, high-efficiency underlying technical support for industrial digital transformation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0019] Figure 1 A flow chart of a method for locating a register address of device display data provided in an embodiment of the present application;

[0020] Figure 2 A schematic diagram of the internal structure of a register address location device for displaying data provided in an embodiment of the present application. DETAILED DESCRIPTION

[0021] To make the purpose, technical solutions, and advantages of this application more clear, the technical solutions of this application will be clearly and completely described below in conjunction with the specific embodiments of this application and the corresponding drawings. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0022] The embodiments of the present application provide a register address locating method, device, and medium for device display data, which are used to solve the following technical problems: how to quickly and accurately locate register addresses without detailed bitmaps, while adaptively and being compatible with the byte order rules and data type variants of devices from multiple manufacturers.

[0023] The technical solutions proposed in the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0024] Figure 1 This is a flow chart of a method for locating the register address of device display data provided in an embodiment of the present application. Figure 1 As shown, an embodiment of the present application provides a method for locating a register address of device display data, which specifically includes the following steps:

[0025] Step 101: Receive visual display data obtained by a user from a device display module through a human-computer interaction interface, and collect original binary data of a device register through a MODBUS protocol.

[0026] In one embodiment of the present application, raw binary data of a device register is collected through the MODBUS protocol, specifically including: establishing a MODBUS-TCP communication connection with a target device; traversing a preset register address range and reading the raw binary data stream in the register in address order; caching the raw binary data stream into a memory buffer in register address order, and marking the starting address offset of each data block.

[0027] In this embodiment, the human-machine interface is a graphical operation panel configured on the industrial control terminal. It includes a data input box, a device connection configuration area, and a real-time communication status indicator module. For example, when engineers are working with older equipment without a point meter (such as a hydraulic control system manufactured 20 years ago), they can visually read the real-time parameter values ​​displayed on the device's LCD screen (such as a temperature value of "38.5°C" or a pressure value of "12.8MPa") and manually enter these values ​​into the data input box to generate the visual display data. It is important to note that this process does not require prior knowledge of register addresses or data formats, effectively eliminating the pain point of traditional methods that rely on device technical documentation.

[0028] The MODBUS protocol acquisition process is implemented as follows: First, a MODBUS-TCP communication connection is established with the target device. This connection is configured with communication parameters based on the industrial field network environment, including the device IP address (e.g., 192.168.1.100), service port number (default 502), and slave device ID. Specifically, the communication module uses an asynchronous handshake mechanism, completing connection authentication through three data packet exchanges, ensuring a stable connection even in complex electromagnetic interference environments.

[0029] It should be noted that the register data acquisition range is set to the 0x0000 to 0xFFFF address space based on typical industrial equipment configurations. When acquiring raw binary data from device registers, the register raw binary data stream is read in a sequential scan, with each batch read optimized to 125 register cells (approximately 250 bytes) to avoid single request timeouts while ensuring transmission efficiency. During data caching, the raw binary data stream is partitioned by address offset and stored in a memory buffer, simultaneously generating an address index mapping table. For example, when reading data in the 0x0100-0x01FF segment, the buffer header automatically marks the starting address 0x0100 and the data block length, providing a basis for rapid location identification for subsequent feature comparison.

[0030] It's understandable that this step, through the combination of human-machine collaborative input and automated data collection, creates a dual data source for subsequent data processing. On the one hand, the visual display data provides the user with an intuitive understanding of the device's status; on the other hand, the raw binary data in the registers preserves the integrity of the device's underlying communication protocol. Together, these two data sources form the processing targets of the address location algorithm.

[0031] Specifically, in data acquisition exception handling scenarios, when communication is interrupted or verification fails (e.g., CRC checksum mismatch), the system automatically triggers a reconnection mechanism and records the abnormal address range. For example, if a read fails in the address range 0x0300-0x0320, the log file will mark the abnormal range and skip collecting subsequent addresses, preventing overall data acquisition interruptions due to local failures. This fault-tolerant design is particularly suitable for retrofitting older equipment with unstable register states.

[0032] Step 102: Determine the data type of the visual display data, and perform binary conversion on the visual display data based on the data type to obtain visual conversion data.

[0033] In one embodiment of the present application, determining the data type of visually displayed data specifically includes: detecting whether the visually displayed data contains a decimal point or an exponential symbol; if a decimal point or an exponential symbol is detected, determining that the visually displayed data is non-integer data; if no decimal point or exponential symbol is detected, determining that the visually displayed data is integer data.

[0034] In one embodiment of the present application, based on the data type, the visual display data is binary converted to obtain visual conversion data, specifically including: if the data type of the visual display data is integer data, determining the numerical range of the visual display data, and selecting a matching digital integer conversion rule based on the numerical range to perform signed or unsigned binary conversion; wherein the digital integer conversion rules include: 8-bit integer conversion rules, 16-bit integer conversion rules, 32-bit integer conversion rules, and 64-bit integer conversion rules; if the data type of the visual display data is non-integer data, using the floating-point format standard to perform 32-bit or 64-bit binary conversion.

[0035] In this embodiment, when determining the data type, the visual display data input by the user is parsed through a character feature scanning engine. It is understandable that the scanning engine uses a regular expression matching algorithm to detect whether the data string contains a decimal point "." or an exponential symbol "E / e" (for example, the input value "36.5" contains a decimal point, and "1.2E3" contains an exponential symbol). It should be noted that this judgment logic is based on the general expression rules for displaying numerical values ​​on industrial equipment - when a decimal point or exponential symbol is detected, it is determined to be non-integer data (floating point type), otherwise it is integer data. Specifically, in the PLC temperature monitoring scenario, the input value "38.5" is identified as a floating point type because it contains a decimal point, while "1500" is determined to be an integer.

[0036] In this embodiment, when performing a binary conversion operation:

[0037] For integer data conversion: The numerical range characteristics of the input value are dynamically evaluated to select the optimal bit width conversion rule. This process, understandably, distinguishes between signed and unsigned scenarios: for negative input values ​​(such as "-25"), the signed two's complement conversion rule is automatically invoked; for positive values, unsigned conversion is used. Specifically, the bit width selection strategy follows the typical data range of industrial equipment. For example, smaller numerical ranges automatically adapt to 8-bit or 16-bit conversion to improve processing efficiency, while larger numerical ranges enable 32-bit or 64-bit conversion to ensure complete accuracy.

[0038] For non-integer data conversion, bit-level mapping is performed strictly in accordance with the IEEE 754 floating-point standard. This process includes sign bit assignment (positive / negative determination), exponent bit offset compensation (based on the 127 / 1023 rule), and mantissa normalization. For example, when converting the input value "36.5" to a 32-bit single-precision floating-point number, the integer portion "36" and the fractional portion "0.5" are first separated. After conversion to scientific notation, the exponent bit characteristic value is generated, ultimately producing a 32-bit or 64-bit binary sequence that conforms to the standard format.

[0039] As you can understand, after the conversion is complete, the system generates visually converted data, whose data structure contains a complete binary representation of the original value. This data serves as the input source for the subsequent matching algorithm, and its format precision directly affects the accuracy of address location. Specifically, in the boiler pressure monitoring case, the floating-point conversion of the input value "12.8MPa" generates 32-bit binary data, which fully preserves the engineering significance and precision characteristics of the original value.

[0040] In one embodiment of the present application, after performing binary conversion on the visual display data based on the data type to obtain visual conversion data, the method further includes: performing a byte order conversion operation on the visual conversion data to generate a visual conversion data set including both big endian and little endian formats.

[0041] It's important to note that after obtaining the basic conversion results, byte order preprocessing is automatically performed: For the same set of visually converted data, two storage formats, big-endian (high-order byte first) and little-endian (low-order byte first), are generated simultaneously. For example, the 16-bit integer value 0x1234 is simultaneously generated as [0x12, 0x34] and [0x34, 0x12]. This design addresses storage differences between devices from different manufacturers, such as Siemens (big-endian) and Omron (little-endian), ensuring compatibility with subsequent matching algorithms.

[0042] Step 103: Match the preset positioning algorithm to be applied based on the data type of the visual conversion data.

[0043] In the embodiment of the present application, the data types include: integer data and non-integer data; the positioning algorithms to be applied include: exact matching algorithm and approximate matching algorithm.

[0044] In this embodiment, the algorithmic matching mechanism constitutes the core decision-making layer for address location. Based on the data type characteristics of the visually converted data generated in step 102, it is automatically routed to the differentiation processing engine. It should be noted that this decision-making logic is designed based on the characteristics of industrial data: integer data (such as device status codes and counter values) is discrete and has no precision loss, while non-integer data (such as temperature and pressure values) has floating-point precision fluctuations. This difference directly determines the selection criteria of the matching algorithm.

[0045] It is understandable that the algorithm matching process is divided into two paths:

[0046] Integer data routing: When the data type is identified as an integer (such as INT16 / INT32), an exact matching algorithm is invoked. Specifically, this algorithm is designed based on the deterministic nature of binary data—the strict correspondence between sign bits and value bits. For example, in a motor speed monitoring scenario, the binary sequence of the input value "1500" (16-bit integer) is unique. Through feature vector decomposition and address space partitioning, precise register-level location can be achieved.

[0047] Non-integer data routing: When the data type is identified as floating point (e.g., FLOAT32), an approximate matching algorithm is used. This choice is based on the storage characteristics of floating-point data in industrial settings: different manufacturers' devices may employ different exponent offsets (e.g., ±127) or mantissa truncation strategies. Specifically, in the boiler temperature monitoring case, the input value "38.5" has multiple valid binary representations after IEEE 754 conversion, requiring multi-modal analysis and three-dimensional error assessment to achieve an optimal match.

[0048] Step 104: If the data type of the visually converted data is integer data, an exact matching algorithm is executed; if the data type of the visually converted data is non-integer data, an approximate matching algorithm is executed to determine the source data corresponding to the visually converted data in the original binary data.

[0049] In one embodiment of the present application, if the data type of the visual conversion data is integer data, an accurate matching algorithm is executed, specifically including: decomposing the visual conversion data into a multidimensional feature vector; wherein the multidimensional feature vector includes a sign bit feature, a value bit feature and a bit width feature; dynamically generating a feature matching mask according to the value range of the visual conversion data, and the feature matching mask differentially configures the matching weights of the sign bit and the value bit; dividing the device register address range into multiple parallel computing partitions, and performing fast screening on each partition based on the feature matching mask to generate a set of candidate addresses; performing a full feature comparison on each address in the candidate address set, and calculating the Hamming distance between the visual conversion data and the register binary data; when the comprehensive index of the sign bit matching, the value bit matching and the byte order matching reaches a preset threshold, it is determined to be an accurate match address.

[0050] In one embodiment of the present application, if the data type of the visual conversion data is non-integer data, an approximate matching algorithm is executed, specifically including: decomposing the visual conversion data into sign bit features, exponent bit features and mantissa bit features according to the IEEE754 standard, and calculating the number of significant digits; generating a parsing pattern set including 16 byte order transformation modes and 8 exponent offset adjustment modes; performing full pattern parsing in the parsing pattern set for each register address through a multi-threaded parallel engine; mapping the parsing results to the IEEE754 feature space, and synchronously calculating the three-dimensional error vectors of absolute error, relative error and engineering error; dynamically adjusting the error threshold based on the order of magnitude of the visual conversion data, and screening the Pareto optimal matching address from the three-dimensional error space.

[0051] In this embodiment, this step achieves precise positioning of register addresses through a dual-channel algorithm engine. This design stems from the inherent differences in industrial field data: the discrete precision of integer data and the continuous approximation of non-integer data. The algorithm execution path is strictly divided based on data type: when the visually converted data is integer (such as a device status code or counter value), the exact matching algorithm is activated; when the data is non-integer (such as analog quantities such as temperature and pressure), the approximate matching algorithm is used.

[0052] It should be noted that the core of the accurate matching algorithm lies in a three-level positioning mechanism. First, integer data is decomposed into a three-dimensional feature vector consisting of a sign bit feature (indicating positive and negative polarity), a value bit feature (storing the actual value), and a bit width feature (indicating data length). For example, in the inverter frequency setting scenario, the input value "50" (INT16) is converted into a feature vector [sign bit 0, value bits "00110010", bit width 16]. Subsequently, a feature matching mask is dynamically generated, assigning a higher weight to the sign bit to quickly eliminate addresses with incorrect polarity. Next, the register address space is divided into multiple parallel computation partitions, and a set of candidate addresses is generated through mask filtering. Finally, a full-feature Hamming distance calculation is performed on the candidate addresses, combined with the pre-byte order conversion data (the big-endian / little-endian data set generated in step 102) to achieve a 100% accurate match. This bit-by-bit comparison mechanism is particularly suitable for scenarios requiring absolute precision, such as device on / off status, to avoid control instruction deviations caused by single-bit errors.

[0053] The approximate matching algorithm is designed to address the unique characteristics of industrial floating-point data: non-integer data is first decomposed into three features: sign bit, exponent bit (including offset compensation), and mantissa bit according to the IEEE 754 standard. In the boiler temperature monitoring case, the input value "85.3" undergoes feature decomposition, automatically generating a parsing pattern library containing 16 byte order permutations (such as word-and-byte swap combinations) and eight exponent offset adjustments. A multi-threaded concurrent engine allows for parallel parsing of all patterns for the same register address, significantly improving processing efficiency. The matching decision stage utilizes an innovative three-dimensional error assessment system: absolute error (the absolute deviation between the parsed value and the visual value), relative error (the ratio of the deviation to the actual value), and engineering error (the allowable deviation based on equipment technical parameters) form the screening criteria. Threshold weights are dynamically adjusted based on the magnitude of the input value: for example, large values ​​(such as a pressure value of 1000 MPa) prioritize relative error control, while small values ​​(such as a temperature fluctuation of 0.5°C) prioritize absolute error constraints. Finally, the optimal address is selected from the multi-dimensional solution space through the Pareto frontier theory. This mechanism is effectively compatible with the floating-point encoding habits of different manufacturers (such as the non-standard exponent offset used by Rockwell PLC), while avoiding the risk of mismatching due to loss of floating-point precision.

[0054] It is worth noting that the collaborative application of the dual algorithms in the retrofit of wind turbine pitch control systems has demonstrated their engineering value: integer data (blade angle codes) achieve zero-error positioning through accurate matching, while non-integer data (wind speed floating-point values) achieve an effective matching rate of over 98% within an engineering error range of ±0.1 m / s. This differentiated processing strategy ensures absolute reliability of key control parameters while accommodating reasonable fluctuations in analog data.

[0055] Step 105: Output the structured information of the source data.

[0056] In the embodiment of the present application, the structured information includes a point address, a data type, and a storage format.

[0057] In one embodiment of the present application, outputting structured information of source data specifically includes: generating a structured report including point address, data type, byte order conversion mode and register storage format; marking the sign bit identifier, numerical bit length and word exchange method of the source data in the structured report; storing the structured report in a local database with a timestamp name and generating a unique traceability identification code; and displaying the matching results and the storage path of the structured report through a human-computer interaction interface.

[0058] In this embodiment, this step serves as the final output stage of the address location process, and is intended to convert the matching results into a standardized report that can be directly applied by engineering personnel. It is understandable that this process not only provides core address information, but also ensures the traceability and visual presentation of the data. It should be noted that the generation of structured information strictly follows the application requirements of the industrial field: first, the source data address (such as 0x00A2) located by the matching algorithm in step 104 is extracted, and a complete set of technical parameters is automatically assembled based on the data type characteristics (such as INT16, FLOAT32). Specifically, in the boiler control system modification scenario, when the temperature parameter register is matched, the system automatically fills in the point address field, data type identifier, and storage form description to form a configuration template that can be directly imported into the SCADA system.

[0059] For example, the generation of a structured report includes multiple technical details: the system creates a report framework containing core fields, where the point address is directly inherited from the output of the matching algorithm (such as the 0x0103 address of the inverter frequency parameter), and the data type annotation traces back to the judgment conclusion of step 102 (such as the integer or floating point type identifier). It can be understood that the construction of the storage format field is particularly critical: the byte order conversion mode (big endian / little endian) and the word swap method (such as the byte swap mark) are dynamically labeled based on the actual parsing pattern during the matching process. It should be noted that the addition of auxiliary identifiers significantly enhances the engineering value of the report: the sign bit identifier (such as the positive / negative mark) helps quickly identify data polarity, the numeric bit length (such as 16 bits) guides the subsequent communication protocol configuration, and the word swap method clarifies the device-specific data reorganization rules.

[0060] Specifically, the report storage and traceability mechanism: The system names report files using a millisecond-accurate timestamp format (e.g., YYYYMMDD_HHMMSS) and generates a globally unique traceability identifier (e.g., TRACE-7B3E). This identifier is bound to the report content using a hash algorithm, ensuring that any modifications can be detected. In a wind power monitoring system implementation, this identifier allows engineers to quickly retrieve matching records from three months ago, effectively supporting parameter review during equipment maintenance.

[0061] In this embodiment, the result output interface utilizes a multi-view collaborative design: the main window displays the currently matched point address and data transformation method in real time, while the sidebar provides navigation to the storage path of the structured report. This design significantly reduces the operational barrier to entry—even novice engineers unfamiliar with the MODBUS protocol can directly apply the results to PLC programming software using the intuitive "Export Configuration" button.

[0062] Finally, this embodiment supports batch report export: in the scenario of renovating an old production line, structured information sets of dozens of parameters can be exported at once and automatically categorized and stored by equipment functional area. This design significantly improves the implementation efficiency of large-scale projects, reducing document compilation time by approximately 90% compared to traditional manual recording methods, fully demonstrating the engineering practical value of this application solution.

[0063] The above is an embodiment of the method proposed in this application. Based on the same inventive concept, this application embodiment also provides a device for locating the register address of device display data, the structure of which is as follows: Figure 2 shown.

[0064] Figure 2 This is a schematic diagram of the internal structure of a device that displays data on a register address provided by an embodiment of the present application. Figure 2 As shown, the equipment includes:

[0065] at least one processor 201;

[0066] and, a memory 202 communicatively coupled to the at least one processor;

[0067] The memory 202 stores instructions that can be executed by at least one processor, and the instructions are executed by the at least one processor 201 to enable the at least one processor 201 to:

[0068] Receive visual display data obtained by the user from the device display module through the human-computer interaction interface, and collect the original binary data of the device register through the MODBUS protocol;

[0069] determining a data type of the visual display data, and performing binary conversion on the visual display data based on the data type to obtain visual conversion data;

[0070] Based on the data type of the visual conversion data, a preset positioning algorithm to be applied is matched; wherein the data type includes integer data and non-integer data; and the positioning algorithm to be applied includes an exact matching algorithm and an approximate matching algorithm;

[0071] If the data type of the visually converted data is integer data, an exact matching algorithm is executed; if the data type of the visually converted data is non-integer data, an approximate matching algorithm is executed to determine the source data corresponding to the visually converted data in the original binary data;

[0072] Output the structured information of the source data; the structured information includes the point address, data type and storage format.

[0073] Some embodiments of the present application provide corresponding Figure 1A non-volatile computer storage medium stores computer executable instructions, wherein the computer executable instructions are configured as follows:

[0074] Receive visual display data obtained by the user from the device display module through the human-computer interaction interface, and collect the original binary data of the device register through the MODBUS protocol;

[0075] determining a data type of the visual display data, and performing binary conversion on the visual display data based on the data type to obtain visual conversion data;

[0076] Based on the data type of the visual conversion data, a preset positioning algorithm to be applied is matched; wherein the data type includes integer data and non-integer data; and the positioning algorithm to be applied includes an exact matching algorithm and an approximate matching algorithm;

[0077] If the data type of the visually converted data is integer data, an exact matching algorithm is executed; if the data type of the visually converted data is non-integer data, an approximate matching algorithm is executed to determine the source data corresponding to the visually converted data in the original binary data;

[0078] Output the structured information of the source data; the structured information includes the point address, data type and storage format.

[0079] The various embodiments in this application are described in a progressive manner. Similar portions between the various embodiments can be referenced to each other. Each embodiment focuses on the differences from the other embodiments. In particular, the IoT device and media embodiments are generally similar to the method embodiments, so their description is relatively simple. For relevant portions, refer to the description of the method embodiments.

[0080] The system and medium provided in the embodiments of the present application correspond one-to-one to the method. Therefore, the system and medium also have similar beneficial technical effects to their corresponding methods. Since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the system and medium will not be repeated here.

[0081] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0082] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0083] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0084] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0085] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0086] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0087] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0088] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0089] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A method for locating a register address of device display data, characterized in that: The method comprises: Receive visual display data obtained by the user from the device display module through the human-computer interaction interface, and collect the original binary data of the device register through the MODBUS protocol; determining a data type of the visual display data, and performing binary conversion on the visual display data based on the data type to obtain visual conversion data; Based on the data type of the visual conversion data, matching a preset positioning algorithm to be applied; wherein the data type includes: integer data and non-integer data; the positioning algorithm to be applied includes: exact matching algorithm and approximate matching algorithm; If the data type of the visually converted data is integer data, the exact matching algorithm is executed; if the data type of the visually converted data is non-integer data, the approximate matching algorithm is executed to determine the source data corresponding to the visually converted data in the original binary data; Outputting structured information of the source data; wherein the structured information includes point address, data type and storage format; If the data type of the visual conversion data is integer data, executing the exact matching algorithm specifically includes: Decomposing the visual conversion data into a multidimensional feature vector; wherein the multidimensional feature vector includes a sign bit feature, a value bit feature, and a bit width feature; Dynamically generating a feature matching mask according to the numerical range of the visually converted data, wherein the feature matching mask differentially configures matching weights of sign bits and value bits; Dividing the device register address range into a plurality of parallel computation partitions, and performing fast screening on each partition based on the feature matching mask to generate a set of candidate addresses; Performing full feature comparison on each address in the candidate address set, and calculating the Hamming distance between the visual conversion data and the register binary data; When the comprehensive index of the sign bit matching, value bit matching and byte order matching reaches the preset threshold, it is determined to be an exact match address; If the data type of the visual conversion data is non-integer data, executing the approximate matching algorithm specifically includes: Decomposing the visually converted data into a sign bit feature, an exponent bit feature, and a mantissa bit feature according to the IEEE 754 standard, and calculating the number of significant digits thereof; Generates a parsing pattern set containing 16 byte order conversion modes and 8 exponent offset adjustment modes; Performing full-mode parsing in the parsing mode set on each register address through a multi-threaded parallel engine; The analytical results are mapped to the IEEE754 feature space, and the three-dimensional error vectors of absolute error, relative error and engineering error are calculated simultaneously; The error threshold is dynamically adjusted based on the magnitude of the visual conversion data, and the Pareto optimal matching address is screened from the three-dimensional error space.

2. The method for locating a register address of device display data according to claim 1, characterized in that: Collect the original binary data of the device register through the MODBUS protocol, including: Establish a MODBUS-TCP communication connection with the target device; Traverse the preset register address range and read the original binary data stream in the register in address order; The original binary data stream is cached in a memory buffer in register address order, and the starting address offset of each data block is marked.

3. The method for locating a register address of device display data according to claim 1, characterized in that: Determining the data type of the visual display data specifically includes: detecting whether the visually displayed data includes a decimal point or an exponential symbol; If a decimal point or an exponential symbol is detected, determining that the visually displayed data is non-integer data; If no decimal point or exponential symbol is detected, it is determined that the visual display data is integer data.

4. The method for locating a register address of device display data according to claim 3, wherein: Based on the data type, binary conversion is performed on the visual display data to obtain visual conversion data, specifically including: If the data type of the visual display data is integer data, determining a numerical range of the visual display data, and selecting a matching digital integer conversion rule based on the numerical range to perform signed or unsigned binary conversion; wherein the digital integer conversion rule includes: 8-bit integer conversion rule, 16-bit integer conversion rule, 32-bit integer conversion rule, and 64-bit integer conversion rule; If the data type of the visual display data is non-integer data, a 32-bit or 64-bit binary conversion is performed using a floating-point format standard.

5. The method for locating a register address of device display data according to claim 4, characterized in that: After performing binary conversion on the visual display data based on the data type to obtain visual conversion data, the method further includes: A byte order conversion operation is performed on the visually converted data to generate a visually converted data set including two formats including big endian and little endian.

6. The method for locating a register address of device display data according to claim 1, wherein: Output the structured information of the source data, specifically including: Generate structured reports including point address, data type, byte order conversion mode and register storage format; Marking the sign bit identifier, value bit length and word swapping mode of the source data in the structured report; The structured report is stored in a local database according to the timestamp and named, and a unique traceability identification code is generated; The matching results and the storage path of the structured report are displayed through a human-computer interaction interface.

7. A device for locating a register address of device display data, characterized in that: The device comprises: at least one processor; and, a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the register address locating method for device display data according to any one of claims 1 to 6.

8. A non-volatile computer storage medium storing computer-executable instructions, characterized in that: When the computer executable instructions are executed, the register address locating method for device display data according to any one of claims 1 to 6 is implemented.

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