Visualization method and device for working state of industrial communication module

Abstract

The invention provides a visualization method and device for the working state of an industrial communication module. The method comprises the steps that digital signal characteristic data of the active state of a communication port and analog physical parameter data of the health state of an internal circuit are synchronously collected; respectively generating a first state identifier corresponding to the digital signal characteristic data and a second state identifier corresponding to the analog physical parameter data according to a state mapping rule; performing fusion analysis on the first state identifier and the second state identifier according to state priority logic to generate a target state code; and querying the visual code mapping table according to the target state code, obtaining a corresponding visual driving instruction, and driving a visual display layer to display. According to the invention, through joint acquisition, state fusion and visual coding mapping of the communication activity state and the internal health state, perceptible display of the comprehensive operation state of the module is realized without an external tool, and the maintainability and the operation and maintenance efficiency of the system are greatly improved.

Description

Technical Field

[0001] This application relates to the field of industrial control, and in particular to a method and apparatus for visualizing the working status of an industrial communication module. Background Technology

[0002] In industrial control cabinets, production line distributed I / O stations, and other field environments, various industrial communication modules (such as T-MOD modules with CAN, RS-485, and DIO interfaces) are widely deployed, undertaking critical communication and data conversion functions. The health status of these modules directly affects the stable operation of the entire automation system. Currently, monitoring their working status mainly relies on two traditional methods: First, maintenance personnel need to manually judge the status on-site by physically plugging and unplugging test equipment or observing simple indicator lights. This method is not only cumbersome and inefficient, but also cannot provide timely warnings when the module has hidden faults (such as signal quality degradation or internal circuit parameter drift but not complete failure). Second, it relies on host computer monitoring software to query the status through polling communication. This method not only increases the network and host computer load, but also makes the module an imperceptible black box when the host or network fails, losing its independent observability.

[0003] Existing technologies all suffer from a fundamental flaw: they cannot achieve autonomous perception, intelligent fusion, and on-site intuitive visualization of the communication module's multi-dimensional operating status (including communication activity and internal health) without being separated from external devices and upper-level systems, resulting in delayed fault location and difficulties in preventive maintenance. Summary of the Invention

[0004] This application provides a method and apparatus for visualizing the working status of an industrial communication module, which solves the problem that related technologies cannot achieve the visualization of the operating status of communication modules, resulting in delayed fault location and difficulty in preventive maintenance.

[0005] The first aspect of this application provides a method for visualizing the operating status of an industrial communication module, the method comprising: During the operation of the industrial communication module, digital signal characteristic data of the communication port activity status and analog physical parameter data of the internal circuit health status are collected synchronously. According to the preset state mapping rules, a first state identifier corresponding to the digital signal feature data and a second state identifier corresponding to the analog physical parameter data are generated respectively. The first state identifier and the second state identifier are fused and analyzed according to the preset state priority logic to generate the target state code; The visual encoding mapping table is queried according to the target state code to obtain the corresponding visual driving instruction, and the visualization display layer is driven to display based on the visual driving instruction.

[0006] Optionally, in the first implementation of the first aspect of this application, the step of synchronously acquiring digital signal characteristic data of the communication port activity status and analog physical parameter data of the internal circuit health status includes: The signal acquisition unit of the industrial communication module continuously samples the level signal of the communication port, and performs statistical analysis and time interval calculation on the rising and falling edges in the sampling sequence to generate digital signal feature data. The analog-to-digital conversion unit of the industrial communication module periodically collects analog voltage and temperature signals that reflect the health status of the internal circuits, generating analog physical parameter data.

[0007] Optionally, in a second implementation of the first aspect of this application, the step of generating a first state identifier corresponding to the digital signal feature data and a second state identifier corresponding to the analog physical parameter data according to a preset state mapping rule includes: Perform time-series analysis on the digital signal feature data to determine the number of valid signal pulses conforming to the communication protocol specifications within a preset statistical time window; A first state identifier is generated based on the comparison result between the number of effective signal pulses and the preset normal communication activity threshold range, as well as the stability index of the interval between adjacent pulses. A multi-dimensional health assessment is performed on the simulated physical parameter data to determine the percentage deviation of the average value of each physical parameter within the sliding time window relative to the preset nominal value. A second state identifier is generated based on the parameter deviation level mapping corresponding to the percentage deviation.

[0008] Optionally, in the third implementation of the first aspect of this application, the step of fusing and analyzing the first state identifier and the second state identifier according to a preset state priority logic to generate a target state code includes: The first state identifier and the second state identifier are respectively parsed into state vectors; Based on a preset weight matrix, the state vector corresponding to the first state identifier and the state vector corresponding to the second state identifier are weighted and superimposed to generate a fused state vector. Determine whether there exists a target state vector in the fused state vector whose fault level value is not lower than the first alarm threshold; If the target state vector exists, the target state code is obtained by querying the state code conversion table based on the number of target state vectors.

[0009] Optionally, in the fourth implementation of the first aspect of this application, after the step of determining whether there is a target state vector in the fused state vector whose fault level value exceeds a preset alarm threshold, the method further includes: Scan the other state vectors in the fused state vectors, excluding the target state vector, to determine the secondary state vectors whose fault level value is lower than the first alarm threshold and higher than the second alarm threshold; The target state vector and the secondary state vector are concatenated to generate a composite query key; The target state code is obtained by querying the state code conversion table using the composite query key.

[0010] Optionally, in the fifth implementation of the first aspect of this application, the step of querying the visual encoding mapping table according to the target state code to obtain the corresponding visual driving instruction, and driving the visualization display layer to display based on the visual driving instruction, includes: The corresponding visual driving parameter set is extracted from the visual encoding mapping table according to the target state encoding. The static display parameters and dynamic timing parameters of the vision driving parameter set are combined to generate a vision driving instruction sequence; The visual driving instructions are parsed sequentially according to the system clock, driving the physical display unit of the visualization display layer to perform dynamic display.

[0011] Optionally, in a sixth implementation of the first aspect of this application, the method further includes: Obtain the first state identifier sequence and the second state identifier sequence generated by the industrial communication module within a preset historical period; Based on the first state identifier sequence and the second state identifier sequence, the rate of change of each state identifier within adjacent time windows is calculated, and abnormal time points where the rate of change exceeds a set acceleration threshold are determined. The fusion state vector corresponding to the abnormal time point is associated with the target state code to generate an abnormal pattern feature vector, and it is detected whether a new target state code is generated within a preset time after the appearance of the abnormal pattern feature vector. If a new target state code is generated within a preset time period, the abnormal pattern feature vector is stored in the prediction knowledge base. During the real-time operation of the industrial communication module, the currently generated fusion state vector is matched with the abnormal pattern feature vector of the prediction knowledge base; If a match is successful, when the driver displays the visualization layer, a warning message corresponding to the abnormal pattern feature vector will be output.

[0012] A second aspect of this application provides a visualization device for the operating status of an industrial communication module. This visualization device is used to implement a method for visualizing the operating status of an industrial communication module. The visualization device for the operating status of the industrial communication module includes: The acquisition module is used to synchronously acquire digital signal characteristic data of the communication port activity status and analog physical parameter data of the internal circuit health status during the operation of the industrial communication module. The generation module is used to generate a first state identifier corresponding to the digital signal feature data and a second state identifier corresponding to the analog physical parameter data according to a preset state mapping rule. The analysis module is used to perform fusion analysis on the first state identifier and the second state identifier according to the preset state priority logic to generate the target state code; The display module is used to query the visual encoding mapping table according to the target state encoding, obtain the corresponding visual driving instruction, and drive the visualization display layer to display based on the visual driving instruction.

[0013] A third aspect of this application provides an electronic device, including a memory and a processor, wherein the processor is configured to execute a computer program stored in the memory, and when the processor executes the computer program, it implements the steps in the visualization method for the working status of an industrial communication module provided in the first aspect of this application.

[0014] The fourth aspect of this application provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements the steps in the visualization method for the working status of an industrial communication module provided in the first aspect of this application.

[0015] In summary, the visualization method and apparatus for the working status of an industrial communication module provided in this application synchronously collects digital signal feature data of the communication port activity status and analog physical parameter data of the internal circuit health status; generates a first status identifier corresponding to the digital signal feature data and a second status identifier corresponding to the analog physical parameter data according to preset status mapping rules; fuses and analyzes the first and second status identifiers according to preset status priority logic to generate a target status code; queries the visual encoding mapping table according to the target status code to obtain the corresponding visual driving instruction, and drives the visualization display layer to display the data based on the visual driving instruction. This application, through the joint collection, status fusion, and visual encoding mapping of communication activity status and internal health status, achieves perceptible display of the module's comprehensive operating status without the need for external tools, greatly improving the system's maintainability and operational efficiency. Attached Figure Description

[0016] Figure 1 A flowchart illustrating the method for visualizing the working status of an industrial communication module provided in an embodiment of this application; Figure 2 This is a schematic diagram illustrating the analysis of synchronization timing signals and health status provided in an embodiment of this application. Figure 3 The state fusion and display decision logic diagram provided in the embodiments of this application; Figure 4 A schematic diagram of the program module of the visualization device for the working status of the industrial communication module provided in the embodiments of this application; Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0017] To make the inventive objectives, features, and advantages of this application more apparent and understandable, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0018] To address the problem that related technologies cannot achieve visualized display of the operational status of communication modules, leading to delayed fault location and difficulties in preventative maintenance, this application provides a method for visualizing the operational status of industrial communication modules, such as... Figure 1 This is a flowchart illustrating the method for visualizing the working status of an industrial communication module provided in this embodiment. The method includes the following steps: Step 110: During the operation of the industrial communication module, simultaneously collect digital signal characteristic data of the communication port activity status and analog physical parameter data of the internal circuit health status.

[0019] Specifically, during the operation of the industrial communication module, the digital signals at the communication port are monitored in real time by the module's internal signal acquisition unit. The acquired data includes characteristics such as voltage level changes, signal frequency, and signal duration. These characteristics directly reflect whether the communication link is active, idle, or in an abnormal state. Simultaneously, the health status of the internal circuitry is characterized by periodic sampling of key voltage and temperature points, with the data sourced from the module's internal analog-to-digital conversion unit. By acquiring both types of data within the same timescale, the comparability between communication status information and hardware health information is ensured, avoiding misjudgments based on only a single dimension of information.

[0020] Step 120: Generate a first state identifier corresponding to the digital signal feature data and a second state identifier corresponding to the analog physical parameter data according to the preset state mapping rules.

[0021] Specifically, after entering the mapping stage, digital signal characteristic data is compared and analyzed against a pre-defined communication activity reference range. For example, it checks whether the signal frequency is within the normal range and whether the signal rhythm remains stable, thus transforming continuously changing data into discrete and distinct communication status identifiers. Simultaneously, analog physical parameter data is compared with corresponding nominal values ​​to determine the degree of deviation, and a status identifier reflecting the hardware's health status is generated based on the level of deviation. These status mapping rules transform continuously changing raw data into a finite and distinguishable form of status expression, enabling complex operational information to be recognized and used by the logic processing unit in a structured manner, thereby reducing the complexity of the status determination process.

[0022] Step 130: Perform a fusion analysis on the first state identifier and the second state identifier according to the preset state priority logic to generate the target state code.

[0023] Specifically, after obtaining the first and second state identifiers, the two types of state information are fused and analyzed according to a preset state priority logic. This priority logic is used to coordinate states from different sources and of different importance, and by comparing the levels or severity of each state, the comprehensive state result that should be given priority at the current moment is determined. Through this fusion process, multiple possible coexisting situations, such as communication anomalies and hardware anomalies, can be reasonably adjudicated, generating a target state code that represents the overall operating status of the industrial communication module, thereby avoiding a situation where a single state information dominates the display and obscures more critical issues.

[0024] Step 140: Query the visual encoding mapping table according to the target state encoding to obtain the corresponding visual driving instruction, and drive the visualization display layer to display based on the visual driving instruction.

[0025] Specifically, after generating the target state code, a pre-established visual code mapping table is consulted to convert the abstract state code into visual driving instructions that can be used to drive the display device. This mapping table defines the correspondence between state codes and display parameters, enabling different operating states to be presented through color, brightness, or time variations. Based on the obtained visual driving instructions, the visualization display layer is controlled, so that the current operating status of the industrial communication module is presented intuitively on the module surface or display interface. This allows maintenance personnel to quickly obtain module operating information without the need for external tools and make judgments accordingly.

[0026] In one optional implementation of this embodiment, the step of synchronously acquiring digital signal characteristic data of the communication port activity status and analog physical parameter data of the internal circuit health status includes: continuously sampling the level signal of the communication port through the signal acquisition unit of the industrial communication module, and performing statistical analysis and time interval calculation on the rising and falling edges in the sampling sequence to generate digital signal characteristic data; and periodically acquiring analog voltage and temperature signals reflecting the health status of the internal circuit through the analog-to-digital conversion unit of the industrial communication module to generate analog physical parameter data.

[0027] In this embodiment, during the operation of the industrial communication module, the signal acquisition unit is directly connected to the physical pins of the communication port to sense changes in the port level over time. The level signal refers to the switching state of the communication port between logic high and logic low levels, corresponding to the data bit transmission behavior in the communication protocol. Continuous sampling refers to the signal acquisition unit reading the current port level state at fixed time intervals, forming a sampling sequence arranged in chronological order. By comparing adjacent sample values ​​in this sampling sequence, a rise edge is determined when the level changes from low to high, and a fall edge is determined when it changes from high to low. The number of rise and fall edges reflects the activity level of the communication signal, while the time interval between adjacent rise or fall edges reflects the stability of the signal rhythm. For example, in a communication module in an industrial field, when the controller continuously sends data to field devices, dense and relatively evenly spaced level changes will be detected in the sampling sequence within a short period, thus forming digital signal feature data with clear statistical characteristics. Simultaneously, the analog-to-digital conversion unit converts continuously changing analog quantities into processable digital quantities. The analog voltage signal originates from a key power supply node inside the module, and the temperature signal originates from a temperature sensing element arranged on the circuit board. Analog voltage signals reflect whether the power supply status is within acceptable limits, while temperature signals reflect the thermal state changes of the module under load. Periodic acquisition refers to the analog-to-digital converter sampling these analog signals at preset time intervals, enabling the voltage and temperature values ​​at different points in time to form a continuous parameter record. For example, in the same industrial communication module, when the communication port maintains high-frequency data transmission for a long time, the temperature signal acquired by the analog-to-digital converter may show a gradually increasing value, while the voltage signal remains within a relatively stable range. The resulting analog physical parameter data can correspond to the aforementioned digital signal characteristic data in time.

[0028] In one optional implementation of this embodiment, the steps of generating a first state identifier corresponding to digital signal feature data and a second state identifier corresponding to analog physical parameter data according to a preset state mapping rule include: performing time-series analysis on the digital signal feature data to determine the number of valid signal pulses conforming to the communication protocol specifications within a preset statistical time window; generating a first state identifier based on the comparison result of the number of valid signal pulses with a preset normal communication activity threshold range and a stability index of the interval between adjacent pulses; performing a multi-dimensional health assessment on the analog physical parameter data to determine the percentage deviation of the average value of each dimension of physical parameter within the sliding time window relative to a preset nominal value; and generating a second state identifier based on the parameter deviation level mapping corresponding to the percentage deviation.

[0029] In this embodiment, as Figure 2As shown, after obtaining the digital signal characteristic data, time-series analysis is performed to understand the true working state of the communication port from a time perspective. Time-series analysis refers to arranging and observing the pulses formed by level changes according to the order in which the signals occur, and processing them centrally within a preset statistical time window. A statistical time window is a fixed-length time interval; for example, during continuous operation of an industrial communication module, several consecutive milliseconds can be selected as an analysis interval to determine whether there are signal activities that meet the requirements of the communication protocol within that time period. The communication protocol specification has clear constraints on the width, interval, and arrangement order of signal pulses. Only when the pulse duration and the interval between adjacent pulses fall within the allowable range are they considered valid signal pulses. By combining and judging the rising and falling edges obtained from sampling, complete signal pulses can be identified, and the number of pulses that meet the specification conditions within the time window can be counted, thereby eliminating invalid changes caused by interference or occasional jitter. After obtaining the number of valid signal pulses, this number is compared with a preset normal communication activity threshold range. The normal communication activity threshold range is a range of quantities determined based on the communication port design rate and application scenario, used to describe the pulse density that should occur when communication is in a stable operating state. Simultaneously, the stability of the time interval between adjacent pulses needs to be assessed. Time interval stability refers to whether the time difference between adjacent effective pulses remains within a small fluctuation range within the statistical window. When the number of pulses is within the threshold range and the time interval changes smoothly, the communication activity can be determined to be in a stable state; if the number of pulses deviates significantly from the threshold range, or the time interval frequently lengthens or compresses, it indicates that there is an anomaly in the communication. Based on the comprehensive judgment of the above two aspects, a first state identifier is generated to describe the current working status of the communication port. For example, in a communication module in an industrial site, when the control system periodically issues control commands, a stable number of signal pulses with uniform intervals can be detected within the statistical window, thereby generating a first state identifier indicating normal communication activity. At the same time, the processing of simulated physical parameter data focuses on reflecting the operational health status of the internal circuits of the industrial communication module. Multi-dimensional health assessment refers to the simultaneous analysis of multiple physical parameters, including key indicators such as power supply voltage and operating temperature. A sliding time window refers to a data interval that is continuously updated over time to smooth out the impact of instantaneous fluctuations. Within the sliding time window, the sampled values ​​of each physical parameter are accumulated and the average value is calculated. This average value is used to reflect the overall level of the parameter over a period of time. Preset nominal values ​​refer to the ideal operating values ​​determined during the module's design phase, such as the rated supply voltage or permissible temperature reference. By comparing the average value within a sliding time window with the corresponding nominal value, a percentage deviation can be obtained, which quantifies the degree to which the parameter deviates from its normal state. When the deviation is within a small range, it indicates that the internal circuitry is operating smoothly; when the deviation gradually increases, it indicates a potential risk.Based on the range of percentage deviation, it is mapped to different parameter deviation levels, and a second state identifier is generated accordingly. For example, in the scenario where the same industrial communication module is running under continuous high load, the average value of the temperature parameter increases significantly relative to the nominal value, while the voltage parameter remains stable. At this time, the generated second state identifier can accurately reflect the changes in the internal thermal state.

[0030] In one optional implementation of this embodiment, the step of fusing and analyzing the first state identifier and the second state identifier according to a preset state priority logic to generate a target state code includes: parsing the first state identifier and the second state identifier into state vectors respectively; weighting and superimposing the state vector corresponding to the first state identifier and the state vector corresponding to the second state identifier based on a preset weight matrix to generate a fused state vector; determining whether there is a target state vector in the fused state vector with a fault level value not lower than a first alarm threshold; if there is a target state vector, querying the state code conversion table according to the number of target state vectors to obtain the target state code.

[0031] In this embodiment, as Figure 3As shown, after obtaining the first and second state identifiers, a unified expression for both types of state identifiers is needed. A state vector is an expression that transforms state information into an ordered set of values, where each position corresponds to a state dimension, and the value at that position represents the state level under that dimension. When parsing the first state identifier, information such as communication activity status and communication anomaly level can be mapped to different positions in the state vector according to a predefined correspondence. When parsing the second state identifier, health-related information such as voltage deviation level and temperature deviation level is mapped to the corresponding positions in the state vector. In this way, state identifiers, which originally existed in the form of symbols or levels, are converted into state vectors with a unified structure and clear positional meaning. After completing the state vector parsing, a unified weighting of state information from different sources is required. A preset weight matrix is ​​used to describe the relative importance of different state dimensions in the comprehensive judgment; its essence is a set of weight coefficients that correspond one-to-one with the dimensions of the state vector. By performing numerical correspondence operations between the state vectors corresponding to the first and second state identifiers and the weight matrix, the communication state and health state exhibit different degrees of influence during the fusion process. Subsequently, the two weighted state vectors are numerically superimposed at corresponding positions to form a fused state vector. Each value in the fused state vector reflects the overall performance of a certain state dimension at the current moment after weight adjustment. For example, in a communication module in an industrial field, when an abnormal pulse occurs at the communication port and the internal temperature rises slightly, the weighted fused state vector can simultaneously show high values ​​in both the communication anomaly dimension and the temperature dimension, thus reflecting the existence of a composite state. After generating the fused state vector, the state level of each dimension needs to be judged to identify whether there are any states requiring special attention. The fault level value is a numerical expression used to represent the severity of the state, while the first alarm threshold is used to distinguish between general states and states requiring immediate alerts. When the fault level value corresponding to a certain dimension in the fused state vector is not lower than the first alarm threshold, it can be determined that a target state vector exists. This target state vector is not a newly generated vector, but rather refers to the set of state dimensions in the fused state vector that meet the alarm conditions, used to indicate the most risky or most alertable source of the current system. In the aforementioned industrial communication module application scenario, when the fault level value of the communication anomaly dimension exceeds the threshold, while the temperature dimension has not yet exceeded the threshold, the target state vector primarily points to communication-related states. After confirming the existence of the target state vector, it needs to be converted into a unified code that can be used for display. As shown in Table 1, the state code conversion table is a pre-established correspondence table used to map the number of target state vectors and their combinations to unique target state codes. This conversion process obtains the target state code by statistically analyzing the number of state dimensions that meet the alarm conditions in the fused state vectors and, in conjunction with their respective types, searching for the corresponding entry in the state code conversion table.For example, in the same industrial communication module, when an alarm is triggered only by a communication anomaly, the corresponding generated target status code is related to the communication fault; when a communication anomaly and a temperature anomaly are triggered simultaneously, a target status code reflecting both anomalies is generated through a conversion table, providing a clear and unified status expression for subsequent visualization.

[0032] Table 1: State Coding Transition Table In an optional implementation of this embodiment, after determining whether there is a target state vector in the fused state vector whose fault level value exceeds a preset alarm threshold, the method further includes: scanning other state vectors in the fused state vector besides the target state vector to determine secondary state vectors whose fault level value is lower than a first alarm threshold and higher than a second alarm threshold; concatenating the target state vector with the secondary state vector to generate a composite query key; and querying the state code conversion table according to the composite query key to obtain the target state code.

[0033] In this embodiment, as Figure 3As shown, after generating the fused state vector and identifying the target state vector, it is necessary to further analyze the remaining state information in the fused state vector that has not reached the main alarm condition, in order to more comprehensively reflect the operating status of the industrial communication module. Scanning the fused state vector refers to reading and judging the fault level value corresponding to each state dimension one by one according to the arrangement order of each dimension in the state vector. The second alarm threshold is used to define the boundary between minor states and negligible states, while the first alarm threshold is used to define the main states that need to be highlighted. When the fault level value of a certain state dimension is lower than the first alarm threshold and higher than the second alarm threshold, the state has neither reached the highest risk level nor deviated significantly from the normal range, and is therefore judged as a minor state vector. Through this judgment process, the ability to describe potential risks can be preserved without weakening the main alarm information. In the specific application scenario of the industrial communication module, for example, when the module is running under continuous communication load, the communication port may have triggered the main alarm, while the internal temperature, although not yet reaching the main alarm condition, has a fault level value that is significantly higher than the normal range. Through the aforementioned scanning process, communication-related states are identified as target state vectors, while temperature-related states are identified as secondary state vectors, enabling the system to simultaneously perceive the existence of primary and secondary risks. This differentiation method avoids focusing on a single anomaly while ignoring other progressively evolving issues, making the state representation closer to the actual operating state. After determining the target and secondary state vectors, they need to be combined to form a unified identifier that reflects the state correlation. Concatenation refers to combining the identifier information of the target state vector with the identifier information of the secondary state vector in a preset order to form a composite query key. This composite query key can be formed by connecting the state number corresponding to the target state vector and the state number corresponding to the secondary state vector according to a fixed rule, so that it contains both primary and secondary state information. In this way, the composite query key not only expresses the most important source of the current anomaly but also retains the description of auxiliary states, thus forming a more distinctive state representation. After forming the composite query key, the state encoding conversion table is queried using this composite query key. The state code conversion table maintains the correspondence between different state combinations and target state codes. Its content is configured during the design phase according to the application requirements of the industrial communication module. When a composite query key is used, the system can locate the entry matching the current state combination in the conversion table based on the key value and read the corresponding target state code. In the aforementioned industrial communication module application scenario, when communication anomaly is the primary state and high temperature is the secondary state, the composite query key can point to a target state code specifically used to describe "communication anomaly as the primary state, accompanied by secondary temperature anomaly."The target status code is then used to drive the subsequent display logic, so that the display results not only highlight the main alarms, but also imply secondary status information, thereby providing maintenance personnel with a more hierarchical and valuable status presentation.

[0034] In one optional implementation of this embodiment, the step of querying the visual encoding mapping table according to the target state code to obtain the corresponding visual driving instruction, and driving the visualization display layer to display based on the visual driving instruction, includes: extracting the corresponding visual driving parameter set from the visual encoding mapping table according to the target state code; synthesizing the static display parameters and dynamic timing parameters of the visual driving parameter set to generate a visual driving instruction sequence; and parsing the visual driving instructions sequentially according to the system clock to drive the physical display unit of the visualization display layer to perform dynamic display.

[0035] In this embodiment, after obtaining the target state code characterizing the overall operating state of the industrial communication module, this abstract code needs to be transformed into control information that can directly affect the display hardware. A visual encoding mapping table is used to establish the correspondence between the target state code and the visual representation. Its contents are stored in the form of entries, each associated with a set of visual driving parameters. The visual driving parameter set is a structured description of the display behavior, including static display parameters used to determine the display appearance and dynamic timing parameters used to describe the display's characteristics over time. By using the target state code as an index and matching it in the visual encoding mapping table, the visual driving parameter set corresponding to the current state can be extracted, thus avoiding re-judgment of the state during the display phase and making the display logic and state analysis logic independent. Static display parameters are used to define the basic appearance attributes presented by the display unit at a certain moment, such as emission color, brightness level, or display area position. These parameters remain unchanged during the display cycle and are used to convey the basic attributes of the state. Dynamic timing parameters are used to describe the rhythmic relationship of the display appearance changing over time, such as the duration of on / off states, repetition cycle, or change sequence, to enhance the recognizability of the state. Synthesizing static display parameters with dynamic timing parameters refers to filling the corresponding time segments with static display parameters based on the time sequence constraints imposed by the dynamic timing parameters, thereby forming a time-ordered sequence of visual driving instructions. Each instruction in this sequence contains explicit display content and its effective duration, enabling precise description of display behavior on the timeline. The system clock provides a unified time reference, and its output timing signal is used to trigger the parsing process of the visual driving instruction sequence. Sequential parsing means that, driven by the system clock, visual driving instructions are read and executed one by one according to the pre-set order and duration in the instruction sequence. Whenever the system clock reaches the time node corresponding to a certain instruction, a control signal matching that instruction is sent to the physical display unit of the visualization display layer, causing the display unit to present the corresponding display state. When the duration of a certain instruction ends, the system clock triggers the parsing and execution of the next instruction, thus forming a continuous dynamic display effect. In practical applications of industrial communication modules, for example, when the module simultaneously detects a communication anomaly accompanied by an excessively high internal temperature, the corresponding target state code can be associated with a set of visual driving parameters containing red display and periodic flashing features in the visual encoding mapping table. Static display parameters determine the red light emitted by the display unit, while dynamic timing parameters specify the duration of the light-on and light-off cycles. The synthesized visual drive command sequence is executed sequentially under the control of the system clock, causing the display unit to repeatedly light up and off at a fixed rhythm. This presents the status information in an intuitive and easily distinguishable manner, allowing maintenance personnel to accurately perceive the module's current operating status without needing to connect external devices.

[0036] Table 2: Visual Encoding Map Table In one optional implementation of this embodiment, a first state identifier sequence and a second state identifier sequence generated by the industrial communication module within a preset historical period are obtained; based on the first state identifier sequence and the second state identifier sequence, the rate of change of each state identifier within an adjacent time window is calculated, and abnormal time points where the rate of change exceeds a set acceleration threshold are determined; the fused state vector corresponding to the abnormal time point is associated with the target state code to generate an abnormal pattern feature vector, and it is detected whether a new target state code is generated within a preset time period after the appearance of the abnormal pattern feature vector; if a new target state code is generated within the preset time period, the abnormal pattern feature vector is stored in the prediction knowledge base; during the real-time operation of the industrial communication module, the currently generated fused state vector is matched with the abnormal pattern feature vector in the prediction knowledge base; if the match is successful, when the visualization display layer is driven to display, a warning prompt message corresponding to the abnormal pattern feature vector is output.

[0037] In this embodiment, during the continuous operation of the industrial communication module, the first and second state identifier sequences are generated sequentially and stored in the module's internal state record area. A preset historical period is used to limit the time range for backtracking analysis, such as limiting it to the most recent continuous operating time, thereby ensuring that the data involved in the analysis is both continuous and reflects recent operating characteristics. By reading the stored first and second state identifier sequences within this historical period, the complete trajectory of the communication state change process and the internal health state change process on the time axis can be obtained. After obtaining the above two types of state identifier sequences, it is necessary to measure their changes within adjacent time windows. Adjacent time windows refer to continuous time intervals divided into fixed lengths within the historical period, with each interval corresponding to a set of state identifier values. The rate of change is used to describe the magnitude of the numerical change of the same state identifier in two adjacent time windows. It is calculated as the difference between the state level of the later time window and the state level of the earlier time window, combined with the time window length for normalization. An acceleration threshold is used to limit the judgment criteria for the rate of change. When the rate of change exceeds this threshold, it indicates that the state evolution speed has significantly accelerated and has deviated from the stable change trajectory. By performing the above calculations on the first and second state identifier sequences respectively, abnormal time points where communication or health status rapidly deteriorates or fluctuates can be identified. For example, in a communication module at an industrial site, the communication port status rapidly develops from a slight abnormality to a severe abnormality within a short period of time. The rate of change corresponding to this process exceeds the acceleration threshold, thus being marked as an abnormal time point. After identifying the abnormal time point, it is necessary to associate the fused state vector corresponding to that time point with the target state code generated at that time. The fused state vector reflects the combined performance of the communication and health status at that moment, while the target state code summarizes the main state information presented externally at that moment. By combining the two, an abnormal pattern feature vector is formed, which describes the overall state structure before and after the occurrence of the abnormal state. Subsequently, the state evolution within a preset time period after the occurrence of the abnormal pattern feature vector is tracked to determine whether a new target state code is generated within this time range. If a new target state code appears within this time range, it indicates that there is a clear correlation between the abnormal pattern and subsequent state changes, and it has value as a predictive reference. Once the correlation between the abnormal pattern feature vector and the subsequent target state code is confirmed, the abnormal pattern feature vector is stored in the prediction knowledge base. The predictive knowledge base is used to centrally store the abnormal patterns and their evolution results that have been verified in the historical operation process. Its content is continuously accumulated as the module runs, enabling the module to have the ability to make state warnings based on its own historical experience.During the real-time operation of the industrial communication module, the currently generated fused state vector is continuously compared with the anomaly pattern feature vector in the prediction knowledge base. This comparison process determines whether the current state structure matches historically recorded anomaly patterns. When the comparison result shows that the current fused state vector successfully matches a certain anomaly pattern feature vector in the prediction knowledge base, it can be determined that the current state may continue to evolve along the previous anomaly path. At this time, while driving the visualization display layer to display the state, a warning message corresponding to the anomaly pattern feature vector is output. For example, in the aforementioned industrial communication module scenario, when the system identifies that the fused state vector of rapidly deteriorating communication status and gradually rising temperature matches the anomaly pattern in the prediction knowledge base, a warning message can be presented on the display layer in addition to the current state indication, so that maintenance personnel can receive a clear reminder before a serious fault occurs, thereby buying time for on-site handling.

[0038] According to the visualization method for the working status of an industrial communication module provided in this application, digital signal feature data of the communication port activity status and analog physical parameter data of the internal circuit health status are collected simultaneously. A first status identifier corresponding to the digital signal feature data and a second status identifier corresponding to the analog physical parameter data are generated according to preset status mapping rules. The first and second status identifiers are fused and analyzed according to preset status priority logic to generate a target status code. The visual code mapping table is queried based on the target status code to obtain the corresponding visual driving instruction, and the visualization display layer is driven to display the data based on the visual driving instruction. This application, through the joint collection, status fusion, and visual code mapping of communication activity status and internal health status, achieves a perceptible display of the module's comprehensive operating status without the need for external tools, greatly improving the maintainability and operational efficiency of the system.

[0039] Figure 4 This application provides a visualization device for the working status of an industrial communication module. This visualization device can be used to implement the visualization method for the working status of the industrial communication module in the foregoing embodiments. Figure 4 As shown, the visualization device for the working status of this industrial communication module mainly includes: The acquisition module 10 is used to synchronously acquire digital signal characteristic data of the communication port activity status and analog physical parameter data of the internal circuit health status during the operation of the industrial communication module. The generation module 20 is used to generate a first state identifier corresponding to the digital signal feature data and a second state identifier corresponding to the analog physical parameter data according to a preset state mapping rule. Analysis module 30 is used to perform fusion analysis on the first state identifier and the second state identifier according to the preset state priority logic to generate the target state code; The display module 40 is used to query the visual encoding mapping table according to the target state encoding, obtain the corresponding visual driving instructions, and drive the visualization display layer to display based on the visual driving instructions.

[0040] In one optional implementation of this embodiment, the acquisition module is specifically used to: continuously sample the level signal of the communication port through the signal acquisition unit of the industrial communication module, and perform statistical analysis and time interval calculation on the rising and falling edges in the sampling sequence to generate digital signal feature data; and periodically acquire the analog voltage signal and temperature signal reflecting the health status of the internal circuit through the analog-to-digital conversion unit of the industrial communication module to generate analog physical parameter data.

[0041] In one optional implementation of this embodiment, the generation module is specifically used for: performing time-series analysis on digital signal characteristic data to determine the number of valid signal pulses conforming to the communication protocol specifications within a preset statistical time window; generating a first state identifier based on the comparison result of the number of valid signal pulses with a preset normal communication activity threshold range and the stability index of the interval between adjacent pulses; performing multi-dimensional health assessment on simulated physical parameter data to determine the percentage deviation of the average value of each dimension of physical parameters within the sliding time window relative to a preset nominal value; and generating a second state identifier based on the parameter deviation level mapping corresponding to the percentage deviation.

[0042] In an optional implementation of this embodiment, the analysis module is specifically used to: parse the first state identifier and the second state identifier into state vectors respectively; weight and superimpose the state vector corresponding to the first state identifier and the state vector corresponding to the second state identifier based on a preset weight matrix to generate a fused state vector; determine whether there is a target state vector in the fused state vector whose fault level value is not lower than the first alarm threshold; if there is a target state vector, query the state code conversion table according to the number of target state vectors to obtain the target state code.

[0043] In an optional implementation of this embodiment, the analysis module is further configured to: scan other state vectors in the fused state vector besides the target state vector to determine secondary state vectors whose fault level values ​​are lower than the first alarm threshold and higher than the second alarm threshold; concatenate the target state vector with the secondary state vectors to generate a composite query key; and query the state code conversion table according to the composite query key to obtain the target state code.

[0044] In one optional implementation of this embodiment, the display module is specifically used to: extract the corresponding visual driving parameter set from the visual encoding mapping table according to the target state code; synthesize the static display parameters and dynamic timing parameters of the visual driving parameter set to generate a visual driving instruction sequence; and parse the visual driving instructions in sequence according to the system clock to drive the physical display unit of the visualization display layer to perform dynamic display.

[0045] In an optional embodiment of this example, the display module is further configured to: acquire a first state identifier sequence and a second state identifier sequence generated by the industrial communication module within a preset historical period; calculate the rate of change of each state identifier within an adjacent time window based on the first state identifier sequence and the second state identifier sequence, and determine the abnormal time point where the rate of change exceeds a set acceleration threshold; associate the fused state vector corresponding to the abnormal time point with the target state code to generate an abnormal pattern feature vector, and detect whether a new target state code is generated within a preset time period after the occurrence of the abnormal pattern feature vector; if a new target state code is generated within the preset time period, the abnormal pattern feature vector is stored in the prediction knowledge base; during the real-time operation of the industrial communication module, the currently generated fused state vector is matched with the abnormal pattern feature vector in the prediction knowledge base; if the match is successful, when driving the visualization display layer to display, an early warning message corresponding to the abnormal pattern feature vector is output.

[0046] According to the visualization device for the working status of an industrial communication module provided in this application, digital signal feature data of the communication port activity status and analog physical parameter data of the internal circuit health status are collected simultaneously. A first status identifier corresponding to the digital signal feature data and a second status identifier corresponding to the analog physical parameter data are generated according to a preset status mapping rule. The first and second status identifiers are fused and analyzed according to a preset status priority logic to generate a target status code. The visual code mapping table is queried based on the target status code to obtain the corresponding visual driving instruction, and the visualization display layer is driven to display the data based on the visual driving instruction. This application, through the joint collection, status fusion, and visual code mapping of communication activity status and internal health status, achieves a perceptible display of the module's comprehensive operating status without the need for external tools, greatly improving the system's maintainability and operational efficiency.

[0047] According to the scheme provided in this application Figure 5 An electronic device is provided as an embodiment of this application. This electronic device can be used to implement the visualization method for the working status of the industrial communication module in the foregoing embodiments, mainly including: The system includes a memory 501, a processor 502, and a computer program 503 stored on the memory 501 and executable on the processor 502. The memory 501 and the processor 502 are communicatively connected. When the processor 502 executes the computer program 503, it implements the visualization method for the operating status of the industrial communication module in the aforementioned embodiments. The number of processors can be one or more.

[0048] Memory 501 can be high-speed random access memory (RAM) or non-volatile memory, such as disk storage. Memory 501 is used to store executable program code, and processor 502 is coupled to memory 501.

[0049] Furthermore, embodiments of this application also provide a computer-readable storage medium, which may be disposed in the electronic device described in the above embodiments, and the computer-readable storage medium may be as described above. Figure 5 The memory in the illustrated embodiment.

[0050] The computer-readable storage medium stores a computer program that, when executed by a processor, implements the visualization method for the operating status of the industrial communication module in the aforementioned embodiments. Furthermore, the computer-readable storage medium can also be a USB flash drive, external hard drive, read-only memory (ROM), RAM, magnetic disk, or optical disk, or any other medium capable of storing program code.

[0051] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0052] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0053] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for visualizing the working status of an industrial communication module, characterized in that, include: During the operation of the industrial communication module, digital signal characteristic data of the communication port activity status and analog physical parameter data of the internal circuit health status are collected synchronously. According to the preset state mapping rules, a first state identifier corresponding to the digital signal feature data and a second state identifier corresponding to the analog physical parameter data are generated respectively. The first state identifier and the second state identifier are fused and analyzed according to the preset state priority logic to generate the target state code; The visual encoding mapping table is queried according to the target state code to obtain the corresponding visual driving instruction, and the visualization display layer is driven to display based on the visual driving instruction.

2. The method for visualizing the working status of an industrial communication module according to claim 1, characterized in that, The steps of synchronously acquiring digital signal characteristic data of the communication port activity status and analog physical parameter data of the internal circuit health status include: The signal acquisition unit of the industrial communication module continuously samples the level signal of the communication port, and performs statistical analysis and time interval calculation on the rising and falling edges in the sampling sequence to generate digital signal feature data. The analog-to-digital conversion unit of the industrial communication module periodically collects analog voltage and temperature signals that reflect the health status of the internal circuits, generating analog physical parameter data.

3. The method for visualizing the working status of an industrial communication module according to claim 1, characterized in that, The step of generating a first state identifier corresponding to the digital signal feature data and a second state identifier corresponding to the analog physical parameter data according to a preset state mapping rule includes: Perform time-series analysis on the digital signal feature data to determine the number of valid signal pulses conforming to the communication protocol specifications within a preset statistical time window; A first state identifier is generated based on the comparison result between the number of effective signal pulses and the preset normal communication activity threshold range, as well as the stability index of the interval between adjacent pulses. A multi-dimensional health assessment is performed on the simulated physical parameter data to determine the percentage deviation of the average value of each physical parameter within the sliding time window relative to the preset nominal value. A second state identifier is generated based on the parameter deviation level mapping corresponding to the percentage deviation.

4. The method for visualizing the working status of an industrial communication module according to claim 1, characterized in that, The step of fusing and analyzing the first state identifier and the second state identifier according to a preset state priority logic to generate a target state code includes: The first state identifier and the second state identifier are respectively parsed into state vectors; Based on a preset weight matrix, the state vector corresponding to the first state identifier and the state vector corresponding to the second state identifier are weighted and superimposed to generate a fused state vector. Determine whether there exists a target state vector in the fused state vector whose fault level value is not lower than the first alarm threshold; If the target state vector exists, the target state code is obtained by querying the state code conversion table based on the number of target state vectors.

5. The method for visualizing the working status of an industrial communication module according to claim 4, characterized in that, After determining whether there is a target state vector in the fused state vector whose fault level value exceeds a preset alarm threshold, the method further includes: Scan the other state vectors in the fused state vectors, excluding the target state vector, to determine the secondary state vectors whose fault level value is lower than the first alarm threshold and higher than the second alarm threshold; The target state vector and the secondary state vector are concatenated to generate a composite query key; The target state code is obtained by querying the state code conversion table using the composite query key.

6. The method for visualizing the working status of an industrial communication module according to claim 1, characterized in that, The step of querying the visual encoding mapping table according to the target state code to obtain the corresponding visual driving instruction, and driving the visualization display layer to display based on the visual driving instruction, includes: The corresponding visual driving parameter set is extracted from the visual encoding mapping table according to the target state encoding. The static display parameters and dynamic timing parameters of the vision driving parameter set are combined to generate a vision driving instruction sequence; The visual driving instructions are parsed sequentially according to the system clock, driving the physical display unit of the visualization display layer to perform dynamic display.

7. The method for visualizing the working status of an industrial communication module according to claim 1, characterized in that, The method further includes: Obtain the first state identifier sequence and the second state identifier sequence generated by the industrial communication module within a preset historical period; Based on the first state identifier sequence and the second state identifier sequence, the rate of change of each state identifier within adjacent time windows is calculated, and abnormal time points where the rate of change exceeds a set acceleration threshold are determined. The fusion state vector corresponding to the abnormal time point is associated with the target state code to generate an abnormal pattern feature vector, and it is detected whether a new target state code is generated within a preset time after the appearance of the abnormal pattern feature vector. If a new target state code is generated within a preset time period, the abnormal pattern feature vector is stored in the prediction knowledge base. During the real-time operation of the industrial communication module, the currently generated fusion state vector is matched with the abnormal pattern feature vector of the prediction knowledge base; If a match is successful, when the driver displays the visualization layer, a warning message corresponding to the abnormal pattern feature vector will be output.

8. A visualization device for the working status of an industrial communication module, characterized in that, The visualization device for the working status of the industrial communication module is used to implement the visualization method for the working status of the industrial communication module as described in claim 1. The visualization device for the working status of the industrial communication module includes: The acquisition module is used to synchronously acquire digital signal characteristic data of the communication port activity status and analog physical parameter data of the internal circuit health status during the operation of the industrial communication module. The generation module is used to generate a first state identifier corresponding to the digital signal feature data and a second state identifier corresponding to the analog physical parameter data according to a preset state mapping rule. The analysis module is used to perform fusion analysis on the first state identifier and the second state identifier according to the preset state priority logic to generate the target state code; The display module is used to query the visual encoding mapping table according to the target state encoding, obtain the corresponding visual driving instruction, and drive the visualization display layer to display based on the visual driving instruction.

9. An electronic device, characterized in that, Includes memory and processor, of which: The processor is used to execute computer programs stored in the memory; When the processor executes the computer program, it implements the steps in the visualization method for the working status of the industrial communication module according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps in the visualization method for the working status of the industrial communication module according to any one of claims 1 to 7.

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