An industrial computer operation monitoring system and method based on data analysis

Abstract

The application discloses an industrial computer operation monitoring system and method based on data analysis, and relates to the technical field of operation monitoring.The application comprises a data acquisition and preprocessing module, a real-time monitoring and fault identification module, and a performance optimization module.The application collects and preprocesses industrial computer operation data through sensors and other equipment, analyzes the data in real time, and displays the state in a graphical interface;based on preset rule algorithm deep analysis, the application automatically identifies fault hidden dangers, pushes warnings, and quickly locates faults with the help of a three-dimensional visual interface combined with a factory layout diagram;the application analyzes historical data to evaluate performance trends and provide optimization suggestions;the multiple modules are cooperated to realize comprehensive monitoring, fault identification, and performance optimization, improve the operation reliability and stability of the industrial computer, and guarantee efficient and safe industrial production.

Description

Technical Field

[0001] This invention relates to the field of operation monitoring technology, and specifically to an industrial control computer operation monitoring system and method based on data analysis. Background Technology

[0002] With the rapid development of industrial information technology, industrial control computers (ICCs) are widely used in industrial scenarios, making their operation monitoring crucial. Traditional monitoring relies on manual inspections and simple threshold judgments, which are inefficient, difficult to handle complex working conditions, and unable to accurately analyze multi-source data. Modern industry has increasingly higher requirements for the reliability and real-time performance of ICCs, necessitating intelligent monitoring methods. To meet the needs of real-time monitoring, fault prediction, and optimized operation, data analysis-based monitoring systems and methods have emerged. By mining the value of data, they achieve accurate diagnosis and prediction, enabling real-time monitoring of the operating status of ICCs, promoting the advancement of monitoring towards intelligence and precision, improving industrial production efficiency and stability, and enhancing industry competitiveness.

[0003] Existing technologies, such as the invention application patent with announcement number CN116679668A, disclose an industrial control computer operation monitoring system based on data analysis. This invention addresses the industrial control computer operation monitoring system by employing a rapid diagnostic unit to diagnose faults and generate logs; an automatic maintenance unit to perform secondary testing after troubleshooting; a condition monitoring unit to generate alert signals, which the monitoring unit then uses to generate adjustment signals, which are executed by the control unit to analyze the cause of the fault; and a data retention unit to save important data based on decisions. The system achieves a closed loop of fault diagnosis, maintenance, monitoring, and data management, thereby improving the reliability of industrial control computer operation.

[0004] Based on the above solutions, it can be found that current industrial control computer operation monitoring systems and methods have limitations. Existing technologies suffer from delayed fault detection, weak automated monitoring capabilities, and an inability to capture anomalies in real time; insufficient processing of complex operating condition data makes it difficult to accurately diagnose potential faults; data is difficult to share, forming "data silos" that hinder integration and analysis; safety measures are weak, and the visualization interface is simple, making it difficult to intuitively present the operating status, affecting monitoring efficiency and decision-making accuracy; thus, they restrict the effectiveness and reliability of industrial control computer operation monitoring and cannot meet the needs of modern industry for efficient and stable monitoring. Summary of the Invention

[0005] The purpose of this invention is to provide an industrial control computer operation monitoring system and method based on data analysis, which solves the problems existing in the background technology.

[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: The first aspect of the present invention provides an industrial control computer operation monitoring system based on data analysis, including: a data acquisition and preprocessing module, which collects the operation data of all industrial control computers in the factory within a set period through various sensors and data acquisition devices, and processes them;

[0007] The real-time monitoring and fault identification module analyzes and processes the collected operating data of all industrial control computers in the factory within a set period in real time, determines whether any industrial control computer in the factory has malfunctioned, and if a certain industrial control computer malfunctions, identifies the set of fault categories of that industrial control computer; determines the fault level of the industrial control computer based on the set of fault categories, and pushes warning information to the industrial control computer operation and maintenance supervisors. At the same time, it dynamically displays the industrial control computer and its set of fault categories through a 3D visualization monitoring interface.

[0008] The performance optimization module acquires the operating data of all industrial control computers in the factory in each historical period, identifies the set of fault categories of all industrial control computers in each historical period, and classifies the inspection level of the automatic inspection robot for all fault categories in the factory.

[0009] A second aspect of the present invention provides a method for executing the data analysis-based industrial computer operation monitoring system of the present invention, comprising: S1. Data acquisition and preprocessing, collecting and processing the operation data of all industrial computers in the factory within a set period through various sensors and data acquisition devices;

[0010] S2. Real-time monitoring and fault identification: Real-time analysis and processing of the operating data of all industrial control computers in the factory within a set period is performed to determine whether any industrial control computer in the factory has malfunctioned. If an industrial control computer malfunctions, the set of fault categories for that industrial control computer is identified. The fault level of the industrial control computer is determined based on the set of fault categories, and a warning message is pushed to the industrial control computer operation and maintenance supervisor. At the same time, the industrial control computer and its set of fault categories are dynamically displayed through a 3D visualization monitoring interface.

[0011] S3. Performance optimization: Obtain the operating data of all industrial control computers in the factory in each historical period, identify the fault category set of all industrial control computers in each historical period, and classify the inspection level of the automatic inspection robot for all fault categories in the factory.

[0012] The beneficial effects of the present invention are as follows: 1. The present invention analyzes data in real time in the real-time monitoring and fault identification module, collects and analyzes data in real time, captures anomalies in a timely manner, improves the automated monitoring capability, and displays the operating status with a graphical interface, so that operators can grasp the status of the industrial control computer in a timely and intuitive manner.

[0013] 2. This invention automatically identifies potential faults in the real-time monitoring and fault identification module, and combines three-dimensional visualization to dynamically display the status and quickly locate faults, thereby improving processing efficiency and reducing downtime losses.

[0014] 3. This invention analyzes and divides the inspection frequency in the performance optimization module, provides optimization suggestions for operation and maintenance supervisors, helps to shift from passive response to proactive predictive maintenance, improves the performance and stability of industrial control computers, and extends equipment life. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the system structure connection of the present invention.

[0017] Figure 2 This is a schematic diagram of the connection of the execution method of the present invention. Detailed Implementation

[0018] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0019] Reference Figure 1 As shown, this invention provides an industrial control computer operation monitoring system based on data analysis, comprising:

[0020] The data acquisition and preprocessing module collects and processes the operating data of all industrial control computers in the factory within a set period through various sensors and data acquisition devices.

[0021] In a specific embodiment of the present invention, the step of collecting operating data of the industrial control computer within a set period and processing the collected data specifically includes:

[0022] Multi-source data acquisition is performed to obtain the time-series operating data of the industrial control computer based on sensor data and industrial control computer performance indicators. The operating data includes hardware data and software data. The hardware data includes a 3D image of the casing, fan speed, temperature of the industrial control computer's heat dissipation area, number of connection interruptions, signal transmission delay, measured equivalent series resistance, actual capacitor operating temperature, and capacitor usage time. The software data includes data transmission error rate, voltage fluctuation amplitude, memory usage rate, number of memory errors, and page swapping rate.

[0023] The collected data is processed by cleaning, removing missing values, denoising, extracting time-series features, converting formats, and normalizing to eliminate dimensional differences.

[0024] It should be noted that data cleaning includes removing noise and outliers. Missing values ​​can be filled using interpolation or mean. Noise reduction can be achieved using sliding window averaging or Kalman filtering. Extracting time-series features includes mean, variance, trend, and periodicity. Format conversion includes standardizing timestamps and units. Data normalization is also performed to eliminate differences in units. Because the units of the data in the calculation are different, the data needs to be standardized to convert some values ​​into values ​​between 0 and 1.

[0025] The real-time monitoring and fault identification module analyzes and processes the collected operating data of all industrial control computers in the factory within a set period in real time, determines whether any industrial control computer in the factory has a fault, and if a certain industrial control computer has a fault, identifies the set of fault categories of the industrial control computer; determines the fault level of the industrial control computer based on the set of fault categories, and pushes warning information to the industrial control computer operation and maintenance supervisors. At the same time, it dynamically displays the industrial control computer and its set of fault categories through a 3D visualization monitoring interface.

[0026] In a specific embodiment of the present invention, the method for determining whether all industrial control computers in the factory have malfunctioned, and if a certain industrial control computer has malfunctioned, identifying the set of malfunction categories of that industrial control computer, is as follows:

[0027] B1. Shell Deformation Fault: Compare the acquired 3D shell images with the original 3D shell images stored in the database to obtain the overlap volume between the current 3D shell image and the original 3D shell image, and substitute it into the tilt deformation judgment model. , This is the serial number of the industrial control computer. , It is any integer greater than 2. Number each measurement. , Let be any integer greater than 2, where Let be the overlap volume between the shell image measured by the nth industrial control computer in the i-th measurement and the original 3D image. Let the volume of the original 3D image of the casing be the volume of the nth industrial control computer during the i-th measurement. If the overlapping volume ratio of the outer casing of a certain industrial control computer is... If the deformation of the outer shell of the device is K, then K is the minimum volume ratio between the outer shell image measured by the industrial control computer and the original three-dimensional image.

[0028] B2. Overheating failure. ,in This is the value used to determine fan operation. The measured fan speed is the value of the nth industrial computer during the i-th measurement. For the fan's rated speed, when The fan malfunctioned. The administrator sets the parameters based on the hardware specifications; ,in Let be the measured temperature of the heat dissipation area of ​​the nth industrial computer during the i-th measurement. This is the set normal operating temperature for the industrial computer's heat dissipation area. This is the critical offset for temperature anomalies, when At that time, the temperature of the industrial computer's heat dissipation area was abnormal; when Industrial computer cooling system malfunction. The logical AND symbol;

[0029] B3. Cable fault, calculate the connector fault value. ,in Let be the monitoring data transmission error rate of the nth industrial control computer during the i-th measurement. To allow for a low data transmission error rate, Let i be the number of connection interruptions during the i-th measurement of the nth industrial control computer. To allow for a certain number of connection interruptions, For signal transmission delay duration, To allow for signal transmission delay duration, For voltage fluctuation anomalies and , The maximum threshold for voltage fluctuation. The weighting coefficients for monitoring data transmission error rate, connection interruption count, signal transmission delay duration, and voltage fluctuation amplitude are respectively... The average value of multiple measurements , At that time, the connector malfunctioned. The set fault threshold;

[0030] B4. Memory Failure, Calculate Memory Failure Score ,in Score the memory usage of the nth industrial computer in the i-th measurement. , Let i be the actual memory usage rate of the nth industrial computer in the i-th measurement. The maximum threshold for memory usage. Score the memory error of the nth industrial computer in the i-th measurement and , Number of memory errors This is the maximum threshold for the number of memory errors. Let i be the page swap anomaly judgment value measured by the nth industrial control computer in the i-th measurement, and , This represents the actual page swapping rate. This is the maximum threshold for page swapping rate. The weighting coefficients for memory utilization, number of memory errors, and page swapping rate are respectively. , At that time, memory failure occurred. The set memory failure threshold;

[0031] B5. Capacitor Failure: Scoring the degree of aging of motherboard capacitors. ,in Score the degree of capacitor aging for the nth industrial control computer in the i-th measurement. To measure the equivalent series resistance, The initial equivalent series resistance is given by an exponent of 1.5, reflecting the accelerating effect of the nonlinear growth of ESR. Let be the actual operating temperature of the capacitor measured by the nth industrial computer in the i-th measurement. Capacitor rated temperature As a temperature acceleration factor, The duration of capacitor usage for the i-th measurement by the nth industrial control computer. For capacitor design life, For time aging weighting coefficient, when At that time, the motherboard capacitors were healthy and showed no signs of aging. At that time, the motherboard capacitors had a slight aging failure; when At that time, the motherboard capacitors were completely aged. Specifically, this refers to the maximum and minimum values ​​of the motherboard capacitor aging score.

[0032] It should be noted that the formula for scoring the aging degree of motherboard capacitors includes... This indicates the nonlinear degradation of the capacitor, specifically the aging growth trend of the capacitor's equivalent series resistance (ESR). This trend is not nonlinear but rather shows an accelerated degradation trend. The index 1.5 is derived from fitting data from accelerated aging tests (105℃ / 2000 hours), which revealed that the slope of the ESR growth curve is approximately equal to 1.5. This indicates temperature stress; capacitors age faster in high-temperature environments. This indicates the cumulative operating time of the capacitor. Aging accumulates at a uniform rate within the designed lifespan, and the risk increases linearly after the design lifespan is exceeded.

[0033] In a specific embodiment of the present invention, determining the fault level of the industrial control computer based on the set of fault categories specifically includes:

[0034] ,in Score the fault level of the nth industrial control computer. The weight for each fault type can be adjusted as needed, and , Scoring for each fault type, ,in To allow the industrial control computer to measure the deviation between the shell image and the original 3D image, , , , The fault level is Based on industry experience, we recommend... .

[0035] In a specific embodiment of the present invention, the step of pushing warning information to the industrial control computer maintenance and supervision personnel, and simultaneously dynamically displaying the industrial control computer and its fault category set through a three-dimensional visualization monitoring interface, specifically includes:

[0036] Notifications are triggered via the Drools rules engine, and can be categorized into sound alarms, pop-up alarms, and SMS or email alarms. When an industrial control computer malfunctions, a specific sound is played to alert maintenance and monitoring personnel. Simultaneously, monitoring images are used to detect whether maintenance and monitoring personnel are in the monitoring room. If so, an alarm window pops up on the graphical interface, displaying alarm information, including alarm time, alarm type, and fault description, to alert the monitoring personnel. If not, the alarm information can be sent to relevant personnel via SMS or email.

[0037] All alarm information is recorded and stored in the database, and an alarm record query function is provided. Operation and maintenance personnel can query the alarm records according to the time range, fault level, and fault type.

[0038] The anomaly identification module performs in-depth analysis of operational data based on preset rules and algorithms, automatically identifies potential fault hazards, and pushes warning information through the system; through a 3D visualization monitoring interface, combined with the factory layout diagram, it dynamically displays the status of each industrial control computer and quickly locates the fault location.

[0039] In a specific embodiment of the present invention, the automatic identification of potential fault hazards specifically includes:

[0040] B1. Degree of shell deformation: The acquired 3D image of the shell is compared with the original 3D image of the shell stored in the database to obtain the overlap volume between the current 3D image and the original 3D image, and then substituted into the tilt deformation judgment model. ,in Let be the overlap volume between the shell image of the p-th device and the original 3D image. Let p be the volume of the original 3D image of the p-th device casing; if the overlap volume ratio of the casings of a certain device is... If this happens, the outer casing of the device will deform.

[0041] B2. Industrial computer cooling system , The number of measurements is assigned. , Let be any integer greater than 2, where This is the actual measured fan speed. For the fan's rated speed, when The fan malfunctioned. The administrator sets the parameters based on the hardware specifications; ,in The measured temperature of the industrial computer's heat dissipation area. This is the set normal operating temperature for the industrial computer's heat dissipation area. This is the critical offset for temperature anomalies, when At that time, the temperature of the industrial computer's heat dissipation area was abnormal; when The industrial computer's cooling system is malfunctioning. It is a logical AND symbol.

[0042] B3. Connector, calculate connector fault values. ,in To monitor the data transmission error rate, This is the maximum normal data transmission error rate. This is the normal value for data transmission error rate. For the number of connection interruptions, This represents the maximum number of connection interruptions. For signal transmission delay duration, This represents the maximum value of the signal transmission delay. This is the normal value for signal transmission delay. For voltage fluctuation amplitude and , This represents the actual voltage fluctuation range. This represents the maximum value of the voltage fluctuation amplitude. The weighting coefficients for monitoring data transmission error rate, connection interruption count, signal transmission delay duration, and voltage fluctuation amplitude are respectively... The average value of multiple measurements , At that time, the connector malfunctioned. The set fault threshold.

[0043] B4. Memory Failure, Calculate Memory Failure Score ,in This represents the actual memory usage rate. This represents the maximum value for normal memory usage. This is a warning value for memory usage. ,and , The number of memory errors and , This represents the maximum number of memory errors. For page swapping rate and , This represents the maximum page swapping rate. The weighting coefficients for memory utilization, number of memory errors, and page swapping rate are respectively. .

[0044] B5. Motherboard capacitor aging: This section rates the degree of aging of the motherboard capacitors. , The number of measurements is assigned. , Let be any integer greater than 2, where To measure the equivalent series resistance, The initial equivalent series resistance is given by an exponent of 1.5, reflecting the accelerating effect of the nonlinear growth of ESR. This refers to the actual operating temperature of the capacitor. Capacitor rated temperature As a temperature acceleration factor, The capacitor's usage time. For capacitor design life, For time aging weighting coefficient, when When the motherboard capacitors are healthy, maintenance costs are low and no intervention is required; when At this time, it is necessary to shorten the testing cycle and optimize heat dissipation or load; when If this happens, it must be replaced immediately to avoid damaging other components. Specifically, this refers to the maximum and minimum values ​​of the motherboard capacitor aging score.

[0045] In a specific embodiment of the present invention, the push notification information specifically includes:

[0046] Notifications are triggered via the Drools rules engine, and can be categorized into sound alarms, pop-up alarms, and SMS or email alarms. When an alarm needs to be triggered to alert operators, a specific sound is played to remind the user. Simultaneously, the system monitors whether there are personnel in the monitoring room. If so, an alarm window pops up on the graphical interface, displaying alarm information, including alarm time, alarm type, and fault description, to alert the monitoring personnel. If not, the alarm information can be sent to relevant personnel via SMS or email.

[0047] All alarm information is recorded and stored in the database, and an alarm record query function is provided. Users can query according to time range, alarm level, alarm type and other conditions to quickly locate and analyze historical alarm information. At the same time, the alarm records can also be statistically analyzed to understand the fault distribution and trend of the industrial control computer, providing a reference for system maintenance and optimization.

[0048] It should be noted that for 3D scene construction, data acquisition can be achieved by using laser scanning or BIM modeling tools to obtain the factory's 3D structure. Each industrial control computer is assigned a unique ID, associated with its physical coordinates, production line, and responsible person. Multi-dimensional positioning assistance is provided, including a planar map positioning, a factory floor plan view, and equipment status marked with different colors. Quick search is supported, and automatic location is achieved by entering the equipment number. Equipment list positioning lists all equipment in a table, with abnormal equipment rows highlighted in red and flashing. Clicking on a row record will jump to the corresponding location in the 3D scene. The graphical interface is divided into different areas, each displaying different types of information. Interactive functions are added to the graphical interface to facilitate user viewing and data analysis. For some key indicators, such as CPU usage and memory usage, updates may be required every second or minute to ensure that users can understand the operating status of the industrial control computers in a timely manner.

[0049] The performance optimization module acquires the operating data of all industrial control computers in the factory in each historical period, identifies the set of fault categories of all industrial control computers in each historical period, and divides the inspection frequency of the automatic inspection robot for all fault categories in the factory.

[0050] In a specific embodiment of the present invention, the step of acquiring the operating data of all industrial control computers in the factory during each historical period and identifying the set of fault categories of all industrial control computers during each historical period specifically includes:

[0051] The identification number, fault category, number of occurrences of each fault category, cycle number, and total number of inspections within each cycle for all industrial control computers in the factory.

[0052] In a specific embodiment of the present invention, the specific steps for determining the occurrence probability of all fault categories within the factory are as follows:

[0053] The set of fault categories of all industrial control computers in the factory in each historical period is obtained f is the fault category number. ,in Let f be the frequency of occurrence of fault f. Let f be the number of times fault f occurs within the historical period, and z be the number of periods.

[0054] In a specific embodiment of the present invention, the step of classifying the inspection levels of the automated inspection robot to obtain all fault categories within the factory specifically includes:

[0055] Based on the number and frequency of occurrence of each fault, an inspection level coefficient is obtained for each fault. ,like If so, the inspection level of the fault is recorded as level j. Let be the range of the fault percentage coefficient corresponding to the j-th inspection level.

[0056] It should be noted that the specific fault percentage coefficient ranges corresponding to each inspection level are determined by the industrial control computer inspection personnel. For example, to prevent high-frequency fault categories from causing significant losses to the factory, the fault percentage coefficient ranges corresponding to each inspection level can be divided as follows: when At this time, it is the first level of fault inspection. At this time, it is the second level of fault inspection. This is the third level of fault inspection.

[0057] It should also be noted that the importance of the three levels of fault inspection—Level 1, Level 2, and Level 3—is less than that of Level 2, and vice versa. In other words, Level 1 industrial control computers have lower failure frequencies and frequency over historical periods, allowing for a reduction in daily inspection frequency and the number of automated inspection robots. Level 2 industrial control computers have moderate failure frequencies and frequency over historical periods, maintaining the historical daily inspection frequency and the number of automated inspection robots. Level 3 industrial control computers have higher failure frequencies and frequency over historical periods, allowing for an increase in daily inspection frequency and the number of automated inspection robots. This provides solid data support for subsequent inspection frequency and cost investment in industrial control computers within the factory, helping to reduce maintenance and management costs while ensuring the rationality of inspection frequency and cost investment.

[0058] In a specific embodiment of the present invention, the fault proportion coefficient range is specifically as follows:

[0059] The higher the failure rate coefficient, the higher the inspection level, the higher the inspection frequency, and the more automated inspection robots are used for inspection and maintenance.

[0060] It should be noted that the present invention also includes a database for storing reference raw data, including the original three-dimensional image of the industrial control computer, the maximum threshold for voltage fluctuation, the cable fault threshold, the maximum threshold for memory utilization, the maximum threshold for the number of memory errors, the maximum threshold for page swapping rate, the memory fault threshold, the maximum and minimum values ​​of motherboard capacitor aging score, and the total number of factory inspections.

[0061] Reference Figure 2 As shown, the second aspect of the present invention provides a method for an industrial control computer operation monitoring system based on data analysis, comprising: S1. Data acquisition and preprocessing, collecting the operation data of all industrial control computers in the factory within a set period through various sensors and data acquisition devices, and processing the data.

[0062] S2. Real-time monitoring and fault identification: The system analyzes and processes the collected operating data of all industrial control computers in the factory within a set period in real time to determine whether any industrial control computer in the factory has malfunctioned. If an industrial control computer malfunctions, the system identifies the set of fault categories of that industrial control computer. Based on the set of fault categories, the system determines the fault level of the industrial control computer and pushes warning information to the industrial control computer operation and maintenance personnel. At the same time, the system dynamically displays the industrial control computer and its set of fault categories through a 3D visualization monitoring interface.

[0063] S3. Performance optimization: Obtain the operating data of all industrial control computers in the factory in each historical period, identify the fault category set of all industrial control computers in each historical period, and classify the inspection level of the automatic inspection robot for all fault categories in the factory.

[0064] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications or additions should fall within the protection scope of the present invention.

Claims

1. An industrial control computer operation monitoring system based on data analysis, characterized in that, include: The data acquisition and preprocessing module collects and processes the operating data of all industrial control computers in the factory within a set period through various sensors and data acquisition devices. The real-time monitoring and fault identification module analyzes and processes the collected operating data of all industrial control computers in the factory within a set period in real time, determines whether any industrial control computer in the factory has malfunctioned, and if a certain industrial control computer malfunctions, identifies the set of fault categories of that industrial control computer; determines the fault level of the industrial control computer based on the set of fault categories, and pushes warning information to the industrial control computer operation and maintenance supervisors. At the same time, it dynamically displays the industrial control computer and its set of fault categories through a 3D visualization monitoring interface. The performance optimization module acquires the operating data of all industrial control computers in the factory in each historical period, identifies the set of fault categories of all industrial control computers in each historical period, and classifies the inspection level of the automatic inspection robot for all fault categories in the factory. The industrial control computer sets the operating data within a certain period and processes the collected data, specifically including: Multi-source data acquisition is performed to obtain the time-series operating data of the industrial control computer based on sensor data and industrial control computer performance indicators. The operating data includes hardware data and software data. The hardware data includes a 3D image of the casing, fan speed, temperature of the industrial control computer's heat dissipation area, number of connection interruptions, signal transmission delay, measured equivalent series resistance, actual capacitor operating temperature, and capacitor usage time. The software data includes data transmission error rate, voltage fluctuation amplitude, memory usage rate, number of memory errors, and page swapping rate. The collected data is processed by cleaning, removing missing values, denoising, extracting time-series features, converting formats, and normalizing data to eliminate dimensional differences. The method for determining whether all industrial control computers in the factory are malfunctioning, and identifying the set of malfunction categories for a particular industrial control computer if it is malfunctioning, is as follows: B1. Shell Deformation Fault: Compare the acquired 3D shell images with the original 3D shell images stored in the database to obtain the overlap volume between the current 3D shell image and the original 3D shell image, and substitute it into the tilt deformation judgment model. , This is the serial number of the industrial control computer. , It is any integer greater than 2. Number each measurement. , Let be any integer greater than 2, where Let be the overlap volume between the shell image measured by the nth industrial control computer in the i-th measurement and the original 3D image. Let the volume of the original 3D image of the casing be the volume of the nth industrial control computer during the i-th measurement. If the overlapping volume ratio of the outer casing of a certain industrial control computer is... If the deformation of the outer shell of the device is K, then K is the minimum volume ratio between the outer shell image measured by the industrial control computer and the original three-dimensional image. B2. Overheating failure. ,in This is the value used to determine fan operation. The measured fan speed is the value of the nth industrial computer during the i-th measurement. For the fan's rated speed, when The fan malfunctioned. The administrator sets the parameters based on the hardware specifications; ,in Let be the measured temperature of the heat dissipation area of ​​the nth industrial computer during the i-th measurement. This is the set normal operating temperature for the industrial computer's heat dissipation area. This is the critical offset for temperature anomalies, when At that time, the temperature of the industrial computer's heat dissipation area was abnormal; when Industrial computer cooling system malfunction. The logical AND symbol; B3. Cable fault, calculate the cable fault value. ,in Let be the monitoring data transmission error rate of the nth industrial control computer during the i-th measurement. To allow for a low data transmission error rate, Let i be the number of connection interruptions during the i-th measurement of the nth industrial control computer. To allow for a certain number of connection interruptions, For signal transmission delay duration, To allow for signal transmission delay duration, For voltage fluctuation anomalies and , This represents the actual voltage fluctuation range. The maximum threshold for voltage fluctuation. The weighting coefficients for monitoring data transmission error rate, connection interruption count, signal transmission delay duration, and voltage fluctuation amplitude are respectively... The average value of multiple measurements , At that time, the cable failed. The set cable fault threshold; B4. Memory Failure, Calculate Memory Failure Score ,in Score the memory usage of the nth industrial computer in the i-th measurement. , Let i be the actual memory usage rate of the nth industrial computer in the i-th measurement. The maximum threshold for memory usage. Score the memory error of the nth industrial computer in the i-th measurement and , Number of memory errors This is the maximum threshold for the number of memory errors. Let i be the page swap anomaly judgment value measured by the nth industrial control computer in the i-th measurement, and , This represents the actual page swapping rate. This is the maximum threshold for page swapping rate. The weighting coefficients for memory utilization, number of memory errors, and page swapping rate are respectively. , At that time, memory failure occurred. The set memory failure threshold; B5. Capacitor Failure: Scoring the degree of aging of motherboard capacitors. ,in Score the degree of capacitor aging for the nth industrial control computer in the i-th measurement. To measure the equivalent series resistance, The initial equivalent series resistance is given by an exponent of 1.5, reflecting the accelerating effect of the nonlinear growth of ESR. Let be the actual operating temperature of the capacitor measured by the nth industrial computer in the i-th measurement. Capacitor rated temperature As a temperature acceleration factor, The duration of capacitor usage for the i-th measurement by the nth industrial control computer. For capacitor design life, For time aging weighting coefficient, when At that time, the motherboard capacitors were healthy and showed no signs of aging. At that time, the motherboard capacitors had a slight aging failure; when At that time, the motherboard capacitors were completely aged. Specifically, this refers to the maximum and minimum values ​​of the motherboard capacitor aging score; Based on the above method, the fault categories of all industrial control computers are determined, and a set of fault categories for all industrial control computers is constructed.

2. The industrial control computer operation monitoring system based on data analysis according to claim 1, characterized in that, The process of determining the fault level of the industrial control computer based on the set of fault categories includes: ,in Score the fault level of the nth industrial control computer. Weights for each fault type, and , Scoring for each fault type, ,in To allow the industrial control computer to measure the deviation between the shell image and the original 3D image, , , , The fault level is .

3. The industrial control computer operation monitoring system based on data analysis according to claim 1, characterized in that, The system pushes warning messages to industrial control computer (ICS) maintenance and monitoring personnel, and simultaneously displays the ICS and its fault category set dynamically through a 3D visualization monitoring interface, which specifically includes: Notifications are triggered via the Drools rules engine, and can be categorized into sound alarms, pop-up alarms, and SMS or email alarms. When an industrial control computer malfunctions, a specific sound is played to alert maintenance and monitoring personnel. Simultaneously, monitoring images are used to detect whether maintenance and monitoring personnel are in the monitoring room. If so, an alarm window pops up on the graphical interface, displaying alarm information, including alarm time, alarm type, and fault description, to alert the monitoring personnel. If not, the alarm information is sent to the relevant personnel via SMS or email. All alarm information is recorded and stored in the database, and an alarm record query function is provided. Operation and maintenance supervisors can query the alarm records according to the time range, fault level, and fault type.

4. The industrial control computer operation monitoring system based on data analysis according to claim 1, characterized in that, The acquisition of operating data of all industrial control computers in the factory during each historical period, and the identification of fault category sets of all industrial control computers during each historical period, specifically includes: The identification number, fault category, number of occurrences of each fault category, cycle number, and total number of inspections within each cycle for all industrial control computers in the factory.

5. The industrial control computer operation monitoring system based on data analysis according to claim 4, characterized in that, The specific steps for determining the probability of occurrence of all fault categories within the factory are as follows: The set of fault categories of all industrial control computers in the factory in each historical period is obtained f is the fault category number. ,in Let f be the frequency of occurrence of fault f. Let f be the number of times fault f occurs within the historical period, and z be the number of periods.

6. The industrial control computer operation monitoring system based on data analysis according to claim 5, characterized in that, The classification determines the inspection levels of automated inspection robots for all fault categories within the factory, specifically including: Based on the number and frequency of occurrence of each fault, an inspection level coefficient is obtained for each fault. ,like If so, the inspection level of the fault is recorded as level j. Let be the range of the fault percentage coefficient corresponding to the j-th inspection level.

7. The industrial control computer operation monitoring system and method based on data analysis according to claim 6, characterized in that, The specific range of the fault percentage coefficient is as follows: The higher the failure rate coefficient, the higher the inspection level, the higher the inspection frequency, and the more automated inspection robots are used for inspection and maintenance.

8. A method for executing the industrial control computer operation monitoring system based on data analysis as described in any one of claims 1-7, comprising: S1. Data Acquisition and Preprocessing: Collect and process the operating data of all industrial control computers in the factory within a set period through various sensors and data acquisition devices. S2. Real-time monitoring and fault identification: Real-time analysis and processing of the operating data of all industrial control computers in the factory within a set period is performed to determine whether any industrial control computer in the factory has malfunctioned. If an industrial control computer malfunctions, the set of fault categories for that industrial control computer is identified. The fault level of the industrial control computer is determined based on the set of fault categories, and a warning message is pushed to the industrial control computer operation and maintenance supervisor. At the same time, the industrial control computer and its set of fault categories are dynamically displayed through a 3D visualization monitoring interface. S3. Performance optimization: Obtain the operating data of all industrial control computers in the factory in each historical period, identify the fault category set of all industrial control computers in each historical period, and classify the inspection level of the automatic inspection robot for all fault categories in the factory.

Images