State monitoring method and system of industrial internet equipment and storage medium

Abstract

The invention relates to the technical field of Internet equipment data monitoring, and particularly discloses a state monitoring method and system for industrial Internet equipment and a storage medium, and the method comprises the steps: analyzing the influence of operation data fluctuation on the data loss degree based on a loss degree large signal, obtaining an operation data fluctuation value, comparing the operation data fluctuation value with a threshold value, and obtaining the state of the industrial Internet equipment. The method comprises the steps of generating an influence degree signal, obtaining a data operation stable value based on the influence degree signal, comparing the data operation stable value with a threshold value, analyzing a network equipment data operation stable state, generating a signal whether data operation is stable or not, and analyzing the influence of operation data fluctuation on the data loss degree. According to the method, the source of a potential problem causing data loss can be quickly identified, and after the source and the influence degree of the data loss problem are identified, the risk of data loss can be reduced and the integrity and availability of the data can be ensured by continuously monitoring the data operation stability.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet device data monitoring, and in particular to a state monitoring method, system and storage medium for industrial Internet devices. Background Art

[0002] Industrial Internet equipment monitoring is one of the core technologies in the Industrial 4.0 era. It provides real-time and accurate data support for the production, management, decision-making and other links of enterprises by real-time monitoring of the status of various equipment in the industrial production process. This technology integrates advanced sensor technology, communication technology and data processing technology to achieve interconnection between equipment, between equipment and control system, and between control system and information system.

[0003] The Chinese invention patent with publication number CN113438114B discloses an Internet system operation status monitoring method, device, equipment and storage medium, collects system log files, extracts current log data from the system log files, and preprocesses the current log data; extracts features of the preprocessed current log data based on a target recurrent neural network model, uses an LSTM neural network to classify and predict the feature extraction results, converts the classification prediction results into probability distribution prediction values ​​through normalization, and identifies the Internet operation status based on the probability distribution prediction values; when the Internet operation status is abnormal, obtains user operation records, and extracts maintenance data from the user operation records; matches the maintenance data with the current log data, and determines whether the abnormality in the operation status of the Internet system is an occasional abnormality based on the matching result.

[0004] However, there is no real-time monitoring of data operation to determine whether data operation generates abnormal signals, nor is there any assessment of the degree of data loss based on abnormal data operation signals. Abnormal conditions cannot be detected before serious problems occur in the equipment, and data support cannot be provided for subsequent maintenance and repairs. At the same time, no adjustments are made based on unstable data operation signals to ensure stable operation after data recovery, reduce service interruption time caused by data loss, and avoid unnecessary waste of resources through precise adjustments. Summary of the invention

[0005] The purpose of the present invention is to provide a state monitoring method, system and storage medium for industrial Internet equipment to solve the technical problems in the above background.

[0006] The purpose of the present invention can be achieved through the following technical solutions: In a first aspect, the present invention provides a method for monitoring the status of an industrial Internet device, comprising the following steps: Step 1: Collect the operation data of Internet devices in real time during the monitoring period, obtain the operation data representation value, compare it with the threshold value, and generate a signal to indicate whether the operation is abnormal; If the operation data characterization value is less than the operation data characterization threshold, an operation abnormality signal is generated; Step 2: Based on the abnormal operation signal, obtain the data loss degree value, compare it with the threshold, and generate a loss degree signal; If the data loss degree value is greater than or equal to the data loss degree threshold, a large loss degree signal is generated; Step 3: Based on the large signal of loss degree, analyze the impact of operation data fluctuation on data loss degree, obtain the operation data fluctuation value, compare it with the threshold, and generate the impact degree signal; If the operating data fluctuation value is greater than or equal to the operating data fluctuation threshold, a high impact signal is generated; Step 4: Based on the large impact signal, obtain the data operation stability value, compare it with the threshold, analyze the data operation stability state of the network device, and generate a data operation stability signal; The data operation stability value is greater than or equal to the data operation stability threshold, generating a data operation instability signal; Step 5: Based on the data operation instability signal, the data operation status is adjusted within the data loss period to obtain the data operation status adjustment value, thereby completing the optimization and adjustment work; The process of obtaining the data operation status adjustment value is as follows: During the data loss period, obtain the current data running value through the formula: Calculate the data operation status adjustment value , Indicates the current data running status value. It is expressed as adjustment factor; The adjustment coefficient is obtained as follows: A data transmission flow adjustment coefficient and a data transmission rate adjustment coefficient are obtained, and the data transmission flow adjustment coefficient and the data transmission rate adjustment coefficient are added together to obtain an adjustment coefficient.

[0007] As a further solution of the present invention: In step 1, the method for obtaining the characterization value of the running data is as follows: Get the data transmission rate value and data transmission flow value, mark the data transmission rate value as V, mark the data transmission flow value as L, and use the formula: , calculate the running data characterization value Y, , Expressed as a preset weight coefficient; How to obtain the data transmission rate value: During the monitoring period, the monitoring period is divided into a number of equal time periods, the data transmission rate is monitored in real time, marked as the real-time data transmission rate, and the real-time data transmission rates are added and averaged to obtain the data transmission rate value; How to obtain the data transmission flow value: During the monitoring period, the monitoring period is divided into several equal time periods, and the data transmission flow in each time period is obtained in real time and marked as real-time data transmission flow. All real-time data transmission flows are added and averaged to obtain the data transmission flow value.

[0008] As a further solution of the present invention: In step 2, the data loss degree value is obtained in the following manner: Obtain the ratio of the number of lost data and the ratio of the duration of lost data within the abnormal time period, add the ratio of the number of lost data and the ratio of the duration of lost data to obtain a data loss degree value; How to obtain the ratio of lost data: Obtain the amount of data transmitted by the data terminal during the monitoring period, and mark it as the initial amount of data; Get the number of data received by the data terminal during the monitoring period, marked as the number of data received; During the monitoring period, the difference between the initial data quantity and the data received quantity is calculated to obtain the data received difference value; Based on the data reception difference value, the amount of lost data in the monitoring period is obtained and marked as the amount of lost data; How to obtain the data loss duration ratio: Based on the data loss signal, obtain the time length corresponding to the lost data in the monitoring period, and mark it as the lost data duration length value; During the monitoring period, the duration length values ​​of the lost data are obtained, and the duration length values ​​of the lost data are added and summed to obtain the total duration value of the lost data; The total value of the duration of lost data is calculated by ratio with the value of the monitoring period length to obtain the data loss duration ratio.

[0009] As a further solution of the present invention: In step 3, the method for obtaining the fluctuation value of the running data is as follows: During the monitoring period, the data transmission rate fluctuation value and the data transmission flow fluctuation value are obtained, and the data transmission rate fluctuation value and the data transmission flow fluctuation value are added together to obtain the operation data fluctuation value.

[0010] As a further solution of the present invention: in step 3, the process of obtaining the data transmission rate fluctuation value is as follows: The real-time data transmission rate corresponding to different time points within the data loss time is obtained, marked as the real-time data loss transmission rate, and substituted into the XY axis two-dimensional coordinate system for marking, where the X axis represents different time points, and the Y axis represents the real-time data loss transmission rate corresponding to different time points, and the marked real-time data loss transmission rate points are connected to output a data loss real-time transmission rate change curve; Based on the data loss real-time transmission rate change curve, the coordinates of the marked data loss real-time transmission rate points are marked as ( , ), obtain the coordinates of the two adjacent peak points and the coordinates of the trough points, and mark the coordinates of the two adjacent peak points and the coordinates of the trough points as ( , )and( , ), through the formula: L= , calculate the peak-to-valley length value; Calculate the standard deviation of all peak-to-valley length values ​​to obtain the data transmission rate fluctuation value; How to obtain the data transmission flow fluctuation value: The real-time data transmission flow corresponding to different time points during the data loss period is obtained, and the data is substituted into the XY axis two-dimensional coordinate system for marking. The X axis represents different time points, and the Y axis represents the data transmission flow corresponding to different time points. The marked real-time data transmission flow points are connected to output a real-time data transmission flow change curve. Based on the real-time data transmission flow rate change curve, the data transmission flow rate fluctuation value is outputted through the above-mentioned data transmission rate fluctuation value processing method.

[0011] As a further solution of the present invention: In step 4, the data operation stability value is obtained in the following manner: The loss degree impact value and the transmission fluctuation impact value are obtained, and the loss degree impact value and the transmission fluctuation impact value are added together to obtain a data operation stability value.

[0012] As a further solution of the present invention: in step 4, the process of obtaining the value of the degree of data loss is as follows: In the monitoring cycle, the monitoring cycle is divided into several monitoring sub-cycles, the number of data losses in each monitoring sub-cycle is obtained, marked as the sub-cycle data loss number, and the number of data losses in all sub-cycles is added and averaged to obtain the average value of the data loss number; Subtract the sub-period data loss number from the average data loss number, take the absolute value, and obtain the sub-period data number deviation value; calculate the ratio of the sub-period data number deviation value to the average data loss number, and obtain the sub-period data deviation coefficient; Calculate the standard deviation of all sub-period data deviation coefficients to obtain the value of the degree of data loss; The process of obtaining the data loss time degree value is as follows: In the monitoring cycle, the monitoring cycle is divided into several monitoring sub-cycles, the duration of data loss in each monitoring sub-cycle is obtained, and marked as the sub-cycle data loss duration length value, and the data loss duration length values ​​of all sub-cycles are added and averaged to obtain the average data loss duration length; Subtract the sub-period data loss duration length value from the average data loss duration length value, take the absolute value, and obtain the sub-period data loss duration length deviation value; calculate the ratio of the sub-period data loss duration length deviation value to the average data loss duration length, and obtain the sub-period data loss duration length deviation coefficient; The standard deviation of the duration coefficient of data loss of all sub-periods is calculated to obtain the value of the data loss time degree.

[0013] As a further solution of the present invention: In step 4, the transmission fluctuation impact value is obtained in the following manner: Obtaining a data transmission flow rate level value and a data transmission rate level value, adding the data transmission flow rate level value and the data transmission rate level value to obtain a transmission fluctuation impact value; The data transmission rate value is obtained as follows: In the lost time period, the lost time period is divided into several sub-time periods, a data transmission rate fluctuation value in each sub-time period is obtained, and the data transmission rate fluctuation values ​​in the sub-time periods are added and averaged to obtain a data transmission rate fluctuation average value; The data transmission rate fluctuation value in the sub-time period is subtracted from the data transmission rate fluctuation average value, and the absolute value is taken to obtain the data transmission rate fluctuation deviation value in the sub-time period; the data transmission rate fluctuation deviation value in the sub-time period is calculated by ratio with the data transmission rate fluctuation average value to obtain the data transmission fluctuation deviation coefficient in the sub-time period; Calculate the standard deviation of the data transmission fluctuation deviation coefficient of the sub-time period to obtain the data transmission rate degree value; The data transmission flow rate value is obtained as follows: In the loss time period, the loss time period is divided into several sub-time periods, a data transmission flow fluctuation value in each sub-time period is obtained, and the data transmission flow fluctuation values ​​in the sub-time periods are added and averaged to obtain a data transmission flow fluctuation average value; The data transmission flow fluctuation value in the sub-time period is subtracted from the data transmission flow fluctuation average value, and the absolute value is taken to obtain the data transmission flow fluctuation deviation value in the sub-time period. The data transmission flow fluctuation deviation value in the sub-time period is calculated by ratio with the data transmission flow fluctuation average value to obtain the data transmission flow fluctuation deviation coefficient in the sub-time period. The data transmission fluctuation deviation coefficient of the sub-time period is calculated by standard deviation to obtain the data transmission flow degree value.

[0014] In a second aspect, the present invention provides a status monitoring system for industrial Internet devices, the system is used to execute the method described in any one of claims 1 to 8 above, and the system includes the following modules: Operation monitoring module: collects Internet device operation data in real time during the monitoring period, obtains the operation data representation value, compares it with the threshold value, and generates a signal to indicate whether the operation is abnormal; If the operation data characterization value is less than the operation data characterization threshold, an operation abnormality signal is generated; Impact analysis module: Based on the abnormal operation signal, obtain the data loss degree value, compare it with the threshold, and generate a loss degree signal; If the data loss degree value is greater than or equal to the data loss degree threshold, a large loss degree signal is generated; Loss assessment module: Based on the large loss degree signal, analyze the impact of operating data fluctuations on the data loss degree, obtain the operating data fluctuation value, compare it with the threshold, and generate an impact degree signal; If the operating data fluctuation value is greater than or equal to the operating data fluctuation threshold, a high impact signal is generated; Stability evaluation module: Based on the large impact signal, obtain the data operation stability value, compare it with the threshold, analyze the data operation stability status of the network equipment, and generate a signal whether the data operation is stable; The data operation stability value is greater than or equal to the data operation stability threshold, generating a data operation instability signal; Adjustment and optimization module: Based on the data operation instability signal, the data operation status is adjusted during the data loss period to obtain the data operation status adjustment value and complete the optimization and adjustment work; The process of obtaining the data operation status adjustment value is as follows: During the data loss period, obtain the current data running value through the formula: Calculate the data operation status adjustment value , Indicates the current data running status value. It is expressed as adjustment factor; The adjustment coefficient is obtained as follows: A data transmission flow adjustment coefficient and a data transmission rate adjustment coefficient are obtained, and the data transmission flow adjustment coefficient and the data transmission rate adjustment coefficient are added together to obtain an adjustment coefficient.

[0015] A storage medium stores an industrial Internet device, which, when executed by a processor, implements the state monitoring method of the industrial Internet device as described in any one of claims 1 to 8.

[0016] Beneficial effects of the present invention: (1) The present invention collects Internet device operation data in real time during the monitoring period to obtain an operation data characterization value, compares it with a threshold, generates an operation abnormality signal, obtains a data loss degree value based on the operation abnormality signal, compares it with a threshold, and generates a loss degree signal. This helps administrators detect abnormal conditions before serious problems occur in the equipment, and early detection of abnormalities can prevent potential risks from further deteriorating, providing data support for later maintenance and repairs. (2) The present invention analyzes the impact of operating data fluctuations on the degree of data loss based on a large signal of the degree of loss, obtains an operating data fluctuation value, compares it with a threshold, and generates an impact magnitude signal. Based on the large signal of the degree of impact, a data operation stability value is obtained, compared with a threshold, and the data operation stability state of the network device is analyzed to generate a data operation stability signal. By analyzing the impact of operating data fluctuations on the degree of data loss, the potential root cause of the problem that causes data loss can be quickly identified. After identifying the root cause and impact of the data loss problem, the risk of data loss can be reduced by continuously monitoring the stability of data operation to ensure data integrity and availability.

[0017] (3) The present invention adjusts the data operation status within the data loss period based on the data operation instability signal to obtain the data operation status adjustment value, thereby completing the optimization adjustment work. During the data loss period, the present invention makes adjustments based on the data operation instability signal to ensure stable operation after data recovery, reduce the service interruption time caused by data loss, and avoid unnecessary waste of resources through precise adjustment. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The present invention will be further described below in conjunction with the accompanying drawings.

[0019] Figure 1 is a flow chart of Embodiment 1 of the present invention; Figure 2 is a flow chart of Embodiment 2 of the present invention; Figure 3 It is the third figure of embodiment of the present invention; Figure 4 Is a schematic diagram of the system of the present invention; Figure 5 It is a structural diagram of embodiment 5 of the present invention. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] Embodiment 1: See also Figure 1 As shown, the method for monitoring the status of an industrial Internet device according to an embodiment of the present invention comprises the following steps: Step 1: Collect the operation data of Internet devices in real time during the monitoring period, obtain the operation data representation value, compare it with the threshold value, and generate a signal to indicate whether the operation is abnormal; In some embodiments, during the monitoring period, the Internet device operation data is collected in real time by a data monitoring device to obtain an operation data characterization value, and the operation data characterization value is compared with the operation data characterization threshold value. The comparison process is as follows: If the operation data characterization value is greater than or equal to the operation data characterization threshold, it means that the data transmission rate is relatively stable, the data transmission flow is relatively stable, the Internet device operation data efficiency is high, and a normal operation signal is generated; If the operation data characterization value is less than the operation data characterization threshold, it means that the data transmission rate is relatively unstable, the data transmission flow is relatively unstable, the Internet device operation data efficiency is low, and an operation abnormality signal is generated; The method for obtaining the characterization value of the running data is as follows: Get the data transmission rate value and data transmission flow value, mark the data transmission rate value as V, mark the data transmission flow value as L, and use the formula: , calculate the running data characterization value Y, , Expressed as a preset weight coefficient; Specifically, the data transmission rate value is obtained as follows: During the monitoring period, the monitoring period is divided into a number of equal time periods, the data transmission rate is monitored in real time, marked as the real-time data transmission rate, and the real-time data transmission rates are added and averaged to obtain the data transmission rate value; How to obtain the data transmission flow value: During the monitoring period, the monitoring period is divided into several equal time periods, and the data transmission flow in each time period is obtained in real time, marked as real-time data transmission flow, and all real-time data transmission flows are added and averaged to obtain the data transmission flow value; Step 2: Based on the abnormal operation signal, obtain the data loss degree value, compare it with the threshold, and generate a loss degree signal; In some embodiments, when an abnormal operation signal is generated, a data loss degree value is obtained, and the data loss degree value is compared with a data loss degree threshold. The comparison process is as follows: If the data loss degree value is greater than or equal to the data loss degree threshold, it means that the data loss degree is large during the abnormal duration period, and a large loss degree signal is generated; If the data loss degree value is less than the data loss degree threshold, it means that the data loss degree during the abnormal duration period is small, and a small loss degree signal is generated; The data loss degree value is obtained in the following way: Obtain the ratio of the number of lost data and the ratio of the duration of lost data within the abnormal time period, add the ratio of the number of lost data and the ratio of the duration of lost data to obtain a data loss degree value; Specifically, the method for obtaining the ratio of lost data is as follows: Obtain the amount of data transmitted by the data terminal during the monitoring period, and mark it as the initial amount of data; Get the number of data received by the data terminal during the monitoring period, marked as the number of data received; During the monitoring period, the difference between the initial data quantity and the data received quantity is calculated to obtain the data received difference value; Based on the data reception difference value, the amount of lost data in the monitoring period is obtained and marked as the amount of lost data; Calculate the ratio of the number of missing data to the initial number of data to obtain the ratio of the number of missing data; How to obtain the data loss time ratio: Based on the data loss signal, obtain the time length corresponding to the lost data in the monitoring period, and mark it as the lost data duration length value; During the monitoring period, the duration length values ​​of the lost data are obtained, and the duration length values ​​of the lost data are added and summed to obtain the total duration value of the lost data; The total value of the duration of lost data is calculated by ratio with the value of the monitoring period length to obtain the data loss time ratio; The specific implementation plan of the embodiment of the present invention is: collect Internet device operation data in real time during the monitoring period, obtain operation data characterization values, compare with threshold values, generate operation abnormality signals, obtain data loss degree values ​​based on the operation abnormality signals, compare with threshold values, and generate loss degree signals. This helps administrators to detect abnormal situations before serious problems occur in the equipment, and early detection of abnormalities can prevent potential risks from further deteriorating, providing data support for subsequent maintenance and repairs.

[0022] Embodiment 2 Based on Example 1, please refer to Figure 2 As shown, the method for monitoring the status of an industrial Internet device according to an embodiment of the present invention comprises the following steps: Step 3: Based on the large signal of loss degree, analyze the impact of operation data fluctuation on data loss degree, obtain the operation data fluctuation value, compare it with the threshold, and generate the impact degree signal; In some embodiments, the process of obtaining the data transmission rate fluctuation value is as follows: The real-time data transmission rate corresponding to different time points within the data loss time is obtained, marked as the real-time data loss transmission rate, and substituted into the XY axis two-dimensional coordinate system for marking, where the X axis represents different time points, and the Y axis represents the real-time data loss transmission rate corresponding to different time points, and the marked real-time data loss transmission rate points are connected to output a data loss real-time transmission rate change curve; Based on the data loss real-time transmission rate change curve, the coordinates of the marked data loss real-time transmission rate points are marked as ( , ), obtain the coordinates of the two adjacent peak points and the coordinates of the trough points, and mark the coordinates of the two adjacent peak points and the coordinates of the trough points as ( , )and( , ), through the formula: L= , calculate the peak-to-valley length value; Calculate the standard deviation of all peak-to-valley length values ​​to obtain the data transmission rate fluctuation value; How to obtain the data transmission flow fluctuation value: The real-time data transmission flow corresponding to different time points during the data loss period is obtained, and the data is substituted into the XY axis two-dimensional coordinate system for marking. The X axis represents different time points, and the Y axis represents the data transmission flow corresponding to different time points. The marked real-time data transmission flow points are connected to output a real-time data transmission flow change curve. Based on the real-time data transmission flow rate change curve, the data transmission flow rate fluctuation value is output through the above-mentioned data transmission rate fluctuation value processing method; Among them, it is necessary to explain that: the meaning of the data transmission rate fluctuation value is: the overall fluctuation degree of the data transmission rate during the data loss period. If the overall fluctuation degree of the data transmission rate is large, the overall fluctuation of the data transmission rate is large, which has a greater impact on data transmission and leads to a greater degree of data loss; If the overall fluctuation of data transmission rate is small, the overall fluctuation of data transmission rate is small, which has less impact on data transmission and leads to less data loss; How to obtain the data transmission flow fluctuation value: The real-time data transmission flow corresponding to different time points during the data loss period is obtained, and the data is substituted into the XY axis two-dimensional coordinate system for marking. The X axis represents different time points, and the Y axis represents the data transmission flow corresponding to different time points. The marked real-time data transmission flow points are connected to output a real-time data transmission flow change curve. Based on the real-time data transmission flow rate change curve, the data transmission flow rate fluctuation value is output through the above processing method; Step 4: Based on the large impact signal, obtain the data operation stability value, compare it with the threshold, analyze the data operation stability state of the network device, and generate a data operation stability signal; In some embodiments, when a large impact signal is generated, a loss impact value and a transmission fluctuation impact value are obtained, and the loss impact value and the transmission fluctuation impact value are added and summed to obtain a data operation stability value; The data operation stability value is compared with the data operation stability threshold. The comparison process is as follows: If the data operation stability value is greater than or equal to the data operation stability threshold, it means that the data loss degree is large and the data transmission fluctuation is large, and a data operation instability signal is generated; If the data operation stability value is less than the data operation stability threshold, it means that the data loss degree is small and the data transmission fluctuation is small, and a data operation stability signal is generated; Among them, the method of obtaining the loss degree impact value is: Obtaining a data loss quantity degree value and a data loss time degree value, adding the loss quantity degree value and the data loss time degree value to obtain a loss degree impact value; Exemplarily, the process of obtaining the data loss quantity degree value is as follows: In the monitoring cycle, the monitoring cycle is divided into several monitoring sub-cycles, the number of data losses in each monitoring sub-cycle is obtained, marked as the sub-cycle data loss number, and the number of data losses in all sub-cycles is added and averaged to obtain the average value of the data loss number; Subtract the sub-period data loss number from the average data loss number, take the absolute value, and obtain the sub-period data number deviation value; calculate the ratio of the sub-period data number deviation value to the average data loss number, and obtain the sub-period data deviation coefficient; Calculate the standard deviation of all sub-period data deviation coefficients to obtain the value of the degree of data loss; The process of obtaining the data loss time degree value is as follows: In the monitoring cycle, the monitoring cycle is divided into several monitoring sub-cycles, the duration of data loss in each monitoring sub-cycle is obtained, and marked as the sub-cycle data loss duration length value, and the data loss duration length values ​​of all sub-cycles are added and averaged to obtain the average data loss duration length; Subtract the sub-period data loss duration length value from the average data loss duration length value, take the absolute value, and obtain the sub-period data loss duration length deviation value; calculate the ratio of the sub-period data loss duration length deviation value to the average data loss duration length, and obtain the sub-period data loss duration length deviation coefficient; The standard deviation of the duration deviation coefficient of all sub-period data loss is calculated to obtain the data loss time degree value; How to obtain the transmission fluctuation impact value: Obtaining a data transmission flow rate level value and a data transmission rate level value, adding the data transmission flow rate level value and the data transmission rate level value to obtain a transmission fluctuation impact value; The data transmission rate value is obtained as follows: In the lost time period, the lost time period is divided into several sub-time periods, a data transmission rate fluctuation value in each sub-time period is obtained, and the data transmission rate fluctuation values ​​in the sub-time periods are added and averaged to obtain a data transmission rate fluctuation average value; The data transmission rate fluctuation value in the sub-time period is subtracted from the data transmission rate fluctuation average value, and the absolute value is taken to obtain the data transmission rate fluctuation deviation value in the sub-time period; the data transmission rate fluctuation deviation value in the sub-time period is calculated by ratio with the data transmission rate fluctuation average value to obtain the data transmission fluctuation deviation coefficient in the sub-time period; Calculate the standard deviation of the data transmission fluctuation deviation coefficient of the sub-time period to obtain the data transmission rate degree value; The data transmission flow rate value is obtained as follows: In the loss time period, the loss time period is divided into several sub-time periods, a data transmission flow fluctuation value in each sub-time period is obtained, and the data transmission flow fluctuation values ​​in the sub-time periods are added and averaged to obtain a data transmission flow fluctuation average value; The data transmission flow fluctuation value in the sub-time period is subtracted from the data transmission flow fluctuation average value, and the absolute value is taken to obtain the data transmission flow fluctuation deviation value in the sub-time period. The data transmission flow fluctuation deviation value in the sub-time period is calculated by ratio with the data transmission flow fluctuation average value to obtain the data transmission flow fluctuation deviation coefficient in the sub-time period. Calculate the standard deviation of the data transmission fluctuation deviation coefficient in the sub-time period to obtain the data transmission flow degree value; Specific implementation scheme of the embodiment of the present invention: Based on the large signal of the loss degree, the influence of the operation data fluctuation on the data loss degree is analyzed to obtain the operation data fluctuation value, which is compared with the threshold to generate an influence degree signal; based on the large signal of the influence degree, the data operation stability value is obtained, which is compared with the threshold, the network device data operation stability state is analyzed, and a data operation stability signal is generated; by analyzing the influence of the operation data fluctuation on the data loss degree, the potential root cause of the problem causing the data loss can be quickly identified; after identifying the root cause and influence degree of the data loss problem, the risk of data loss can be reduced by continuously monitoring the data operation stability to ensure the integrity and availability of the data.

[0023] Embodiment 3 Based on the first and second embodiments, please refer to Figure 3 As shown, the state monitoring method of the industrial Internet device according to the embodiment of the present invention is specifically the following steps: Step 5: Based on the data operation instability signal, the data operation status is adjusted within the data loss period to obtain the data operation status adjustment value, thereby completing the optimization and adjustment work; Wherein, adjusting the data operation state includes: a data transmission flow adjustment signal, a data transmission rate adjustment signal and a data operation adjustment signal; What needs to be explained is: If the real-time data transmission rate reaches the data transmission rate standard value, and the real-time data transmission flow rate does not reach the data transmission flow rate standard value, a data transmission flow rate adjustment signal is generated; If the real-time data transmission flow rate reaches the data transmission flow rate standard value, and the real-time data transmission rate does not reach the data transmission rate standard value, a data transmission rate adjustment signal is generated; If the real-time data transmission flow rate does not reach the data transmission flow rate standard value, and the real-time data transmission rate does not reach the data transmission rate standard value, a data operation adjustment signal is generated; In some embodiments, when a data operation instability signal is generated, during a data loss period, analyzing when a data operation adjustment signal is generated; When a data transmission flow adjustment signal is generated, the data operation transmission flow is adjusted to obtain a data operation adjustment value, and the optimization adjustment work is completed based on the data operation adjustment value; The process of obtaining the data operation status adjustment value is as follows: During the data loss period, obtain the current data running value through the formula: Calculate the data operation status adjustment value , Indicates the current data running status value. It is expressed as adjustment factor; The adjustment coefficient is obtained as follows: Acquire a data transmission flow adjustment coefficient and a data transmission rate adjustment coefficient, and add the data transmission flow adjustment coefficient and the data transmission rate adjustment coefficient to obtain an adjustment coefficient; The data transmission flow adjustment coefficient is obtained as follows: The data transmission flow rate coefficient and the data transmission flow rate coefficient are added together to obtain the data transmission flow rate adjustment coefficient; Specifically, the data transmission flow rate coefficient is obtained as follows: Obtaining a data transmission flow rate value, subtracting the data transmission flow rate value from a data transmission flow rate threshold, and performing ratio calculation on the difference to obtain a data transmission flow rate coefficient; The data transmission flow coefficient is obtained as follows: Obtaining a data transmission flow coefficient, subtracting the data transmission flow coefficient from a data transmission flow coefficient threshold, and performing ratio calculation on the difference to obtain the data transmission flow coefficient; The data transmission rate adjustment coefficient is obtained as follows: The data transmission rate degree coefficient and the data transmission rate coefficient are added together to obtain the data transmission rate adjustment coefficient; Specifically, the data transmission rate coefficient is obtained as follows: Obtaining a data transmission rate value, subtracting the data transmission rate value from a data transmission rate threshold, and performing ratio calculation on the difference to obtain a data transmission rate coefficient; The data transmission rate coefficient is obtained as follows: Obtaining a data transmission rate coefficient, subtracting the data transmission rate coefficient from a data transmission rate coefficient threshold, and performing ratio calculation on the difference to obtain the data transmission rate coefficient; The specific implementation plan in the embodiment of the present invention is: based on the data operation instability signal, the data operation state is adjusted within the data loss time period to obtain the data operation state adjustment value, and the optimization adjustment work is completed. During the data loss time period, adjustment is performed based on the data operation instability signal, which can more effectively restore the stable operation state of the data, reduce the service interruption time caused by data loss, and avoid unnecessary waste of resources through precise adjustment.

[0024] Embodiment 4 Based on the first, second and third embodiments, please refer to Figure 4 As shown, the state monitoring storage system of the industrial Internet device according to the embodiment of the present invention includes the following modules: Operation monitoring module: collects Internet device operation data in real time during the monitoring period, obtains the operation data representation value, compares it with the threshold value, and generates a signal to indicate whether the operation is abnormal; If the operation data characterization value is less than the operation data characterization threshold, an operation abnormality signal is generated; Loss assessment module: based on the abnormal operation signal, obtains the data loss degree value, compares it with the threshold, and generates a loss degree signal; If the data loss degree value is greater than or equal to the data loss degree threshold, a large loss degree signal is generated; Impact analysis module: Based on the large signal of loss degree, analyze the impact of operation data fluctuation on data loss degree, obtain the operation data fluctuation value, compare it with the threshold, and generate the impact degree signal; If the operating data fluctuation value is greater than or equal to the operating data fluctuation threshold, a high impact signal is generated; Stability evaluation module: Based on the large impact signal, obtain the data operation stability value, compare it with the threshold, analyze the data operation stability status of the network equipment, and generate a signal whether the data operation is stable; The data operation stability value is greater than or equal to the data operation stability threshold, generating a data operation instability signal; Adjustment and optimization module: Based on the data operation instability signal, the data operation status is adjusted during the data loss period to obtain the data operation status adjustment value and complete the optimization and adjustment work; The process of obtaining the data operation adjustment value is as follows: During the data loss period, obtain the current data running value through the formula: Calculate the data operation transmission flow adjustment value , Indicates the transmission flow value for the current data operation. It is expressed as adjustment factor; The adjustment coefficient is obtained as follows: A data transmission flow adjustment coefficient and a data transmission rate adjustment coefficient are obtained, and the data transmission flow adjustment coefficient and the data transmission rate adjustment coefficient are added together to obtain an adjustment coefficient.

[0025] Embodiment 5 See also Figure 5 As shown, Figure 5 The state monitoring storage medium diagram of the industrial Internet device according to the embodiment of the present invention is as follows: Figure 5 As shown, this embodiment provides a state monitoring storage medium 600 of an industrial Internet device, on which a state monitoring system 601 of an industrial Internet device is stored. The state monitoring system 601 of the industrial Internet device is executed by a processor to implement the following steps: Step 1: Collect the operation data of Internet devices in real time during the monitoring period, obtain the operation data representation value, compare it with the threshold value, and generate a signal to indicate whether the operation is abnormal; If the operation data characterization value is less than the operation data characterization threshold, an operation abnormality signal is generated; Step 2: Based on the abnormal operation signal, obtain the data loss degree value, compare it with the threshold, and generate a loss degree signal; If the data loss degree value is greater than or equal to the data loss degree threshold, a large loss degree signal is generated; Step 3: Based on the large signal of loss degree, analyze the impact of operation data fluctuation on data loss degree, obtain the operation data fluctuation value, compare it with the threshold, and generate the impact degree signal; If the operating data fluctuation value is greater than or equal to the operating data fluctuation threshold, a high impact signal is generated; Step 4: Based on the large impact signal, obtain the data operation stability value, compare it with the threshold, analyze the data operation stability state of the network device, and generate a data operation stability signal; The data operation stability value is greater than or equal to the data operation stability threshold, generating a data operation instability signal; Step 5: Based on the data operation instability signal, the data operation status is adjusted within the data loss period to obtain the data operation status adjustment value, thereby completing the optimization and adjustment work; The process of obtaining the data operation adjustment value is as follows: During the data loss period, obtain the current data running value through the formula: Calculate the data operation transmission flow adjustment value , Indicates the transmission flow value for the current data operation. It is expressed as adjustment factor; The adjustment coefficient is obtained as follows: A data transmission flow adjustment coefficient and a data transmission rate adjustment coefficient are obtained, and the data transmission flow adjustment coefficient and the data transmission rate adjustment coefficient are added together to obtain an adjustment coefficient.

[0026] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for monitoring the status of industrial Internet equipment, characterized in that: The following steps are involved: Step 1: Collect the operation data of Internet devices in real time during the monitoring period, obtain the operation data representation value, compare it with the threshold value, and generate a signal to indicate whether the operation is abnormal; If the operation data characterization value is less than the operation data characterization threshold, an operation abnormality signal is generated; Step 2: Based on the abnormal operation signal, obtain the data loss degree value, compare it with the threshold, and generate a loss degree signal; If the data loss degree value is greater than or equal to the data loss degree threshold, a large loss degree signal is generated; Step 3: Based on the large signal of loss degree, analyze the impact of operation data fluctuation on data loss degree, obtain the operation data fluctuation value, compare it with the threshold, and generate the impact degree signal; If the operating data fluctuation value is greater than or equal to the operating data fluctuation threshold, a high impact signal is generated; Step 4: Based on the large impact signal, obtain the data operation stability value, compare it with the threshold, analyze the data operation stability state of the network device, and generate a data operation stability signal; The data operation stability value is greater than or equal to the data operation stability threshold, generating a data operation instability signal; Step 5: Based on the data operation instability signal, the data operation status is adjusted within the data loss period to obtain the data operation status adjustment value, thereby completing the optimization and adjustment work; The process of obtaining the data operation status adjustment value is as follows: During the data loss period, obtain the current data running value through the formula: Calculate the data operation status adjustment value , Indicates the current data running status value. It is expressed as adjustment factor; The adjustment coefficient is obtained as follows: A data transmission flow adjustment coefficient and a data transmission rate adjustment coefficient are obtained, and the data transmission flow adjustment coefficient and the data transmission rate adjustment coefficient are added together to obtain an adjustment coefficient.

2. The method for monitoring the status of industrial Internet equipment according to claim 1, characterized in that: In step 1, the method for obtaining the characterization value of the running data is as follows: Get the data transmission rate value and data transmission flow value, mark the data transmission rate value as V, mark the data transmission flow value as L, and use the formula: , calculate the running data characterization value Y, , Expressed as a preset weight coefficient; How to obtain the data transmission rate value: During the monitoring period, the monitoring period is divided into a number of equal time periods, the data transmission rate is monitored in real time, marked as the real-time data transmission rate, and the real-time data transmission rates are added and averaged to obtain the data transmission rate value; How to obtain the data transmission flow value: During the monitoring period, the monitoring period is divided into several equal time periods, and the data transmission flow in each time period is obtained in real time and marked as real-time data transmission flow. All real-time data transmission flows are added and averaged to obtain the data transmission flow value.

3. The method, system and storage medium for monitoring the status of industrial Internet devices according to claim 1, characterized in that: In step 2, the data loss degree value is obtained by: Obtain the ratio of the number of lost data and the ratio of the duration of lost data within the abnormal time period, add the ratio of the number of lost data and the ratio of the duration of lost data to obtain a data loss degree value; How to obtain the ratio of lost data: Obtain the amount of data transmitted by the data terminal during the monitoring period, and mark it as the initial amount of data; Get the number of data received by the data terminal during the monitoring period, marked as the number of data received; During the monitoring period, the difference between the initial data quantity and the data received quantity is calculated to obtain the data received difference value; Based on the data reception difference value, the amount of lost data in the monitoring period is obtained and marked as the amount of lost data; How to obtain the data loss duration ratio: Based on the data loss signal, obtain the time length corresponding to the lost data in the monitoring period, and mark it as the lost data duration length value; During the monitoring period, the duration length values ​​of the lost data are obtained, and the duration length values ​​of the lost data are added and summed to obtain the total duration value of the lost data; The total value of the duration of lost data is calculated by ratio with the value of the monitoring period length to obtain the data loss duration ratio.

4. The method, system and storage medium for monitoring the status of industrial Internet devices according to claim 1, characterized in that: In step 3, the method for obtaining the data fluctuation value is as follows: During the monitoring period, the data transmission rate fluctuation value and the data transmission flow fluctuation value are obtained, and the data transmission rate fluctuation value and the data transmission flow fluctuation value are added together to obtain the operation data fluctuation value.

5. The method, system and storage medium for monitoring the status of industrial Internet devices according to claim 4, characterized in that: In step 3, the process of obtaining the data transmission rate fluctuation value is as follows: The real-time data transmission rate corresponding to different time points within the data loss time is obtained, marked as the real-time data loss transmission rate, and substituted into the XY axis two-dimensional coordinate system for marking, where the X axis represents different time points, and the Y axis represents the real-time data loss transmission rate corresponding to different time points, and the marked real-time data loss transmission rate points are connected to output a data loss real-time transmission rate change curve; Based on the data loss real-time transmission rate change curve, the coordinates of the marked data loss real-time transmission rate points are marked as ( , ), obtain the coordinates of the two adjacent peak points and the coordinates of the trough points, and mark the coordinates of the two adjacent peak points and the coordinates of the trough points as ( , )and( , ), through the formula: L= , calculate the peak-to-valley length value; Calculate the standard deviation of all peak-to-valley length values ​​to obtain the data transmission rate fluctuation value; How to obtain the data transmission flow fluctuation value: The real-time data transmission flow corresponding to different time points during the data loss period is obtained, and the data is substituted into the XY axis two-dimensional coordinate system for marking. The X axis represents different time points, and the Y axis represents the data transmission flow corresponding to different time points. The marked real-time data transmission flow points are connected to output a real-time data transmission flow change curve. Based on the real-time data transmission flow rate change curve, the data transmission flow rate fluctuation value is outputted through the above-mentioned data transmission rate fluctuation value processing method.

6. The method, system and storage medium for monitoring the status of industrial Internet devices according to claim 1, characterized in that: In step 4, the method for obtaining the stable value of data operation is as follows: The loss degree impact value and the transmission fluctuation impact value are obtained, and the loss degree impact value and the transmission fluctuation impact value are added together to obtain a data operation stability value.

7. The method, system and storage medium for monitoring the status of industrial Internet devices according to claim 6, characterized in that: In step 4, the process of obtaining the value of the amount of data loss is as follows: In the monitoring cycle, the monitoring cycle is divided into several monitoring sub-cycles, the number of data losses in each monitoring sub-cycle is obtained, marked as the sub-cycle data loss number, and the number of data losses in all sub-cycles is added and averaged to obtain the average value of the data loss number; Subtract the sub-period data loss number from the average data loss number, take the absolute value, and obtain the sub-period data number deviation value; calculate the ratio of the sub-period data number deviation value to the average data loss number, and obtain the sub-period data deviation coefficient; Calculate the standard deviation of all sub-period data deviation coefficients to obtain the value of the degree of data loss; The process of obtaining the data loss time degree value is as follows: In the monitoring cycle, the monitoring cycle is divided into several monitoring sub-cycles, the duration of data loss in each monitoring sub-cycle is obtained, and marked as the sub-cycle data loss duration length value, and the data loss duration length values ​​of all sub-cycles are added and averaged to obtain the average data loss duration length; Subtract the sub-period data loss duration length value from the average data loss duration length value, take the absolute value, and obtain the sub-period data loss duration length deviation value; calculate the ratio of the sub-period data loss duration length deviation value to the average data loss duration length, and obtain the sub-period data loss duration length deviation coefficient; The standard deviation of the duration coefficient of data loss of all sub-periods is calculated to obtain the value of the data loss time degree.

8. The method, system and storage medium for monitoring the status of industrial Internet devices according to claim 6, characterized in that: In step 4, the transmission fluctuation impact value is obtained by: Obtaining a data transmission flow rate level value and a data transmission rate level value, adding the data transmission flow rate level value and the data transmission rate level value to obtain a transmission fluctuation impact value; The data transmission rate value is obtained as follows: In the lost time period, the lost time period is divided into several sub-time periods, a data transmission rate fluctuation value in each sub-time period is obtained, and the data transmission rate fluctuation values ​​in the sub-time periods are added and averaged to obtain a data transmission rate fluctuation average value; The data transmission rate fluctuation value in the sub-time period is subtracted from the data transmission rate fluctuation average value, and the absolute value is taken to obtain the data transmission rate fluctuation deviation value in the sub-time period; the data transmission rate fluctuation deviation value in the sub-time period is calculated by ratio with the data transmission rate fluctuation average value to obtain the data transmission fluctuation deviation coefficient in the sub-time period; Calculate the standard deviation of the data transmission fluctuation deviation coefficient of the sub-time period to obtain the data transmission rate degree value; The data transmission flow rate value is obtained as follows: In the loss time period, the loss time period is divided into several sub-time periods, a data transmission flow fluctuation value in each sub-time period is obtained, and the data transmission flow fluctuation values ​​in the sub-time periods are added and averaged to obtain a data transmission flow fluctuation average value; The data transmission flow fluctuation value in the sub-time period is subtracted from the data transmission flow fluctuation average value, and the absolute value is taken to obtain the data transmission flow fluctuation deviation value in the sub-time period. The data transmission flow fluctuation deviation value in the sub-time period is calculated by ratio with the data transmission flow fluctuation average value to obtain the data transmission flow fluctuation deviation coefficient in the sub-time period. The data transmission fluctuation deviation coefficient of the sub-time period is calculated by standard deviation to obtain the data transmission flow degree value.

9. The status monitoring system of industrial Internet equipment is characterized by: The system is used to execute the method described in any one of claims 1 to 8, and the system includes the following modules: Operation monitoring module: collects Internet device operation data in real time during the monitoring period, obtains the operation data representation value, compares it with the threshold value, and generates a signal to indicate whether the operation is abnormal; If the operation data characterization value is less than the operation data characterization threshold, an operation abnormality signal is generated; Impact analysis module: Based on the abnormal operation signal, obtain the data loss degree value, compare it with the threshold, and generate a loss degree signal; If the data loss degree value is greater than or equal to the data loss degree threshold, a large loss degree signal is generated; Loss assessment module: Based on the large loss degree signal, analyze the impact of operating data fluctuations on the data loss degree, obtain the operating data fluctuation value, compare it with the threshold, and generate an impact degree signal; If the operating data fluctuation value is greater than or equal to the operating data fluctuation threshold, a high impact signal is generated; Stability evaluation module: Based on the large impact signal, obtain the data operation stability value, compare it with the threshold, analyze the data operation stability status of the network equipment, and generate a signal whether the data operation is stable; The data operation stability value is greater than or equal to the data operation stability threshold, generating a data operation instability signal; Adjustment and optimization module: Based on the data operation instability signal, the data operation status is adjusted during the data loss period to obtain the data operation status adjustment value and complete the optimization and adjustment work; The process of obtaining the data operation status adjustment value is as follows: During the data loss period, obtain the current data running value through the formula: Calculate the data operation status adjustment value , Indicates the current data running status value. It is expressed as adjustment factor; The adjustment coefficient is obtained as follows: A data transmission flow adjustment coefficient and a data transmission rate adjustment coefficient are obtained, and the data transmission flow adjustment coefficient and the data transmission rate adjustment coefficient are added together to obtain an adjustment coefficient.

10. A storage medium for monitoring the status of an industrial Internet device, characterized in that: The storage medium stores an industrial Internet device, and when the industrial Internet device is executed by the processor, the status monitoring method of the industrial Internet device according to any one of claims 1 to 8 is implemented.

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