Health degree analysis method and device applied to DCS (Distributed Control System), electronic equipment and medium

Abstract

The embodiment of the invention provides a health degree analysis method and device, electronic equipment and a medium, which are mainly applied to a DCS (Distributed Control System). The method comprises the following steps: for each scoring factor of each health degree index of each specified workstation, collecting diagnosis information of each scoring factor in a specified time period; determining a score corresponding to each scoring factor according to the diagnosis information; and according to the score corresponding to each scoring factor, determining the score corresponding to each health degree index of each specified workstation. According to the embodiment of the invention, standardized evaluation of the health degree of the DCS can be realized, and the reliability is high.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of DCS system and its performance analysis, in particular to a health degree analysis method and device, and an electronic device and a medium, mainly applied to a DCS system. BACKGROUND

[0002] DCS (Distributed Control System) is a computer system for process control, which realizes the automation of parameter acquisition, analysis and control through the architecture of decentralized control and centralized management, and is widely used in industrial fields. At present, there is a lack of reliable analysis method for the health degree of DCS system. SUMMARY

[0003] In view of this, the present disclosure provides a health degree analysis method and device applied to a DCS system, and an electronic device and a medium, for at least partially solving the above technical problems.

[0004] The first aspect of the present disclosure provides a health degree analysis method applied to a DCS system, the method comprising: collecting, for each scoring factor of each health degree index of each specified workstation, diagnostic information of the each scoring factor within a specified time period; determining a score corresponding to the each scoring factor according to the diagnostic information; and determining a score corresponding to each health degree index of the each specified workstation according to the score corresponding to the each scoring factor.

[0005] The second aspect of the present disclosure provides a health degree analysis device applied to a DCS system, the device comprising: a collection module configured to collect, for each scoring factor of each health degree index of each specified workstation, diagnostic information of the each scoring factor within a specified time period; a first determination module configured to determine a score corresponding to the each scoring factor according to the diagnostic information; and a second determination module configured to determine a score corresponding to each health degree index of the each specified workstation according to the score corresponding to the each scoring factor.

[0006] The third aspect of the present disclosure provides an electronic device, comprising: a processor, a communication interface, a memory and a bus, the processor, the communication interface and the memory complete communication with each other through the bus; the memory is configured to store at least one executable instruction, the executable instruction causes the processor to perform the operation corresponding to the method of the first aspect.

[0007] The fourth aspect of the present disclosure provides a computer readable storage medium, the computer readable storage medium stores a determination machine instruction, the determination machine instruction causes the processor to execute the method of the first aspect when the processor executes the determination machine instruction

[0008] In the embodiments of the present disclosure, the diagnostic information of each scoring factor corresponding to each health index of each specified workstation in a specified time period is collected, the score of each scoring factor is determined according to the diagnostic information, and then the score of each health index corresponding to each specified workstation is determined. Different scoring factor combinations are reasonably configured for each health index, and the health score of the specified workstation is evaluated from different health index dimensions, and then the total health score of the DCS system is obtained. In this way, the standardized evaluation of the health of the DCS system is realized, and the reliability is high. Further, different automatic scoring rules are provided for different types of scoring factors, so that the health analysis process is completely automated and does not require manual operation. In particular, the time influence factor of the deduction score proportion is obtained from the occurrence time of the deduction event identified from the diagnostic information, and the deduction score proportion of the corresponding scoring factor is automatically calculated according to the time influence factor and the maximum value and the minimum value of the score of the corresponding scoring factor, and then the score of the first type of scoring factor is calculated. At the same time, the scoring condition identified from the diagnostic information is used to directly score the second type of scoring factor, so that the scoring process of each scoring factor is standardized, the complex problem is simplified, and the processing efficiency is greatly improved. In addition, in addition to giving the total score of the health of the DCS system, the scores of the health of all automated stations, the scores of the health of all operator stations, the scores of the health of all engineer stations, the scores of the health of each automated station, the scores of the health of each operator station, and the scores of the health of each engineer station are also given. Moreover, in addition to giving the scores of the system and each part, the health of the DCS system can also be graphically displayed from different dimensions. The data is clear, transparent, intuitive, and has strong readability, and has the advantages of a data complete and transparent display platform. BRIEF DESCRIPTION OF DRAWINGS

[0009] Figure 1 is a flowchart of a health analysis method applied to a DCS system according to an embodiment of the present disclosure.

[0010] Figure 2 shows an example display interface of the health of a DCS system.

[0011] Figure 3 shows a curve graph of a negative correlation relationship of an example of the present disclosure.

[0012] Figure 4 shows a relationship curve graph of a time influence factor, a maximum value of a score, a minimum value of a score, and a deduction score proportion of an example of the present disclosure.

[0013] Figure 5 is a structure diagram of a health analysis device applied to a DCS system according to an embodiment of the present disclosure.

[0014] Figure 6 Structural diagram of an electronic device according to an embodiment of the present disclosure.

[0015] List of reference numerals in the attached diagram:

[0016] 500. Health analysis device for DCS system; 510. Data acquisition module;

[0017] 520. First determining module; 530. Second determining module;

[0018] 600. Electronic devices; 602. Processors;

[0019] 604. Communication interface; 606. Memory;

[0020] 608. Bus; 610. Program. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this disclosure clearer, the following detailed description is provided with reference to the accompanying drawings and embodiments. Obviously, the described embodiments are merely some, not all, of the embodiments of this disclosure. All other technical solutions obtained by those skilled in the art based on the embodiments of this disclosure are within the scope of protection of this disclosure.

[0022] Figure 1 A flowchart illustrating a health (KPI) analysis method according to an embodiment of this disclosure is shown, which is primarily applied to DCS systems. For example... Figure 1 As shown, the method mainly includes:

[0023] In S110, for each scoring factor of each health indicator for each specified workstation, diagnostic information for each scoring factor is collected within a specified time period. The deadline for this specified time period is preferably the data collection time to ensure the real-time nature of the health analysis. Alternatively, any historical time period can be arbitrarily specified as this specified time period.

[0024] Optionally, health indicators include one or more of the following: system availability, system security, system maintenance assessment, system lifecycle, system standardization, and system authorization effectiveness. Each health indicator can contain one or more specified scoring factors, and an interface for changing these scoring factors (e.g., adding a new factor) can be set up. Scoring factors can be added or removed as needed later.

[0025] It is understood that a DCS system typically includes automation stations AS, operator stations OS, and engineer stations ES. In the present embodiment, the designated workstation preferably includes one or more of the automation stations AS, operator stations OS, and engineer stations ES of the DCS system. In addition, the diagnostic information can be collected differently for each of the automation stations AS, operator stations OS, and engineer stations ES, for example, by collecting diagnostic information from a diagnostic buffer of the CPU of each automation station AS, by using a diagnostic tool to collect diagnostic information for each operator station OS, and by using a diagnostic tool to collect diagnostic information for each engineer station ES.

[0026] Further, for the automation station, the scoring factors of the system availability of the corresponding automation station include one or more of the time synchronization condition, the station drop condition, the IO access condition, the redundancy switching condition, the newness of the firmware version, the stop and error checking mode, and the CPU communication load; the scoring factors of the system security of the corresponding automation station include one or more of the time synchronization condition and the newness of the firmware version; the scoring factors of the system maintenance evaluation of the corresponding automation station include one or more of the time synchronization condition, the station drop condition, the IO access condition, the redundancy switching condition, and the newness of the firmware version; the scoring factors of the system life cycle of the corresponding automation station include one or more of the newness of the firmware version and the newness of the hardware version; and the scoring factors of the system specification of the corresponding automation station include the time synchronization condition. For the operator station, the scoring factors of the system availability of the corresponding operator station include one or more of the time synchronization condition, the number of times of restarting the operator station, the Host / lmhost file configuration condition, the number of times of restarting the operating system, the script execution condition, the process state, the software performance, the switch communication state, the redundancy state, the communication state, and whether the archiving setting exceeds the system recommended performance; the scoring factors of the system security of the corresponding operator station include one or more of the time synchronization condition, the antivirus software installation state, and the patch package installation condition; the scoring factors of the system maintenance evaluation of the corresponding operator station include one or more of the time synchronization condition and the number of times of restarting the operator station; the scoring factors of the system life cycle of the corresponding operator station include one or more of the software version and the operating system version; the scoring factors of the system specification of the corresponding operator station include one or more of the time synchronization condition, the Host / lmhost file configuration condition, the compatibility condition, whether the archiving setting exceeds the system recommended performance, the software performance, and the redundancy configuration; and the scoring factors of the system authorization validity of the corresponding operator station include the authorization serial number.For the engineer station, the scoring factors corresponding to the system usability of the engineer station include one or more of the time synchronization condition, the number of restarts of the engineer station, the Host / lmhost file configuration condition, the number of restarts of the operating system, the script execution condition, the process state, the software performance, the switch communication state, the redundancy state, the communication state, and whether the archiving setting exceeds the system recommended performance; the scoring factors corresponding to the system security of the engineer station include one or more of the time synchronization condition, the installation state of the antivirus software, and the installation condition of the patch package; the scoring factors corresponding to the system maintenance evaluation of the engineer station include one or more of the time synchronization condition and the number of restarts of the engineer station; the scoring factors corresponding to the system life cycle of the engineer station include one or more of the software version and the operating system version; the scoring factors corresponding to the system standardization of the engineer station include one or more of the time synchronization condition, the Host / lmhost file configuration condition, the compatibility condition, whether the archiving setting exceeds the system recommended performance, the software performance, and the redundancy configuration; and the scoring factors corresponding to the system authorization validity of the engineer station include the authorization serial number.

[0027] Then, S120 is entered, and each scoring factor corresponding to each health index of each designated workstation is determined according to the diagnostic information.

[0028] As described above, the scoring factors include at least the first type of scoring factor and the second type of scoring factor. The aforementioned IO access condition, the station drop condition, the redundancy switching condition, the stop and error checking mode, the number of restarts of the operator station, the number of restarts of the operating system, the script execution condition, the process state, the software performance, the switch communication state, the redundancy state, the communication state, and whether the archiving setting exceeds the system recommended performance belong to the first type of scoring factor. The aforementioned time synchronization condition, the new and old condition of the firmware version, the new and old condition of the hardware version, the CPU communication load, the Host / lmhost file configuration condition, the redundancy configuration, and the authorization serial number belong to the second type of scoring factor. In actual applications, the first type of scoring factor can be configured alone, the second type of scoring factor can be configured alone, or both the first type of scoring factor and the second type of scoring factor can be configured. Moreover, different types of scoring factors correspond to different scoring rules.

[0029] Further, in S120, the scoring rule for the first type of scoring element is optionally included: identifying the deduction event in the diagnostic information corresponding to the scoring factor; after identifying the deduction event, determining the time influence factor of the deduction proportion corresponding to the scoring factor according to the time of the deduction event and the collection time; determining the deduction proportion corresponding to the scoring factor according to the time influence factor of the deduction proportion corresponding to the scoring factor, the maximum value of the score obtained for the scoring factor, and the minimum value of the score obtained for the scoring factor; obtaining the score for the scoring factor according to the deduction proportion corresponding to the scoring factor; if the deduction event is not identified, determining the score for the scoring factor as a specified score (usually full score, such as 100 points, 10 points, etc.). For example, the scoring rule for the scoring factor of the automatic station drop-out situation can include “identify whether there is drop-out information in the collected diagnostic information (EventID is compared with WarningCat: IOStationError in the knowledge base ASDiagbuffer to identify), if there is drop-out information (i.e. deduction event occurs), the score for the corresponding drop-out situation is automatically calculated according to the formula described below; otherwise, the score is 100”. For example, the scoring rule for the scoring factor of the number of Windows restarts of the operator station can include “identify whether there is Windows restart situation in the collected diagnostic information, if there is restart situation, i.e. deduction event occurs, the score for the corresponding number of Windows restarts is automatically calculated according to the formula described below; otherwise, the score is 100 points”. Other first type of scoring elements are the same.

[0030] Optionally, the aforementioned “determining the time influence factor of the deduction proportion corresponding to the scoring factor according to the time of the deduction event and the collection time” can be further implemented as: determining the time difference between the time of the deduction event corresponding to the scoring factor and the collection time according to the time of the deduction event corresponding to the scoring factor and the collection time; determining the time influence factor of the deduction proportion of each deduction event corresponding to the scoring factor according to the time difference; and determining the time influence factor of the deduction proportion corresponding to the scoring factor according to the time influence factor of the deduction proportion of each deduction event corresponding to the scoring factor. For the last step, for example, the sum of the time influence factors of the deduction proportions of all deduction events corresponding to each scoring factor can be calculated, and the sum is determined as the time influence factor of the deduction proportion corresponding to each scoring factor. And it can be understood that the disclosure is not limited to this, for example, the sum after adding an empirical coefficient to the time influence factors of the deduction proportions of all deduction events corresponding to each scoring factor can be calculated, and the sum after adding the coefficient is determined as the time influence factor of the deduction proportion corresponding to each scoring factor, etc.

[0031] Further, a preset relationship function of time influence factor and time difference can be stored in advance, and the preset relationship function can be used to determine the time influence factor of the score deduction proportion of each score deduction event corresponding to each score factor according to the time difference in S130b. For example, the preset relationship function is a negative correlation function.

[0032] For another example, the preset relationship function satisfies the following conditions: for the time difference being less than or equal to a first time length, the time influence factor is 1; for the time difference being greater than the first time length, the time influence factor is negatively correlated with the time difference. Specifically, the end time of a specified time period is the collection time, and the time length of the specified time period is m, the first time length is n, m and n are natural numbers, and the relationship formula of the negative correlation in the example can be: wherein k t represents the time difference between the occurrence time of each score deduction event corresponding to each score factor and the collection time, x t represents the time influence factor of the score deduction proportion of the score deduction event corresponding to each score factor. For example, as shown in Figure 3 , n is equal to 3 days, and m is 93 days. If the occurrence time is within 3 days, x t =1 (k t ≤3), otherwise the calculation is performed according to the proportion, and the corresponding function is For another example, taking the system availability of AS as an example, it is assumed that it contains 7 score factors of time synchronization, station drop, IO access, AS redundancy switching, firmware version, stop and error checking mode, and AS CPU communication load. The time difference k1=10 of the evaluation factor corresponding to the time synchronization indicates that it occurred once 10 days before the collection time, and is brought into the formula k2=3 indicates that it occurred once 3 days before the collection time, and is brought into the formula x2=1 (k2≤3). Therefore, the time influence factor of the score deduction proportion of the evaluation factor corresponding to the time synchronization is

[0033] Alternatively, the maximum value of the score corresponding to each score factor can be obtained by the following steps: obtaining a preset weight corresponding to each score factor; calculating the sum of the preset weights corresponding to each score factor for each health degree index; and obtaining the maximum value B i of the score corresponding to each score factor according to the preset weight corresponding to each score factor and the sum of the preset weights corresponding to each score factor. Continuing to take the system availability of AS as an example, since it contains 7 score factors of time synchronization, station drop, IO access, AS redundancy switching, firmware version, stop and error checking mode, and AS CPU communication load, i.e. i=7, the preset weight Qi For "Q1=0.1Q2=0.5, Q3=0.1, Q4=0.4, Q5=0.5, Q6=0.5, Q7=0.4", then, ∑Q i =0.1+0.5+0.1+0.4+0.5+0.5+0.4=2.5, It can be understood that the preset weight can be changed as needed.

[0034] Optionally, the aforementioned "minimum value of the score obtained for the corresponding scoring factor" can be obtained, for example, by obtaining the minimum value of the score obtained for each scoring factor according to the maximum value of the score obtained for the corresponding each scoring factor and a preset proportion coefficient γ, 0<γ<1. Further, for example, the value of the product of the maximum value of the score obtained for the corresponding each scoring factor and the preset proportion coefficient γ can be calculated, and the value of the product is taken as the minimum value of the score obtained for the corresponding each scoring factor A i .

[0035] Optionally, the aforementioned "determining the deduction proportion for the corresponding scoring factor according to the time influence factor of the deduction proportion for the corresponding scoring factor, the maximum value of the score obtained for the corresponding scoring factor, and the minimum value of the score obtained for the corresponding scoring factor" can be further implemented as: determining the total deduction proportion for the corresponding scoring factor by using a function relationship According to the time influence factor of the deduction proportion for the corresponding each scoring factor, the maximum value of the score obtained for the corresponding each scoring factor, and the minimum value of the score obtained for the corresponding each scoring factor, the total deduction proportion for the corresponding each scoring factor is determined, wherein x represents the time influence factor of the deduction proportion for the corresponding i-th scoring factor, A i represents the minimum value of the score obtained for the corresponding i-th scoring factor (min, x=1), B i represents the maximum value of the score obtained for the corresponding i-th scoring factor, y i represents the total deduction proportion for the corresponding i-th scoring factor. Continuing with the example of the time synchronization of the system availability of the aforementioned AS, the maximum value of the score obtained for the scoring factor corresponding to the time synchronization Then,

[0036] Optionally, the aforementioned "obtaining the score for the corresponding scoring factor according to the deduction proportion for the corresponding scoring factor" can be further implemented as: obtaining the score for the corresponding i-th scoring factor S i = S0-y i * S0 according to the total deduction proportion y i for the corresponding i-th scoring factor, to obtain the score S iS0represents a specified score value, which is preferably equal to a specified score value equal to the score determined for the first type of scoring factor when the deduction event is not identified, e.g. both are 100 points, 10 points, etc.

[0037] In addition, in S120, the following scoring rule for the second type of scoring element can also be optionally included: for the second type of scoring factor, identifying the scoring condition in the diagnostic information corresponding to the scoring factor, determining the score corresponding to the scoring factor as the score value matched with the scoring condition based on the identified scoring condition and the corresponding relationship between the scoring condition and the score value corresponding to the scoring factor. Wherein, the corresponding relationship between the scoring condition and the score value corresponding to each scoring factor can be pre-configured or from the reference knowledge base. For example, the scoring rule for the scoring factor of the time synchronization condition of the automation station can include "identifying whether the specified year information (e.g. 199X, 200X or 201X) is contained in the collected diagnostic information, if yes, the score is 0; otherwise, the score is 100". For the scoring factor of the time synchronization condition of the operator station, if its diagnostic information is locally collected, its scoring rule is the same as that of the time synchronization condition of the automation station; if its diagnostic information is remotely collected, its scoring rule can include "for the diagnostic information (e.g. SDT: ComputerSyncInfo.txt) collected remotely by the PC (usually the engineer station), identifying whether the time deviation values of each operator station and the PC in the diagnostic information are the same, if the time deviation values of any two operator stations and the PC are the same, the score for the scoring factor of the two operator stations is 100, otherwise the score is 0; if the time deviation value of any one operator station and the PC is different from the time deviation values of the other operator stations and the PC, the score for the scoring factor of the operator station is 0." For example, the scoring rule for the scoring factor of the Host / lmhost file configuration condition of the operator station can include "judging whether the Host and lmhost files are configured in the identified diagnostic information, i.e. whether there is content, if the Host and lmhost files are not configured, the score is 0; if only one of the Host and lmhost files is configured, the score is 50; if both the Host and lmhost files are configured, the score is 100". For example, the scoring rule for the scoring factor of the software version of the operator station can include "comparing the PCS7 version in the collected diagnostic information with the PCS7 version in the reference knowledge base, according to the corresponding LifeCycle column in the knowledge base, each row in the column corresponds to a different score value, and the value of the target row of the LifeCycle column matched with the PCS7 version in the diagnostic information is taken as the score value according to the comparison result". For example, the scoring rule for the scoring factor of the operating system version of the operator station can include "comparing the Windows system version in the collected diagnostic information with the WinCompatibility operating system compatibility knowledge base in the reference knowledge base, and directly scoring the operating system version according to the corresponding YearCurrent-YearReleased formula in the knowledge base". Other second type of scoring elements are the same.

[0038] Thereafter, S130 is entered, and scores for each health index of the each designated workstation are determined according to the scores corresponding to each scoring factor.

[0039] Alternatively, S130 can be further implemented as: determining an average value of the scores corresponding to each scoring factor as the score for each health index of the each designated workstation.

[0040] As described above, the DCS system usually includes automation stations, operator stations and engineer stations. In this embodiment, the method can further include: respectively summing up the scores of each health index of all automation stations in the corresponding DCS system to obtain the score of each health index of the corresponding automation station; and displaying the score of the health index of the corresponding automation station in a graphical manner according to the score of each health index of the corresponding automation station. The method can further include: respectively summing up the scores of each health index of all operator stations in the corresponding DCS system to obtain the score of each health index of the corresponding operator station; and displaying the score of the health index of the corresponding operator station in a graphical manner according to the score of each health index of the corresponding operator station. The method can further include: respectively summing up the scores of each health index of all engineer stations in the corresponding DCS system to obtain the score of each health index of the corresponding engineer station; and displaying the score of the health index of the corresponding engineer station in a graphical manner according to the score of each health index of the corresponding engineer station. The method can further include: respectively summing up the scores of each health index of all automation stations in the corresponding DCS system to obtain the score of each health index of the corresponding automation station; and summing up the scores of each health index of the corresponding automation station in a weighted manner according to the score of each health index of the corresponding automation station to obtain the health score of the corresponding automation station. The method can further include: respectively summing up the scores of each health index of all operator stations in the corresponding DCS system to obtain the score of each health index of the corresponding operator station; and summing up the scores of each health index of the corresponding operator station in a weighted manner according to the score of each health index of the corresponding operator station to obtain the health score of the corresponding operator station. The method can further include: respectively summing up the scores of each health index of all engineer stations in the corresponding DCS system to obtain the score of each health index of the corresponding engineer station; and summing up the scores of each health index of the corresponding engineer station in a weighted manner according to the score of each health index of the corresponding engineer station to obtain the health score of the corresponding engineer station. The method can further include: for each health index, summing up the score of the health index of the corresponding automation station, the score of the health index of the corresponding operator station and the score of the health index of the corresponding engineer station in a weighted manner to obtain the score of each health index of the corresponding DCS system; and displaying the score of each health index of the corresponding DCS system in a graphical manner according to the score of each health index of the corresponding DCS system.For example, the method can further include: for each health index, performing a weighted summation of the score of the health index of the corresponding automation station, the score of the health index of the corresponding operator station, and the score of the health index of the corresponding engineer station, to obtain a score of each health index of the DCS system; and performing a weighted summation of the scores of the health indexes of the DCS system, to obtain a health score of the DCS system. It should be noted that the embodiments can further include a new implementation mode obtained by combining any of the example implementation modes described in this paragraph. In addition, the graphical display mode in the embodiments includes, for example but not limited to, a spider chart (such as Figure 2 ), a pie chart, a radar chart, a scatter chart, a column chart, etc.

[0041] To implement the health analysis method of the DCS system in the above embodiments, other embodiments of the present disclosure further provide a health analysis device 500. As shown in Figure 5 , the device 500 includes a collection module 510, a first determination module 520, and a second determination module 530. It should be noted that since the following embodiments are to implement the foregoing method embodiments, each module in the motion control system is to implement each step of the foregoing method, and therefore the present disclosure is not limited to the following embodiments, and any device or module that can implement the foregoing method should be included in the protection scope of the present disclosure.

[0042] The collection module 510 is configured to collect, for each scoring factor of each health index of each designated workstation, diagnostic information of the scoring factor within a designated time period. The end time of the designated time period is preferably the collection time, so as to ensure the real-time performance of the health analysis; or a historical time period can be arbitrarily designated as the designated time period.

[0043] The health index includes one or more of system availability, system security, system maintenance evaluation, system life cycle, system specification, and system authorization validity. For the automation station: the scoring factors corresponding to the system availability include one or more of time synchronization, station drop, IO access, redundancy switching, firmware version, stop and error checking mode, and CPU communication load; the scoring factors corresponding to the system security include one or more of time synchronization and firmware version; the scoring factors corresponding to the system maintenance evaluation include one or more of time synchronization, station drop, IO access, redundancy switching, and firmware version; the scoring factors corresponding to the system life cycle include one or more of firmware version and hardware version; and the scoring factors corresponding to the system specification include time synchronization.

[0044] For the operator station, the scoring factors corresponding to system availability include one or more of time synchronization, number of operator station restarts, Host / lmhost file configuration, number of operating system restarts, script execution, operator station process status, operator station software performance, switch communication status, operator station redundancy status, operator station communication status, whether the archiving settings exceed the system recommended performance, and the like; the scoring factors corresponding to system security include one or more of time synchronization, antivirus software installation status, patch installation, and the like; the scoring factors corresponding to system maintenance evaluation include one or more of time synchronization, number of operator station restarts, and the like; the scoring factors corresponding to system lifecycle include one or more of software version, operating system version, and the like; the scoring factors corresponding to system specification include one or more of time synchronization, Host / lmhost file configuration, compatibility, whether the archiving settings exceed the system recommended performance, operator station software performance, operator station redundancy configuration, and the like; and the scoring factors corresponding to system authorization validity include the authorization serial number.

[0045] For the operator station, the scoring factors corresponding to system availability include one or more of time synchronization, number of operator station restarts, Host / lmhost file configuration, number of operating system restarts, script execution, process status, software performance, switch communication status, redundancy status, communication status, whether the archiving settings exceed the system recommended performance, and the like; the scoring factors corresponding to system security include one or more of time synchronization, antivirus software installation status, patch installation, and the like; the scoring factors corresponding to system maintenance evaluation include one or more of time synchronization, number of operator station restarts, and the like; the scoring factors corresponding to system lifecycle include one or more of software version, operating system version, and the like; the scoring factors corresponding to system specification include one or more of time synchronization, Host / lmhost file configuration, compatibility, whether the archiving settings exceed the system recommended performance, software performance, redundancy configuration, and the like; and the scoring factors corresponding to system authorization validity include the authorization serial number.

[0046] The first determining module 520 is configured to determine each scoring factor of each health index corresponding to each specified workstation according to the diagnostic information.

[0047] In this embodiment, the score factors include at least first type score factors and second type score factors. The IO access condition, the station drop condition, the redundancy switching condition, the stop and error checking mode, the operator station restart times, the operating system restart times, the script execution condition, the process state, the software performance, the switch communication state, the redundancy state, the communication state, and whether the archiving setting exceeds the system recommended performance belong to the first type score factors. The time synchronization condition, the firmware version, the hardware version, the CPU communication load, the Host / lmhost file configuration condition, the redundancy configuration, and the authorization serial number belong to the second type score factors.

[0048] Optionally, the first determining module 520 is further configured to, for the first type score factors, identify a deduction event corresponding to the score factor in the diagnostic information; after identifying the deduction event, determine a time influence factor of a deduction proportion corresponding to the score factor according to a time when the deduction event corresponding to the score factor occurs and the collection time; determine the deduction proportion corresponding to the score factor according to the time influence factor of the deduction proportion corresponding to the score factor, a maximum value of a score obtained by the score factor, and a minimum value of the score obtained by the score factor; obtain the score of the score factor according to the deduction proportion corresponding to the score factor; and if the deduction event is not identified, assign a specified score value to the score of the score factor.

[0049] Further, the first determining module 520 is further configured to determine a time difference between the time when the deduction event corresponding to the score factor occurs and the collection time according to the time when the deduction event corresponding to the score factor occurs and the collection time; determine a time influence factor of a deduction proportion of each deduction event corresponding to the score factor according to the time difference; and determine a sum value of the time influence factors of the deduction proportions of all deduction events corresponding to the score factor as the time influence factor of the deduction proportion corresponding to the score factor.

[0050] For example, the time influence factor is negatively correlated with the time difference. For another example, for the time difference being less than or equal to a first time length, the time influence factor is 1; for the time difference being greater than the first time length, the time influence factor is negatively correlated with the time difference. Further, the end time of the specified time period is the collection time and the time length of the specified time period is m, and the first time length is equal to n; then, the relationship formula of the negative correlation is: wherein k t represents the time difference between the time when the deduction event corresponding to each score factor occurs and the collection time, x t represents the time influence factor of the deduction proportion of the deduction event corresponding to each score factor.

[0051] Optionally, the first determining module 520 is further configured to use the formula The deduction proportion corresponding to the scoring factor is determined according to a time influence factor of the deduction proportion corresponding to the scoring factor, a maximum value of the score obtained for the scoring factor, and a minimum value of the score obtained for the scoring factor, wherein x represents the time influence factor of the deduction proportion corresponding to the i th scoring factor, A i B represents the minimum value of the score obtained for the i th scoring factor, i A represents the maximum value of the score obtained for the i th scoring factor, and y i represents the total deduction proportion corresponding to the i th scoring factor. Optionally, the first determining module 520 is further configured to obtain a preset weight corresponding to the scoring factor; calculate a sum value of the preset weights corresponding to the scoring factors for each health index; and obtain a maximum value of the score obtained for each scoring factor according to the preset weight corresponding to the scoring factor and the sum value of the preset weights corresponding to the scoring factors. Optionally, the first determining module 520 is further configured to obtain a minimum value of the score obtained for each scoring factor according to the maximum value of the score obtained for each scoring factor and a preset proportion coefficient γ, 0 < γ < 1.

[0052] In addition, optionally, the first determining module 520 is further configured to, for the second type of scoring factor, identify a scoring condition corresponding to the scoring factor in the diagnosis information; and determine the score obtained for the scoring factor as a score value corresponding to the scoring factor that matches the scoring condition.

[0053] The second determining module 530 is configured to determine the score of each health index of each designated workstation according to the score obtained for each scoring factor. For example, the second determining module 530 can be further configured to determine an average value of the score obtained for each scoring factor as the score of each health index of each designated workstation.

[0054] The DCS system usually comprises automation stations, operator stations and engineer stations. In this embodiment, the second determining module 530 is further configured to: sum up scores of each health index of all automation stations in the corresponding DCS system respectively to obtain scores of each health index of the corresponding automation station; and display the scores of the health index of the corresponding automation station graphically according to the scores of each health index of the corresponding automation station. The second determining module 530 is further configured to: sum up scores of each health index of all operator stations in the corresponding DCS system respectively to obtain scores of each health index of the corresponding operator station; and display the scores of the health index of the corresponding operator station graphically according to the scores of each health index of the corresponding operator station. The second determining module 530 is further configured to: sum up scores of each health index of all engineer stations in the corresponding DCS system respectively to obtain scores of each health index of the corresponding engineer station; and display the scores of the health index of the corresponding engineer station graphically according to the scores of each health index of the corresponding engineer station. The second determining module 530 is further configured to: sum up scores of each health index of all automation stations in the corresponding DCS system respectively to obtain scores of each health index of the corresponding automation station; and sum up the scores of each health index of the corresponding automation station to obtain a health score of the corresponding automation station according to the scores of each health index of the corresponding automation station. The second determining module 530 is further configured to: sum up scores of each health index of all operator stations in the corresponding DCS system respectively to obtain scores of each health index of the corresponding operator station; and sum up the scores of each health index of the corresponding operator station to obtain a health score of the corresponding operator station according to the scores of each health index of the corresponding operator station. The second determining module 530 is further configured to: sum up scores of each health index of all engineer stations in the corresponding DCS system respectively to obtain scores of each health index of the corresponding engineer station; and sum up the scores of each health index of the corresponding engineer station to obtain a health score of the corresponding engineer station according to the scores of each health index of the corresponding engineer station. The second determining module 530 is further configured to: sum up the scores of each health index of the corresponding automation station, the scores of each health index of the corresponding operator station and the scores of each health index of the corresponding engineer station to obtain scores of each health index of the corresponding DCS system according to each health index; and display the scores of each health index of the corresponding DCS system graphically according to the scores of each health index of the corresponding DCS system.For example, the second determining module 530 is further configured to, for each health index, sum up the score of the health index of the corresponding automation station, the score of the health index of the corresponding operator station and the score of the health index of the corresponding engineer station to obtain the score of each health index of the DCS system; and sum up the scores of the health indexes of the DCS system to obtain the health score of the DCS system. It should be noted that the present embodiment can also include a new implementation mode obtained by combining any of the example implementation modes described in this paragraph. In addition, the graphical display mode in the present embodiment may, for example, but is not limited to, a spider chart (such as Figure 2 ), a pie chart, a radar chart, a scatter chart, a column chart, etc.

[0055] It should be noted that the health analysis method of the foregoing embodiment is a method embodiment corresponding to the health analysis device 500 of the present embodiment, and the health analysis device 500 of the present embodiment can be implemented in cooperation with the health analysis method of the foregoing embodiment. The related technical details mentioned in the health analysis method of the foregoing embodiment are still valid in the health analysis device 500 of the present embodiment. In order to reduce repetition, they will not be described here.

[0056] Figure 6 FIG. 6 is a schematic diagram of an electronic device 600 according to an embodiment of the present disclosure. The present embodiment does not limit the specific implementation of the electronic device. Referring to FIG. 6, the electronic device 600 provided by the present embodiment includes a processor 602, a communications interface 604, a memory 606, and a bus 608. Figure 6

[0057] In the present embodiment, the processor 602, the communications interface 604, and the memory 606 can communicate with each other through the bus 608.

[0058] The processor 602, the communications interface 604, and the memory 606 can communicate with each other through the bus 608.

[0059] The communications interface 604 is configured to communicate with other electronic devices or servers.

[0060] The processor 602 is configured to execute the program 610, and specifically can execute the related steps in the method embodiments described above.

[0061] Specifically, the program 610 can include program code including computer operation instructions.

[0062] ​The processor 602 can be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement one or more embodiments of the present disclosure. The one or more processors included in the smart device can be the same type of processor, such as one or more CPUs, or different types of processors, such as one or more CPUs and one or more ASICs.

[0063] The memory 606 is configured to store a program 610. The memory 606 can include a high-speed RAM memory, and can further include a non-volatile memory, such as at least one disk memory.

[0064] The program 610 can be specifically configured to cause the processor 602 to perform the method in any of the foregoing embodiments.

[0065] The specific implementation of each step in the program 610 can refer to the corresponding description in the corresponding step and unit in the method embodiments described above, and will not be described herein. It can be clearly understood by those skilled in the art that, for the convenience and brevity of description, the specific working process of the device and module described above can refer to the corresponding process description in the foregoing method embodiments, and will not be described herein.

[0066] The present disclosure also provides a computer-readable storage medium storing instructions for causing a machine to perform the method described herein. Specifically, a system or device equipped with a storage medium can be provided, and the storage medium stores software program code for implementing the functions of any of the above embodiments, and causes the computer (or CPU or MPU) of the system or device to read and execute the program code stored in the storage medium.

[0067] In this case, the program code read from the storage medium itself can implement the functions of any of the above embodiments, and therefore the program code and the storage medium storing the program code constitute a part of the present disclosure.

[0068] The storage medium for providing the program code includes a floppy disk, a hard disk, a magneto-optical disk, an optical disk (such as a CD-ROM, a CD-R, a CD-RW, a DVD-ROM, a DVD-RAM, a DVD-RW, a DVD+RW), a magnetic tape, a non-volatile memory card, and a ROM. Alternatively, the program code can be downloaded from a server computer via a communication network.

[0069] The embodiments of the present disclosure also provide a computer program product, including computer instructions instructing a computing device to perform any corresponding operation in the above method embodiments.

[0070] It should be noted that, according to the needs of implementation, each component / step described in the embodiments of the present disclosure can be split into more components / steps, or two or more components / steps or partial operations of the components / steps can be combined into a new component / step, to achieve the purpose of the embodiments of the present disclosure.

[0071] The above-described method according to the embodiments of the present disclosure can be implemented in hardware, firmware, or as software or computer code that can be stored in a recording medium such as a CD ROM, a RAM, a floppy disk, a hard disk, or an optical disk, or be downloaded through a network originally stored in a remote recording medium or a non-transitory machine-readable medium and then stored in a local recording medium, so that the method described herein can be processed by such software using a general computer, a special purpose processor, or programmable or special purpose hardware (such as ASIC or FPGA). It can be understood that the computer, processor, microprocessor controller, or programmable hardware includes a storage component (for example, RAM, ROM, flash memory, etc.) that can store or receive software or computer code, when the software or computer code is accessed and executed by the computer, processor, or hardware, the method described herein is implemented. In addition, when a general computer accesses the code for implementing the method shown herein, the execution of the code will convert the general computer into a special purpose computer for executing the method shown herein.

[0072] It should be noted that not all steps and modules in the above-mentioned flowcharts and system structure diagrams are necessary, and some steps or modules can be omitted according to actual needs. The execution order of each step is not fixed and can be adjusted as needed. The system structure described in each of the above embodiments can be a physical structure or a logical structure, that is, some modules can be implemented by the same physical entity, or some modules can be implemented by multiple physical entities, or can be implemented by some components in multiple independent devices.

[0073] The pronouns and pronouns in this patent application are not limited to a specific gender. The term "includes", "contains" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or includes elements inherent to such process, method, article or device. Without more limitations, the element defined by the sentence "includes one" does not exclude the presence of another identical element in the process, method, article or device including the element.

[0074] In the above embodiments, a hardware module can be implemented mechanically or with electrical components. For example, a hardware module can include dedicated processor(s), FPGA(s), or ASIC(s) for carrying out certain operations, or it can include programmable processor(s) with a software module stored in a memory that can be temporarily configured by the software module to carry out certain operations. The manner in which the hardware module is implemented can depend on the cost and time considerations of the particular implementation.

[0075] The present disclosure has been shown and described in detail above by way of the accompanying drawings and preferred embodiments, but it will be apparent to those skilled in the art that various modifications and changes can be made without departing from the scope of the present disclosure. Based on the above embodiments, those skilled in the art can know that the different embodiments, optional implementations, or exemplary implementations described above can be combined to obtain more embodiments of the present disclosure, and these embodiments are also within the protection scope of the present disclosure.

Claims

1. A health status analysis method, applied to a DCS system, characterized in that, The method includes: For each health indicator and each scoring factor of each designated workstation, collect diagnostic information for each scoring factor within a specified time period; Based on the diagnostic information, determine the score corresponding to each scoring factor; Based on the score for each of the scoring factors, the score for each health indicator for each specified workstation is determined.

2. The method according to claim 1, characterized in that, The step of determining the score for each scoring factor based on the diagnostic information includes: For the first type of scoring factor Identify the deduction events in the diagnostic information corresponding to the scoring factors; After identifying the deduction event, the time influence factor of the deduction weight of the corresponding scoring factor is determined based on the occurrence time and collection time of the deduction event. The deduction weight of the corresponding scoring factor is determined based on the time influence factor of the deduction weight, the maximum score of the corresponding scoring factor, and the minimum score of the corresponding scoring factor. The score of the corresponding scoring factor is obtained based on the deduction weight of the corresponding scoring factor. If the deduction event is not identified, a specified score will be assigned to the score corresponding to the scoring factor.

3. The method according to claim 2, characterized in that, The step of determining the score for each scoring factor based on the diagnostic information further includes: For the second type of scoring factor Identify the scoring conditions corresponding to the scoring factors in the diagnostic information; Based on the identified scoring conditions and the correspondence between the scoring conditions and the scores of the corresponding rating factors, the score that matches the scoring conditions is determined as the score of the corresponding rating factor.

4. The method according to claim 3, characterized in that, The step of determining the score for each health indicator for each specified workstation based on the score for each of the scoring factors further includes: The average score of each scoring factor is determined as the score of each health indicator for each specified workstation.

5. The method according to claim 2, characterized in that, The step of determining the time-influence factor of the deduction weight corresponding to the scoring factor based on the occurrence time and collection time of the deduction event corresponding to the scoring factor further includes: Based on the occurrence time and collection time of the deduction event corresponding to the scoring factor, determine the time difference between the occurrence time and the collection time of the deduction event corresponding to the scoring factor; Based on the time difference, determine the time influence factor of the deduction weight of each deduction event corresponding to the scoring factor; The sum of the time-related factors of the deduction weight of all deduction events corresponding to the scoring factor is determined as the time-related factor of the deduction weight of the scoring factor.

6. The method according to claim 5, characterized in that, The time-influence factor is negatively correlated with the time difference.

7. The method according to claim 5, characterized in that, When the time difference is less than or equal to the first duration, the time influence factor is 1; when the time difference is greater than the first duration, the time influence factor is negatively correlated with the time difference.

8. The method according to claim 7, characterized in that, The deadline for the specified time period is the collection time, and the duration of the specified time period is m, where the first duration is equal to n. The formula for the negative correlation is: Where, k t x represents the time difference between the occurrence of the deduction event for each scoring factor and the data collection time. t This represents the time-related influence factor that indicates the weight of the deduction for each deduction event corresponding to each of the scoring factors.

9. The method according to claim 2, characterized in that, The step of determining the deduction weight of the corresponding scoring factor based on the time influence factor of the deduction weight of the corresponding scoring factor, the maximum score of the corresponding scoring factor, and the minimum score of the corresponding scoring factor further includes: Using formula The deduction weight of a given scoring factor is determined based on the time influence factor of the deduction weight corresponding to that scoring factor, the maximum score of that scoring factor, and the minimum score of that scoring factor, where x represents the time influence factor of the deduction weight corresponding to the i-th scoring factor, and A i B represents the minimum score for the i-th rating factor. i y represents the maximum score corresponding to the i-th rating factor. i This represents the total deduction weight corresponding to the i-th scoring factor.

10. The method according to claim 9, characterized in that, The maximum score corresponding to the scoring factor is obtained through the following steps: Obtain the preset weights corresponding to the scoring factors; For each of the health indicators, calculate the sum of the preset weights of the corresponding scoring factors; The maximum score for each scoring factor is obtained by summing the preset weights of the corresponding scoring factors and the preset weights of the corresponding scoring factors.

11. The method according to claim 10, characterized in that, The minimum score corresponding to each of the scoring factors is obtained through the following steps: Based on the maximum score of each scoring factor and the preset proportional coefficient γ, the minimum score of each scoring factor is obtained, where 0 < γ < 1.

12. The method according to any one of claims 1-11, characterized in that, The health indicators include one or more of the following: system availability, system security, system maintenance assessment, system lifecycle, system standardization, and system authorization effectiveness. The designated workstation includes one or more of the following: automation station, operator station, and engineer station.

13. The method according to claim 12, characterized in that, The method further includes: The scores of each health indicator for all automated stations in the corresponding DCS system are weighted and summed to obtain the score of each health indicator for the corresponding automated station. The scores of each health indicator for all operator stations in the corresponding DCS system are weighted and summed to obtain the score of each health indicator for the corresponding operator station. The scores of each health indicator for all engineer stations in the corresponding DCS system are weighted and summed to obtain the score of each health indicator for the corresponding engineer station.

14. The method according to claim 13, characterized in that, The method further includes: Based on the score of each health indicator of the corresponding automated station, the score of the health indicator of the corresponding automated station is displayed graphically. Based on the score of each health indicator of the corresponding operator station, the score of the health indicator of the corresponding operator station is displayed graphically. Based on the score of each health indicator of the corresponding engineering station, the score of the corresponding engineering station's health indicator is displayed graphically.

15. The method according to claim 13, characterized in that, The method further includes: Based on the score of each health indicator of the corresponding automated station, the scores of each health indicator of the corresponding automated station are weighted and summed to obtain the health score of the corresponding automated station. Based on the score of each health indicator of the corresponding operator station, the scores of each health indicator of the corresponding operator station are weighted and summed to obtain the health score of the corresponding operator station. Based on the score of each health indicator of the corresponding engineering station, the scores of each health indicator of the corresponding engineering station are weighted and summed to obtain the health score of the corresponding engineering station.

16. The method according to claim 13, characterized in that, The method further includes: For each health indicator, the scores of the corresponding automated station, the corresponding operator station, and the corresponding engineer station for that health indicator are weighted and summed to obtain the score of each health indicator for the DCS system. Based on the score of each health indicator of the corresponding DCS system, the score of each health indicator of the corresponding DCS system is graphically displayed; and / or the scores of each health indicator of the corresponding DCS system are weighted and summed to obtain the health score of the corresponding DCS system.

17. The method according to claim 12, characterized in that, For the automated station: the scoring factors corresponding to its system availability include one or more of the following: time synchronization, station failure, IO access, redundancy switching, firmware version, stop and error checking mode, and CPU communication load; the scoring factors corresponding to its system security include one or more of the following: time synchronization, firmware version; the scoring factors corresponding to its system maintenance assessment include one or more of the following: time synchronization, station failure, IO access, redundancy switching, and firmware version; the scoring factors corresponding to its system lifecycle include one or more of the following: firmware version and hardware version; the scoring factors corresponding to its system standardization include time synchronization. For either the operator station or the engineer station: the scoring factors for system availability include one or more of the following: time synchronization status, number of operator station restarts, Host / lmhost file configuration, number of operating system restarts, script execution status, process status, software performance, switch communication status, redundancy status, communication status, and whether archiving settings exceed the system's recommended performance; the scoring factors for system security include one or more of the following: time synchronization status, antivirus software installation status, and patch installation status; the scoring factors for system maintenance assessment include one or more of the following: time synchronization status and number of operator station restarts; the scoring factors for system lifecycle include one or more of the following: software version and operating system version; the scoring factors for system compliance include one or more of the following: time synchronization status, Host / lmhost file configuration, compatibility status, whether archiving settings exceed the system's recommended performance, software performance, and redundancy configuration; the scoring factor for system authorization validity includes the authorization serial number. The following are the scoring factors: IO access status, site failure status, redundancy switching status, stop and error checking mode, operator station restart count, operating system restart count, script execution status, process status, software performance, switch communication status, redundancy status, communication status, and whether the archiving settings exceed the system's recommended performance. These are the first category of scoring factors. The following are the scoring factors: time synchronization status, firmware version status, hardware version status, CPU communication load, Host / lmhost file configuration status, redundancy configuration, and authorized serial number.

18. A health analysis device for a DCS system, characterized in that, The device includes: The data acquisition module (510) is used to collect diagnostic information of each scoring factor for each health indicator of each specified workstation within a specified time period. The first determining module (520) is used to determine the score corresponding to each scoring factor based on the diagnostic information; The second determining module (530) is used to determine the score of each health indicator corresponding to each specified workstation based on the score of each of the scoring factors.

19. An electronic device (600), the electronic device (600) comprising: The processor (602), communication interface (604), memory (606), and bus (608) communicate with each other through the bus (608). The memory (606) is used to store at least one executable instruction that causes the processor (602) to perform an operation corresponding to the method as described in any one of claims 1-17.

20. A computer-readable storage medium storing deterministic machine instructions, which, when executed by a processor, cause the processor to perform the method of any one of claims 1-17.

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