RAFUS comprehensive factor-based automatic control system risk assessment method and system

Abstract

The invention discloses an automatic control system risk assessment method and system based on RAFUS comprehensive factors. The method comprises the following steps: operating data based on an automatic control system; evaluating the reliability R, availability A, functionality F, use performance U of the automatic control system, the influence E of external conditions on the automatic control system and a performance index S of autonomous safety performance, and analyzing the influence of the current performance on other performances to obtain a corrected performance index; based on the corrected performance index, obtaining each single risk index, and further obtaining a comprehensive risk index of the comprehensive system; and comparing the comprehensive risk index of the comprehensive system with a preset risk grading evaluation index, and determining the comprehensive risk grade of the current system. On the basis of analyzing each unit module, risk evaluation is carried out on the overall operation performance of the system, and the problems that the hidden risk of the automatic control system is deeply hidden, and a chain from a fault to a failure is long are effectively solved.

Description

Technical Field

[0001] The invention belongs to the technical field of automatic control, and relates to a risk assessment method and system for an automatic control system based on RAFUS comprehensive factors. Background Art

[0002] The automation control system plays a vital role in smooth production. The operational reliability and practical application strategy of the control system itself have a great impact on the operational performance. Faced with the continuous upgrading and increasing diversification of automatic control systems, especially in-service automatic control systems, how to evaluate their risk status, predict the remaining life of in-service automatic control systems within acceptable risks, find out the inherent and external risk weaknesses of the system during operation, and respond in advance to avoid unexpected losses in production operations are issues that many companies are concerned about and urgently need to solve.

[0003] At present, the evaluation of the operation of automatic control systems at home and abroad is often one-sided, and only considers a limited range of aspects, such as relying solely on hardware failure rate analysis to calculate the reliability performance index of a module or unit, etc. In this way, it is generally difficult to truly and effectively reflect the overall operation risk of the automatic control system with multiple units and modules; at the same time, the influence of systematic internal and external factors such as different configurations, different application environments, different management environments, and different operating environments on the overall operation performance of each unit, module, and system. Summary of the invention

[0004] The purpose of the present invention is to solve the problem in the prior art that the operation risk of an automation control system cannot be comprehensively assessed, and to provide a risk assessment method and system for an automation control system based on RAFUS comprehensive factors.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] The risk assessment method of automated control systems based on RAFUS comprehensive factors includes:

[0007] Sort out the architecture, component composition, use and configuration environment conditions, and operating environment conditions of the automation control system to be analyzed, and obtain the operating data of the automation control system;

[0008] Based on the acquired operation data, evaluate the reliability performance R, availability A, functionality F, usage performance U, the impact of external conditions on the automation control system E and the performance index S of autonomous safety performance of the automation control system;

[0009] Based on the various performance indexes of the automated control system, analyze the impact of the current performance on other performances and obtain the corrected performance index;

[0010] Based on the revised performance index, obtain each individual risk index, and then obtain the comprehensive system comprehensive risk index;

[0011] Compare the comprehensive system risk index with the pre-set risk grading evaluation indicators to determine the comprehensive risk level of the current system.

[0012] A further improvement of the present invention is:

[0013] Furthermore, the components include: an engineer station, an operator station, a historical data station, a process control station, a process I / O card, a power supply and grounding module, a communication device, a communication network, a server and a printing device.

[0014] Furthermore, the operating data of the automation control system includes: historical fault records of the automation control system, historical disturbance records, control functions, logic functions, diagnostic functions, alarm function data of each component in the automation control system, operation logs, geographic environment information of the automation control system, and system safety protection technical measures and management measures.

[0015] Furthermore, the reliability performance R of the automation control system is evaluated, specifically:

[0016] Based on the historical fault records of the automation control system and referring to the industry's experience failure database, a reliability analysis matrix for each component is established;

[0017] Based on the reliability analysis matrix of each component, analyze and calculate the reliability R of each component 工程师站 , R 操作员站 , R 过程控制站 , R IO站 , R 通信设备 ;

[0018] Based on the connection relationship of each component, the dependency relationship between the components is determined, and then the system reliability association matrix is ​​established;

[0019] Based on the system reliability correlation matrix, the correlation factor of each component is obtained, and based on the correlation factor of each component and the reliability of each component, the current reliability index R of the system is obtained;

[0020] Furthermore, the availability A of the automation control system is evaluated, specifically:

[0021] Based on the historical disturbance records of the automation control system and referring to the industry's experience misoperation database, an availability analysis matrix is ​​constructed;

[0022] Based on the availability analysis matrix of each component, analyze and calculate the availability A of each component 工程师站 , A 操作员站 , A 过程控制站, A IO站 and A 通信设备 ;

[0023] Based on the connection relationship of each component, the dependency relationship between the components is determined, and then the system availability association matrix is ​​established;

[0024] Based on the system availability association matrix, the association factor of each component is obtained, and based on the weight coefficient of each component and the association factor of each component, the current availability index A of the system is obtained.

[0025] Furthermore, the functionality F of the automation control system is evaluated as follows:

[0026] Based on the control function, logic function, diagnostic function, and alarm function data formed after the various components of the automation control system are combined with each other, a system functional analysis matrix is ​​constructed;

[0027] Based on the system functional analysis matrix and the functional reliability F based on historical data or expert opinions R , Functional availability A Conduct assessments;

[0028] Set the correlation factors and weight coefficients between various functions to obtain the current functionality index F of the system;

[0029] Furthermore, the performance U of the automation control system is evaluated as follows:

[0030] Establish system performance analysis matrix based on the operation log of the automation control system;

[0031] Based on the system performance analysis matrix and the reliability U based on historical data or expert opinions R , Usability A Conduct assessments;

[0032] Analyze the performance coefficient of each factor, set the correlation factor and weight coefficient between each factor, and obtain the current performance index U of the system.

[0033] Furthermore, the impact of external conditions on the automation control system is evaluated as follows:

[0034] Based on the geographical environment information and operating environment information of the location of the automation control system, an analysis matrix of the system's external influencing conditions is constructed;

[0035] Based on the system external impact condition analysis matrix, set the performance impact coefficient of each environmental indicator to obtain the current external impact condition index E;

[0036] The performance index S for evaluating the autonomous safety performance of the automated control system is:

[0037] Construct an independent safety performance analysis matrix based on system security protection technical measures and management measures;

[0038] Analyze system vulnerability S based on autonomous safety performance analysis matrix C , Safety protection S L， And analyze and calculate the current autonomous safety index S of the system.

[0039] Furthermore, based on each performance index of the automated control system, the influence of the current performance on other performances is analyzed to obtain a corrected performance index, specifically: based on the influence of the current index on other indexes, an association network of the current index to other indexes is constructed; in the association network, each component forms a group of association factor groups relative to each index, which are then multiplied by the weight coefficient of the component to form a group of correction coefficient groups; thereby obtaining a set of correction coefficient groups for each component of the system to each index; selecting any index from among the indexes, and in each correction coefficient group, adding and averaging the correction coefficients of the selected index to obtain the correction coefficient of the current index to any index in the indexes, and then multiplying it by the value of the selected index to obtain the correction value of the selected index after correction by the current index; similarly, obtaining the correction values ​​of each index after correction by the current index.

[0040] Furthermore, based on the revised performance index, each individual risk index is obtained, and then the comprehensive system comprehensive risk index is obtained, specifically: the weighted average of the revised index is taken to obtain each individual risk index; the relative importance of each individual risk factor is determined based on the expert scoring method, historical data analysis method and questionnaire survey method, and the weight coefficient is allocated accordingly; the comprehensive risk index is calculated by multiplying each individual risk index by the corresponding weight coefficient and then summing them up.

[0041] The automated control system risk assessment system based on RAFUS comprehensive factors includes:

[0042] A first acquisition module, which sorts out the architecture, component composition, use and configuration environment conditions, and operating environment conditions of the automation control system to be analyzed, and acquires operating data of the automation control system;

[0043] An evaluation module, which evaluates the reliability performance R, availability A, functionality F, usage performance U, impact E of external conditions on the automation control system, and performance index S of autonomous safety performance of the automation control system based on the acquired operation data;

[0044] A second acquisition module, wherein the second acquisition module analyzes the influence of the current performance on other performances based on various performance indexes of the automatic control system and acquires a corrected performance index;

[0045] A third acquisition module, which acquires each individual risk index based on the corrected performance index, and then acquires a comprehensive system comprehensive risk index;

[0046] The comparison module compares the comprehensive risk index of the comprehensive system with the pre-set risk classification evaluation index to determine the comprehensive risk level of the current system.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] The present invention comprehensively considers various possible and potential risk factors that affect the stable operation of the automatic control system, and makes a risk assessment of the overall operating performance of the system based on the analysis of each unit module, so as to intuitively reflect the overall risk status of the system and the impact on production operation; it effectively solves the problems of hidden risks, long fault-to-failure chain, and diversified development paths that are difficult to track and lock under the increasingly complex trend of automated control systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0050] Figure 1 It is a schematic flow chart of the risk assessment method of the automated control system based on the RAFUS comprehensive factor of the present invention;

[0051] Figure 2 It is a structural schematic diagram of the risk assessment system of the automated control system based on RAFUS comprehensive factors of the present invention;

[0052] Figure 3 Schematic diagram of comprehensive risk factors for comprehensive risk assessment of automatic control systems. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0054] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. 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.

[0055] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0056] In the description of the embodiments of the present invention, it should be noted that if the terms "upper", "lower", "horizontal", "inner", etc. indicate an orientation or positional relationship based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship in which the product of the invention is usually placed when in use, it is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In addition, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0057] In addition, if the term "horizontal" appears, it does not mean that the component must be absolutely horizontal, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", which does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0058] In the description of the embodiments of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal connection of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0059] The present invention is further described in detail below in conjunction with the accompanying drawings:

[0060] See also Figure 1 The present invention discloses a risk assessment method for an automated control system based on RAFUS comprehensive factors, comprising:

[0061] S101, sorting out the architecture, component composition, use and configuration environment conditions, and operating environment conditions of the automation control system to be analyzed, and obtaining operating data of the automation control system;

[0062] The components include: engineer station, operator station, historical data station, process control station, process I / O card, power supply and grounding module, communication equipment, communication network, server and printing equipment.

[0063] The operating data of the automation control system, specifically: historical fault records of the automation control system, historical disturbance records, control functions, logic functions, diagnostic functions, alarm function data of each component in the automation control system, operation logs, geographical environment information of the automation control system, and system safety protection technical measures and management measures.

[0064] S102, based on the acquired operation data, evaluate the reliability performance R, availability A, functionality F, usage performance U, impact E of external conditions on the automation control system, and performance index S of autonomous safety performance of the automation control system;

[0065] Evaluate the reliability performance R of the automation control system, specifically:

[0066] Based on the historical fault records of the automation control system and referring to the industry's experience failure database, a reliability analysis matrix for each component is established;

[0067] Taking the reliability block diagram method as an example, a reliability block diagram is drawn based on the series-parallel relationship between structures. The reliability of a single structural component is R = e -λt , where λ is the failure rate and t is the time; the reliability of the series structure is R=R1*R2, and the reliability of the parallel structure is R=R1+R2-R1*R2; and so on, the reliability analysis matrix of each component is established;

[0068] Based on the reliability analysis matrix of each component, analyze and calculate the reliability R of each component 工程师站 , R 操作员站 , R 过程控制站 , R IO站 , R 通信设备 ;

[0069] Based on the connection relationship of each component, the dependency relationship between the components is determined, and then the system reliability association matrix is ​​established;

[0070] Based on the system reliability correlation matrix, the correlation factor of each component is obtained, and based on the correlation factor of each component and the reliability of each component, the current reliability index R of the system is obtained;

[0071] Evaluate the availability A of the automation control system, specifically:

[0072] Based on the historical disturbance records of the automation control system and referring to the industry's experience misoperation database, an availability analysis matrix is ​​constructed;

[0073] Among them, the availability of a single structural component is A = MTBF / (MTBF+MTTR). If MTBF = 1 / λ, MTTR = t, then A = 1 / (1+λt); the availability of the series structure is A = A1*A2, and the availability of the parallel structure is A = A1+A2-A1*A2. Based on the structural relationship of the automation control system, an availability analysis matrix is ​​constructed;

[0074] Based on the availability analysis matrix of each component, analyze and calculate the availability A of each component 工程师站 , A 操作员站 , A 过程控制站 , A IO站 and A 通信设备 ;

[0075] Based on the connection relationship of each component, the dependency relationship between the components is determined, and then the system availability association matrix is ​​established;

[0076] Based on the system availability association matrix, the association factor of each component is obtained, and based on the weight coefficient of each component and the association factor of each component, the current availability index A of the system is obtained.

[0077] The functionality F of the automation control system is evaluated as follows:

[0078] Construct a system functional analysis matrix based on the control function, logic function, diagnostic function, and alarm function data of each component of the automation control system;

[0079] For a certain functional circuit, clarify the components used in the function and the failure rate λ of the components related to the function. F , functional reliability of a single structural component F R =e -λFt , functional availability F A =1 / (1+λ F t). Analyze the relationship between functional components (series, parallel, conditional trigger, etc.). Draw a reliability block diagram, and calculate the functional reliability F for functions with components in series relationship. R =F R1 *F R2 For functions in which components are connected in parallel, the functional reliability F R =F R1 +F R2 -F R1 *F R2 Draw an availability block diagram and calculate the functional availability F for functions with serial components. A =F A1 *F A2 For functions with parallel components, the functional availability F A =F A1 +F A2-F A1 *F A2 By analogy, a series of calculation formulas for hybrid structure functional reliability and functional availability can be constructed.

[0080] Based on the system functional analysis matrix and the functional reliability F based on historical data or expert opinions R , Functional availability A Conduct assessments;

[0081] Set the correlation factors and weight coefficients between various functions to obtain the current functionality index F of the system;

[0082] Among them, the control function, logic function, diagnosis function, and alarm function are analyzed for system correlation weights respectively, and the weight coefficient β takes any value between 0 and 1, 1 means strong correlation, and 0 means no correlation;

[0083] System current functionality index F = β R控制 (∑F R控制n ) / n+β R逻辑 (∑F R逻辑n ) / n+β R诊断 (∑F R诊断n ) / n+β R报警 (∑F R报警n ) / n+β A控制 (∑F A控制n ) / n+β A逻辑 (∑F A逻辑n ) / n+β A诊断 (∑F A诊断n ) / n+β A报警 (∑F A报警n ) / n.

[0084] The specific performance U of the automation control system is evaluated as follows:

[0085] Establish system performance analysis matrix based on the operation log of the automation control system;

[0086] Based on the system performance analysis matrix and the reliability U based on historical data or expert opinions R , Usability A Conduct assessments;

[0087] Assume that the reliability of the evaluation item is M. R , if a reliability score R is used p1 , which uses the reliability score U R1 =R p1 / M R1 . Assume that the evaluation item uses the availability full M A , if an item has a usability score of A p1 , the item uses the availability score UA1 =A p1 / M A1 The following is an example (expert experience + historical data):

[0088]

[0089] Analyze the performance coefficient of each factor, and set the correlation factor and weight coefficient between each factor to obtain the current performance index U of the system;

[0090] U=∑(θ Rn R pn / M Rn ) / ∑θ Rn +∑(θ An A pn / M An ) / ∑θ An

[0091] Among them, θ R is the weight coefficient of reliability; θ A is the weight coefficient for usage availability.

[0092] The impact of external conditions on the automation control system is evaluated as follows:

[0093] Based on the geographical environment information and operating environment information of the location of the automation control system, an analysis matrix of the system's external influencing conditions is constructed;

[0094] Based on the system external impact condition analysis matrix, the performance impact coefficient of each environmental indicator is set to obtain the current external impact condition index E.

[0095] Suppose that the full score of an environmental assessment item is M E , if the score is E p , the impact coefficient л, then the current environmental impact index of the system E=∑(л n E pn / M En ) / ∑л n . Where n represents the number of evaluation items.

[0096] The performance index S for evaluating the autonomous safety performance of the automated control system is:

[0097] Construct an independent safety performance analysis matrix based on system security protection technical measures and management measures;

[0098] Technical measures include usage control, authorization control, resource availability, data confidentiality, data transmission control, anti-tampering, timely response, etc. Select a component of the system, analyze the vulnerabilities of usage control (such as illegal intrusion, data tampering, etc.), and derive the system usage control vulnerability score S based on expert experience and industry consensus / standards. C使用控制 , analyze the specific measures taken by the system in terms of usage control, such as behavior monitoring, etc., and derive the protectiveness score S of the system's usage control based on expert experience and industry consensus / standards L使用控制 , the system uses control autonomous safety S 使用控制 =S C使用控制 / S L使用控制 By analogy, we can get the system S 授权控制 =S C授权控制 / S L授权控制 , S 资源可用 =S C资源可用 / S L资源可用 , S 数据保密 =S C数据保密 / S L数据保密 , S 传输控制 =S C传输控制 / S L传输控制 , S 防篡改 =S C防篡改 / S L防篡改 , S 及时响应 =S C及时响应 / S L及时响应 .

[0099] Analyze system vulnerability S based on autonomous safety performance analysis matrix C , Safety protection S L， And analyze and calculate the current autonomous safety index S of the system.

[0100] The current autonomous safety index of the system S = (S 使用控制 +S 授权控制 +S 资源可用 +S 数据保密 +S 传输控制 +S 防篡改 +S 及时响应 .

[0101] S103, based on each performance index of the automatic control system, analyzing the influence of the current performance on other performances, and obtaining a corrected performance index;

[0102] Based on the influence of the current index on other indexes, a correlation network of the current index to other indexes is constructed; in the correlation network, each component forms a group of correlation factor groups relative to each index, which are then multiplied by the weight coefficient of the component to form a group of correction coefficient groups; thus, a set of correction coefficient groups for each component of the system to each index is obtained; any index among the indexes is selected, and in each correction coefficient group, the correction coefficients of the selected index are summed and averaged to obtain the correction coefficient of the current index to any index among the indexes, and then multiplied by the value of the selected index to obtain the correction value of the selected index after correction by the current index; similarly, the correction values ​​of each index after correction by the current index are obtained.

[0103] S104, based on the modified performance index, obtaining each individual risk index, and then obtaining the comprehensive system comprehensive risk index;

[0104] The weighted average of the revised index is taken to obtain each individual risk index; the relative importance of each individual risk factor is determined based on the expert scoring method, historical data analysis method and questionnaire survey method, and the weight coefficient is allocated accordingly; the comprehensive risk index is calculated by multiplying each individual risk index by the corresponding weight coefficient and then summing them up.

[0105] S105, compare the comprehensive system risk index with the pre-set risk classification evaluation index to determine the comprehensive risk level of the current system

[0106] See also Figure 2 The present invention discloses a risk assessment system for an automated control system based on RAFUS comprehensive factors, comprising:

[0107] A first acquisition module, which sorts out the architecture, component composition, use and configuration environment conditions, and operating environment conditions of the automation control system to be analyzed, and acquires operating data of the automation control system;

[0108] An evaluation module, which evaluates the reliability performance R, availability A, functionality F, usage performance U, impact E of external conditions on the automation control system, and performance index S of autonomous safety performance of the automation control system based on the acquired operation data;

[0109] A second acquisition module, wherein the second acquisition module analyzes the influence of the current performance on other performances based on various performance indexes of the automatic control system and acquires a corrected performance index;

[0110] A third acquisition module, which acquires each individual risk index based on the corrected performance index, and then acquires a comprehensive system comprehensive risk index;

[0111] The comparison module compares the comprehensive risk index of the comprehensive system with the pre-set risk classification evaluation index to determine the comprehensive risk level of the current system.

[0112] Example:

[0113] The present invention discloses a risk assessment method for an automated control system based on a RAFUS comprehensive factor, comprising:

[0114] Step 1: Select the automation control system to be analyzed, and clarify basic information, functionality, manufacturers and services, personnel completeness, document completeness, etc.

[0115] Step 2: Sort out the system architecture, component composition (engineer station, operator station, historical data station, process control station (device), process I / O card, power supply and grounding module (power supply module, grounding module), communication equipment (switches, routers), communication network, server, printing equipment, etc.), use and configuration environment conditions, operating environment conditions and other information;

[0116] Step 3: Construct the factor analysis matrix and calculate the index. Specifically include:

[0117] See also Figure 3 , R (reliability performance): historical fault records + experience failure database -> establish reliability analysis matrix -> analyze and calculate R 工程师站 , R 操作员站 , R 过程控制站 , R IO站 , R 通信设备 Etc. -> Establish system reliability correlation matrix -> Set correlation factor + R weight coefficient of each component -> Analyze and calculate the current reliability index R of the system.

[0118] A (Availability): Historical disturbance records + empirical misoperation database -> Establish availability analysis matrix -> Calculate A 工程师站 , A 操作员站 , A 过程控制站 , A IO站 , A 通信设备 Etc. -> Establish system availability correlation matrix -> Set the correlation factor + A weight coefficient of each component -> Analyze and calculate the current availability index A of the system.

[0119] F (Functionality): List of control functions + logic functions + diagnostic functions + alarm functions, etc. -> Establish system functional analysis matrix -> Analyze functional reliability F R , Functional availability A ——>Set the correlation factor between every two functions + F weight coefficient——>Analyze and calculate the current functionality index F of the system.

[0120] U (usage performance): collect usage date + user + spare parts status + maintenance (cycle / tool / procedure / response requirements) -> establish system usage performance analysis matrix -> analyze usage reliability U R , Usability A ——>Analyze the performance coefficient of each factor——>Set the correlation factor + U weight coefficient between each factor——>Analyze and calculate the current performance index U of the system.

[0121] E (external influencing conditions): Collect the geographical environment information (altitude, average air pressure, extreme temperature, thunderstorm / electricity frequency) + operating environment information (temperature, humidity, pressure, dust, radiation, etc.) where the system operates - > establish a system external influencing condition analysis matrix - > analyze and set the performance impact coefficient of each environmental indicator - > analyze and calculate the current external influencing condition index E of the system.

[0122] S (Autonomous safety performance): Collect system security protection technical measures + management measures -> Establish an autonomous safety performance analysis matrix -> Analyze system vulnerabilities S C , Safety protection S L ——>Analyze and calculate the current autonomous safety index S of the system.

[0123] Step 4: Construct a comprehensive factor multidimensional analysis network and calculate the system comprehensive risk index.

[0124] R correction: Establish the correlation network of reliability index R to other indexes A, F, U, E, S -> Analyze the correlation factor of reliability index R to other indexes A, F, U, E, S + determine the correction coefficient -> Calculate the index A after the reliability index R is corrected Rmod 、F Rmod , U Rmod 、E Rmod , S Rmod The value range of the correlation factor is set to 0 to 1, 0 for no correlation, 1 for strong correlation, and the intermediate value is set according to the correlation density. The minimum value of the R correlation factor is the smallest computing component / unit of the system, which is the same as R in step 3. 工程师站 , R 操作员站 Correspondingly, each component forms a set of correlation factors for each index A, F, U, E, S, and then multiplies it by the R weight coefficient of the component to form a set of correction coefficients. By analogy, we can get the correction coefficient set of each component of the system for each index A, F, U, E, S. The correction coefficient of A in each correction coefficient group is added and averaged to calculate the correction coefficient of reliability index R to A, and then multiplied by the value of availability index A to get the index A after the reliability index R is corrected. Rmod ; Similarly, calculate the reliability index R after the correction of each index F Rmod , U Rmod、E Rmod , S Rmod .

[0125] A correction: Establish the correlation network of availability index A to other indexes R, F, U, E, S -> Analyze the correlation factor of availability index A to other indexes R, F, U, E, S + determine the correction coefficient -> Calculate the index R after availability index A is corrected Amod 、F Amod , U Amod 、E Amod , S Amod The range of the association factor is the same as above. The minimum assignment object of the A association factor is the smallest computing component / unit of the system, which is the same as A in step 3. 工程师站 , A 操作员站 Correspondingly, each component forms a set of correlation factors for each index R, F, U, E, S, and then multiplies it by the A weight coefficient of the component to form a set of correction coefficients. By analogy, we can get the set of correction coefficients for each component of the system for each index R, F, U, E, S. The R correction coefficients in each correction coefficient group are added and averaged to calculate the correction coefficient of the availability index A to R, and then multiplied by the value of the reliability index R to get the index R after the availability index A is corrected. Amod ; Similarly, calculate the availability index A after the correction of each index F Amod , U Amod 、E Amod , S Amod .

[0126] F correction: Establish the correlation network of functional index F to other indexes R, A, U, E, S -> Analyze the correlation factor of functional index F to other indexes R, A, U, E, S + determine the correction coefficient -> Calculate the index R after functional index F is corrected Fmod , A Fmod , U Fmod 、E Fmod , S Fmod . The assignment range of the correlation factor is the same as above. The minimum assignment object of the F correlation factor is the functional loop of the system, which corresponds to the functions in the list of control function + logic function + diagnostic function + alarm function in step 3. Each functional loop forms a set of correlation factor groups for each index R, A, U, E, S, and then multiplies it by the F weight coefficient of the function to form a set of correction coefficient groups. By analogy, a set of correction coefficient groups for each function of the system for each index R, A, U, E, S can be obtained. The R correction coefficients in each correction coefficient group are added and averaged to calculate the correction coefficient of the functional index F to R, and then multiplied by the value of the reliability index R to obtain the index R after the functional index F is corrected. Fmod Similarly, calculate the functional index F after the correction of each index A Fmod, U Fmod 、E Fmod , S Fmod。

[0127] U correction: Establish the correlation network of the performance index U to other indexes R, A, F, E, S -> Analyze the correlation factors of the performance index U to other indexes R, A, F, E, S + determine the correction coefficient -> Calculate the index R after the performance index U is corrected Umod , A Umod 、F Umod 、E Umod , S Umod . The value range of the correlation factor is the same as above. The minimum value assignment object of the U correlation factor is the usage factor of the system, which corresponds to the usage date + user + spare parts status + maintenance and inspection in step 3. Each factor forms a set of correlation factor groups for each index R, A, F, E, S, and then multiplied by the U weight coefficient of the factor to form a set of correction coefficient groups. By analogy, we can get a set of correction coefficient groups for each element of the system for each index R, A, F, E, S. By adding and averaging the R correction coefficients in each correction coefficient group, we can calculate the correction coefficient of the usage performance index U to R, and then multiply it by the value of the reliability index R to get the index R after the usage performance index U is corrected. Umod ; Similarly, calculate the various indexes A after using the performance index U to correct Umod 、F Umod 、E Umod , S Umod .

[0128] E correction: Establish the correlation network of external influence condition index E to other indexes R, A, F, U, S -> Analyze the correlation factor of external influence condition index E to other indexes R, A, F, U, S + determine the correction coefficient -> Calculate the indexes R after the correction of external influence condition index E Emod , A Emod 、F Emod , U Emod , S Emod . The value range of the correlation factor is the same as above. The minimum value assignment object of the E correlation factor is the environmental condition element of the system, which corresponds to the geographical environment + operating environment in step 3. Each element forms a set of correlation factor groups for each index R, A, F, U, S, and then multiplied by the environmental indicator performance impact coefficient to form a set of correction coefficient groups. By analogy, we can get a set of correction coefficient groups for each element of the system for each index R, A, F, U, S. By adding and averaging the R correction coefficients in each correction coefficient group, we can calculate the correction coefficient of the external influence condition index E to R, and then multiply it by the value of the reliability index R to get the corrected index R of the external influence condition index E. Emod Similarly, calculate the index A after the external influence condition index E is correctedEmod 、F Emod , U Emod , S Emod .

[0129] S correction: Establish the correlation network of autonomous safety performance index S to other indexes R, A, F, U, E -> Analyze the correlation factors of autonomous safety performance index S to other indexes R, A, F, U, E + determine the correction coefficient -> Calculate the indexes R after the autonomous safety performance index S is corrected Smod , A Smod 、F Smod , U Smod 、E Smod . The value range of the correlation factor is the same as above. The minimum value assignment object of the S correlation factor is the system's safety measures, which corresponds to the technical measures + management measures in step 3. Each measure forms a set of correlation factor groups for each index R, A, F, U, and E, and then multiplies it by the influence coefficient of the measure to form a set of correction coefficient groups. By analogy, we can get a set of correction coefficient groups for each measure of the system for each index R, A, F, U, and E. By adding and averaging the R correction coefficients in each correction coefficient group, we can calculate the correction coefficient of the autonomous safety performance index S to R, and then multiply it by the value of the reliability index R to get the corrected index R of the autonomous safety performance index S. Smod ; Similarly, calculate the index A after the autonomous safety performance index S is corrected Smod 、F Smod , U Smod 、E Smod .

[0130] Take the weighted average of the revised index and calculate the individual risk index R risk , A risk 、F risk , U risk 、E risk and S risk .

[0131] in,

[0132] R risk =(R+R Amod +R Fmod +R Umod +R Emod +R Smod ) / 6

[0133] A risk =(A+A Rmod +A Fmod +A Umod +A Emod +A Smod ) / 6

[0134] Frisk =(F+F Rmod +F Amod +F Umod +F Emod +F Smod ) / 6

[0135] U risk =(U+U Rmod +U Amod +U Fmod + U Emod +U Smod ) / 6

[0136] E risk =(E+E Rmod +E Amod +E Fmod + E U mod +E Smod ) / 6

[0137] S risk =(S+S Rmod +S Amod +S Fmod + S Umod +S Emod ) / 6

[0138] Based on the expert scoring method, historical data analysis method and questionnaire survey method, the relative importance of each individual risk factor is determined, and the weight coefficient is assigned accordingly. The comprehensive risk index is calculated by multiplying each individual risk index by the corresponding weight coefficient and then summing them up. According to the calculated comprehensive risk index, it is compared with the defined risk level range to determine the comprehensive risk level of the system.

[0139] According to the risk standards of national regulations, industry experience data and the actual operation of enterprises, the risk is divided into 4 levels as an example: Grade A (major risk): indicates that the risk is extremely high, and once it occurs, it will cause major losses or serious impacts to the enterprise; the threshold score is set to 80 points. When the comprehensive risk index exceeds 80 points, the system is currently considered to be in Grade A. Grade B (relatively high risk): indicates that the risk is relatively high and needs to be paid close attention to and corresponding measures are taken for management and control; the threshold score interval is set to 50-80 points. When the comprehensive risk index exceeds 50 points and does not exceed 80 points, the system is currently considered to be in Grade B. Grade C (general risk): indicates that the risk is moderate and needs to be monitored regularly and appropriate preventive measures are taken; the threshold score interval is set to 30-50 points. When the comprehensive risk index exceeds 30 points and does not exceed 50 points, the system is currently considered to be in Grade C. Grade D (low risk): indicates that the risk is relatively low, but it still needs to be paid attention to in order to prevent the risk from escalating; the threshold score is set to 30 points. When the comprehensive risk index does not exceed 30 points, the system is currently considered to be in Grade D.

[0140] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. The automated control system risk assessment method based on RAFUS comprehensive factors is characterized by: include: Sort out the architecture, component composition, use and configuration environment conditions, and operating environment conditions of the automation control system to be analyzed, and obtain the operating data of the automation control system; Based on the acquired operation data, evaluate the reliability performance R, availability A, functionality F, usage performance U, the impact of external conditions on the automation control system E and the performance index S of autonomous safety performance of the automation control system; Based on the various performance indexes of the automated control system, analyze the impact of the current performance on other performances and obtain the corrected performance index; Based on the revised performance index, obtain each individual risk index, and then obtain the comprehensive system comprehensive risk index; Compare the comprehensive system risk index with the pre-set risk grading evaluation indicators to determine the comprehensive risk level of the current system.

2. The automated control system risk assessment method based on RAFUS comprehensive factors according to claim 1 is characterized in that: The components include: an engineer station, an operator station, a historical data station, a process control station, a process I / O card, a power supply and grounding module, a communication device, a communication network, a server and a printing device.

3. The automated control system risk assessment method based on RAFUS comprehensive factors according to claim 1 is characterized in that: The operating data of the automation control system specifically includes: historical fault records of the automation control system, historical disturbance records, control functions, logic functions, diagnostic functions, alarm function data of each component in the automation control system, operation logs, geographic environment information of the automation control system, and system safety protection technical measures and management measures.

4. The automated control system risk assessment method based on RAFUS comprehensive factors according to claim 3 is characterized in that: Evaluate the reliability performance R of the automation control system, specifically: Based on the historical fault records of the automation control system and referring to the industry's experience failure database, a reliability analysis matrix for each component is established; Based on the reliability analysis matrix of each component, analyze and calculate the reliability R of each component 工程师站 , R 操作员站 , R 过程控制站 , R IO站 , R 通信设备 ; Based on the connection relationship of each component, the dependency relationship between the components is determined, and then the system reliability association matrix is ​​established; Based on the system reliability correlation matrix, the correlation factor of each component is obtained, and based on the correlation factor of each component and the reliability of each component, the current reliability index R of the system is obtained; Evaluate the availability A of the automation control system, specifically: Based on the historical disturbance records of the automation control system and referring to the industry's experience misoperation database, an availability analysis matrix is ​​constructed; Based on the availability analysis matrix of each component, analyze and calculate the availability A of each component 工程师站 , A 操作员站 , A 过程控制站 , A IO站 and A 通信设备 ; Based on the connection relationship of each component, the dependency relationship between the components is determined, and then the system availability association matrix is ​​established; Based on the system availability association matrix, the association factor of each component is obtained, and based on the weight coefficient of each component and the association factor of each component, the current availability index A of the system is obtained.

5. The automated control system risk assessment method based on RAFUS comprehensive factors according to claim 4 is characterized in that: The functionality F of the automation control system is evaluated as follows: Based on the control function, logic function, diagnostic function, and alarm function data formed after the various components of the automation control system are combined with each other, a system functional analysis matrix is ​​constructed; Based on the system functional analysis matrix and the functional reliability F based on historical data or expert opinions R , Functional availability A Conduct assessments; Set the correlation factors and weight coefficients between various functions to obtain the current functionality index F of the system; The specific performance U of the automation control system is evaluated as follows: Establish system performance analysis matrix based on the operation log of the automation control system; Based on the system performance analysis matrix and the reliability U based on historical data or expert opinions R , Usability A Conduct assessments; Analyze the performance coefficient of each factor, set the correlation factor and weight coefficient between each factor, and obtain the current performance index U of the system.

6. The automated control system risk assessment method based on RAFUS comprehensive factors according to claim 5 is characterized in that: The impact of external conditions on the automation control system is evaluated as follows: Based on the geographical environment information and operating environment information of the location of the automation control system, an analysis matrix of the system's external influencing conditions is constructed; Based on the system external impact condition analysis matrix, set the performance impact coefficient of each environmental indicator to obtain the current external impact condition index E; The performance index S for evaluating the autonomous safety performance of the automated control system is: Construct an independent safety performance analysis matrix based on system security protection technical measures and management measures system; Analyze system vulnerability S based on autonomous safety performance analysis matrix C , Safety protection S L， And analyze and calculate the current autonomous safety index S of the system.

7. The automated control system risk assessment method based on RAFUS comprehensive factors according to claim 6 is characterized in that: The method analyzes the influence of the current performance on other performances based on the performance indexes of the automatic control system to obtain the corrected performance index, specifically: based on the influence of the current index on other indexes, constructs an association network of the current index to other indexes; in the association network, each component forms a group of association factors relative to each index, which are then multiplied by the weight coefficient of the component to form a group of correction coefficients; and then obtains a group of correction coefficients for each component of the system to each index; Select any index from among the various indexes, and in each correction coefficient group, add and average the correction coefficients of the selected index to obtain the correction coefficient of the current index to any index from among the various indexes, and then multiply it by the value of the selected index to obtain the correction value of the selected index after correction by the current index; Similarly, the corrected values ​​of each index after being corrected by the current index are obtained.

8. The automated control system risk assessment method based on RAFUS comprehensive factors according to claim 7 is characterized in that: The method of obtaining each individual risk index based on the revised performance index, and then obtaining the comprehensive system comprehensive risk index, is specifically: taking a weighted average of the revised index to obtain each individual risk index; Determine the relative importance of each individual risk factor based on expert scoring, historical data analysis and questionnaire survey, and assign weight coefficients accordingly; The comprehensive risk index is calculated by multiplying each individual risk index by the corresponding weight coefficient and then summing them up.

9. The automated control system risk assessment system based on RAFUS comprehensive factors is characterized by: include: A first acquisition module, which sorts out the architecture, component composition, use and configuration environment conditions, and operating environment conditions of the automation control system to be analyzed, and acquires operating data of the automation control system; An evaluation module, which evaluates the reliability performance R, availability A, functionality F, usage performance U, impact E of external conditions on the automation control system, and performance index S of autonomous safety performance of the automation control system based on the acquired operation data; A second acquisition module, wherein the second acquisition module analyzes the influence of the current performance on other performances based on various performance indexes of the automatic control system and acquires a corrected performance index; A third acquisition module, which acquires each individual risk index based on the corrected performance index, and then acquires a comprehensive system comprehensive risk index; The comparison module compares the comprehensive risk index of the comprehensive system with the pre-set risk classification evaluation index to determine the comprehensive risk level of the current system.

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