Technical method for preventing misoperation of industrial control system

Abstract

The application discloses a technical method for preventing misoperation of an industrial control system, and comprises the following steps: collecting basic data of a control loop in a control system to form a control loop misoperation data set and bringing the control loop misoperation data set into an evaluation model, screening out key control loops which need secondary function development, analyzing automatic control equipment under the jurisdiction of the key control loops, determining specific research objects which need secondary function development, putting forward specific function requirements, respectively designing program flows corresponding to the requirements, building configuration programs for each specific research object through the designed program flows, compiling bottom layer logic codes, designing prompt, alarm and secondary determination function panels, finally testing the developed application functions, and perfecting the operation technical method. Through the method, the control objects which need to be developed with the misoperation prevention function can be effectively determined, misoperation accidents can be greatly reduced, great convenience can be brought to the safe and stable operation of a production device, and production and operation risks can be reduced.

Description

Technical Field

[0001] This invention relates to industrial automation anti-misoperation technology, and more particularly to a technical method for preventing misoperation in industrial control systems. Background Technology

[0002] Industrial control systems are the core of safe plant operation. Human error in these systems can lead to equipment damage, safety hazards, economic losses, and environmental pollution. Therefore, research on anti-misoperation technologies for industrial control systems is of great significance.

[0003] Currently available DCS systems do not have a dedicated anti-misoperation operating system. Production and operation units generally adopt the following approach for anti-misoperation operating system technology for industrial control systems: For various automatic control loops connected to the system, process operators remotely monitor and operate them through an operator station; For key control equipment such as manual shut-off valves and regulating valves, technical management personnel issue work tickets with clear work information (operation time, equipment location, operation instructions, etc.) after confirmation, and process operators use the corresponding work tickets to perform manual operation.

[0004] The operation and status of the aforementioned technical methods are highly dependent on the experience, condition, and subjective awareness of technical management personnel and process operators. Management and operation are time-consuming and labor-intensive. Negligence by management or fatigue among operators can lead to various misjudgments and misoperations. This technical method typically reacts with a lag to equipment failures and misoperations, failing to effectively predict and control events in advance. Failure to effectively monitor the operational status of critical control loops in real time and suppress human error will not only increase employee workload and shorten equipment lifespan but may also trigger various safety, economic, and environmental problems. Summary of the Invention

[0005] The purpose of this invention is to overcome the above-mentioned shortcomings in the prior art and to provide a technical method for preventing misoperation in industrial control systems.

[0006] To achieve the above-mentioned objectives, the present invention provides the following technical solution:

[0007] A technical method for preventing misoperation in an industrial control system includes the following steps:

[0008] Step S1: Collect basic data of all control loops under the control system to form a control loop misoperation dataset and establish a control loop information database;

[0009] Step S2: Establish a reliable evaluation model, input the control loop misoperation dataset into the evaluation model, obtain the probability and ease of control loop misoperation, and screen out the key control loops that require secondary function development.

[0010] Step S3: Analyze the automatic control equipment such as regulating valves, shut-off valves, and generator units under the control of the key control loop in sequence to determine the specific research objects that need secondary function development;

[0011] Step S4: Determine the secondary development functions required for each specific research object and propose specific functional requirements;

[0012] Step S5: Design the corresponding program flow according to the specific functional requirements;

[0013] Step S6: Based on the designed program flow, build a configuration program for each specific research object and compile the underlying logic code;

[0014] Step S7: Design the function panel to include: prompts, alarms, and secondary confirmation for whether to make changes;

[0015] Step S8: The operator gives an operation command or changes the input value to meet the alarm logic requirements, and tests the developed application function;

[0016] Step S9: Based on the feedback from the test results, return to step S3 to make corrections. Once no further feedback is received, end the loop and refine the operational techniques.

[0017] This invention provides a technical method for preventing misoperation in industrial control systems. It effectively identifies the control objects that require misoperation prevention functions and achieves fully automatic, full-lifecycle misoperation prevention technology management and operation of the industrial control system by comprehensively understanding its operating status.

[0018] Preferably, in step S1, establishing the control loop misoperation dataset includes the following steps:

[0019] S101. Through qualitative and quantitative analysis, select evaluation indicators that are easy to quantify and can help evaluate the ease of control loop misoperation, such as cumulative number of misoperations, cumulative operation time, annual number of misoperations, monthly operation frequency, frequency of relevant professional knowledge assessment, number of skilled operators, number of night operations, and cumulative losses caused by misoperation, and establish an evaluation indicator system.

[0020] S102. Collect index data for each control loop according to the indicators in the evaluation index system, and construct a data sample matrix X = (x ij ) m×n This refers to the control loop misoperation dataset, where m represents the total number of underlying evaluation indicators, n represents the total number of control loops, and x... ij This represents the index data corresponding to the i-th index and the j-th control loop, where i = 1 to m and j = 1 to n.

[0021] Preferably, in step S2, establishing the evaluation model includes the following steps:

[0022] S201. By standardizing the data sample matrix composed of individual underlying indicator data, the dimensional effect of each evaluation indicator is eliminated, and a relative membership matrix R = (r ij ) m×n , where r ij This represents the relative membership value corresponding to the i-th index and the j-th control loop. The standardized evaluation index values ​​can form a relative membership matrix R = (r ij ) m×n ;

[0023] S202. Construct a judgment matrix B = (b...) to determine the index weights using the relative membership matrix. ij ) m×n ;

[0024] S203. Use an accelerated genetic algorithm to correct the consistency of the judgment matrix so that it meets the consistency test. The consistency test, correction, and weight calculation of the judgment matrix must satisfy the requirement ω. i >0 and Where, ω i This represents the weight of the i-th indicator. The weight values ​​{ω} of each evaluation indicator are obtained based on the judgment matrix. i |i=1,2,…,m}, matrix B has complete consistency;

[0025] Due to the complexity of actual evaluation systems, the diversity of people's understanding, and the subjective bias and instability, the incomplete satisfaction of the consistency condition of judgment matrix B is an objective reality that cannot be completely eliminated in practical applications. If B does not have satisfactory consistency, it needs to be modified.

[0026] Let the corrected judgment matrix of B be Y = {y ij} m×m The weights of each element in Y are still denoted as {ω}. i If |i=1,2,…,m}, then the optimal consistency judgment matrix of B has complete consistency with the m-order judgment matrix B, and according to the constraints... It can be seen that the global minimum value is unique.

[0027] S204. Based on the judgment matrix obtained in step S203, use the summation method to calculate the index weights.

[0028] S205. Select an appropriate synthesis operator, calculate the comprehensive index value using the fuzzy evaluation matrix and index weights, and assign the weight value ω of the i-th evaluation index to the index. i Membership degree r with the corresponding evaluation index ij The corresponding products are multiplied and added together to obtain the comprehensive index value representing the final score, denoted as z.j ;

[0029] z j The larger the value, the more easily the control loop is misoperated, and the more necessary it is to develop anti-misoperation technology.

[0030] S206. Select a suitable comprehensive index threshold. Control loops with scores greater than the threshold are considered to be control loops that are prone to malfunctions. Secondary functional development will be carried out on the equipment in the control loop.

[0031] S207. Analyze each device in the control loop determined in step S206, and further screen out key devices that require secondary function development, such as valves and units. The screening results should include various types of devices and modules that have design specifications limited by control valves and are selected based on the experience of actual operators.

[0032] Preferably, in step S202, the formula for constructing the judgment matrix is:

[0033]

[0034] Among them, s i s represents the standard deviation of the i-th row of the relative membership matrix. j This represents the standard deviation of the j-th column. s represents the average value of the data for each evaluation indicator. max s min They are s i The maximum and minimum values; b m b is a parameter indicating relative importance. m =min{9,int[s max / s min +0.5]};

[0035] Preferably, in step S201, in order to preserve the change information of each evaluation index value as much as possible, a normalization method is used on the information, the method including:

[0036] The standardization formula for larger indicators, which are more prone to errors, is as follows:

[0037]

[0038] The standardization formula for larger indicators, where smaller data points are more prone to errors, is as follows:

[0039]

[0040] The standardized formula for handling data with a higher probability of error, where the frequency of operation in each control loop should not be too high or too low, is as follows:

[0041]

[0042] Where, r ij x represents the standardized evaluation index value. imin x imax x imid These represent the minimum, maximum, and intermediate optimal values ​​corresponding to the i-th index in the relative membership matrix, respectively.

[0043] Among them, when the indicator and the score result are positively correlated, the larger the data, the easier it is to make a mistake. When the indicator and the score result are negatively correlated, the smaller the data, the easier it is to make a mistake. When the indicator and the score result are neither positively nor negatively correlated, the larger the data, the easier it is to make a mistake.

[0044] Preferably, in step S203, matrix B has the following property:

[0045]

[0046] Among them, property ① is called the identity property of the judgment matrix; property ② is called the reciprocal property (reciprocity) of the judgment matrix; property ③ is called the consistency condition of the judgment matrix, indicating that the relationship between them can be quantitatively transmitted, and property ③ is a sufficient condition for property ① and property ②.

[0047] Preferably, in step S203, the objective function CIC(n) is called the consistency index coefficient; d∈(0,0.5] is a non-negative parameter. The average random consistency index coefficient RIC(n) value of the judgment matrix is ​​introduced. 500 random judgment matrices of order 3 to n are constructed respectively by random simulation method. They satisfy the unit and reciprocal properties of the judgment matrix, but do not guarantee that the judgment matrix satisfies the consistency condition. The consistency index coefficient value of the random matrix is ​​calculated, and the average value is the RIC(n) value.

[0048] The consistency index coefficient CIC(n) value varies for judgment matrices of different orders n. To measure whether a judgment matrix has satisfactory consistency, the average random consistency index coefficient RIC(n) value of the judgment matrix is ​​introduced.

[0049] Preferably, when the consistency coefficient CIC(n) of the judgment matrix is ​​less than 0.10, the judgment matrix has satisfactory consistency, and the weight values ​​ω of each evaluation index are calculated accordingly. i Otherwise, the parameter d needs to be increased until satisfactory consistency is achieved.

[0050] Preferably, in step S4, based on existing functional modules, the existing equipment's conventional operation methods and habits are analyzed and improved by expanding or adding basic functions and using programming configuration. Existing equipment includes: regulating valves, shut-off valves, key units, etc. For equipment operation processes in emergency or special situations, scientific and effective methods are adopted to avoid operator errors. The proposed functional requirements include: automatic valve position limiting function, key valve self-locking function, and process parameter early warning function. Specific functional requirements include:

[0051] For the automatic valve position limiting function, the functional requirements are further refined based on the actual situation of the operating system, including: adding deviation value limiting function for valves, valve position limiting function for regulating valves in key units and process pipelines, and SP value limiting function for key control loops;

[0052] For valves, the addition of a deviation limit function addresses the issue that industrial control system operation panels currently lack deviation limits for input values. Operators may input values ​​that are too large or too small, leading to significant fluctuations in process parameters and causing plant shutdowns. When the input value deviates too much from the actual value, the system imposes input restrictions and requests secondary confirmation. Simultaneously, based on the actual process requirements, it assigns technicians the authority to modify the limit values, thus improving module usability.

[0053] For critical units and process pipeline regulating valves, the lack of limiting and early warning functions makes it easy for operators to misoperate beyond the design-specified adjustment range, potentially causing liquid level overflow in critical equipment, triggering interlocks, and leading to unit shutdown. This new function combines the condition of whether the pumps are in operation with input value limits and pop-up warning prompts.

[0054] For the SP value limit function of critical control loops, during the operation of the unit, the process parameters of complex control loops are adjusted according to the given design values. If the SP value is entered incorrectly, it will cause the process parameters to deviate from the design specifications, resulting in fluctuations in process parameters, and in severe cases, it may trigger the unit's interlock shutdown.

[0055] S403: For the self-locking function of key valves, the functional requirements are further refined based on the actual situation of the operating system, including: the self-locking function of the shut-off valve when the pump is running, the logic control function of the shut-off valve / regulating valve opening and closing with process parameters, and the self-locking function of the pump running status and the opening and closing of the regulating valve.

[0056] Regarding the self-locking function of the shut-off valve when the pump is running, during production operation, if the operator does not control the valves of the unit in the correct sequence according to the process requirements, abnormal accidents such as high pressure followed by low pressure may occur, and there is a significant risk in opening and closing the valves.

[0057] For shut-off valves and regulating valves, logic control functions are implemented to control their on / off states in relation to process parameters. Failure to strictly adhere to operating procedures during process operation may result in tank evacuation, delayed operational response, and potential accidents, posing a significant risk. To address this, logic control and early warning functions are added to these valves. When the specified process medium (such as liquid level or air volume) does not meet design requirements, the system applies operational restrictions and provides warnings based on logic control principles.

[0058] For pump operation status and control valve opening / closing functions, a self-locking function is needed. The actions of some critical control valves are not sequentially controlled according to equipment operating status. If the inlet and outlet control valves are suddenly closed during equipment operation, it could cause accidents such as pressure buildup, overload, or cavitation, posing a significant safety hazard. Valve position limiting and early warning functions should be implemented for these types of control valves.

[0059] S404: For the process parameter early warning function, the functional requirements are further refined based on the actual situation of the operating system, including: process parameter sudden change early warning function, process parameter trend change and valve action early warning function, motor status monitoring early warning function, and complex control loop operation indication function.

[0060] For the early warning function of sudden changes in process parameters, when process parameters change significantly, instruments malfunction, signals interfere, or measurement data are distorted, the system data will suddenly fluctuate, but the conditions for triggering an alarm have not yet been met. This may lead to misjudgment or untimely response by operators. Therefore, the early warning function for large fluctuations in process parameters was developed.

[0061] Regarding the process parameter trend change and valve action early warning function, when some level control valves are put into manual control, there may be a situation where the liquid level drops, but the operator fails to notice in time and still opens the bottom solvent outlet control valve too much or does not close the outlet control valve, which may lead to the bottom solution being evacuated and damage the pumps.

[0062] For motor condition monitoring and early warning functions, abnormal motor parameters triggering interlock shutdown is a common accident in production and operation units. When an accident occurs, parameter changes go through six stages: stable operation → slow increase → rapid increase → high alarm → high-high alarm → triggering interlock shutdown. When the parameters reach the rapid increase stage, there is no time for emergency response. To solve the problem of untimely manual response in motor failures, a condition monitoring and early warning function was developed for continuously changing motor parameters.

[0063] For complex control loops, such as split-range control, three-impulse control, and proportional control, the control logic is relatively complex, and operators cannot intuitively view the loop sequence and logic. In conjunction with the operating procedures, an operation prompt function is added to the control loop operation panel to objectively reflect the information of the complex control loop. Furthermore, the process operation flow, precautions, and key operating points are set on the secondary screen.

[0064] Based on the same concept, the present invention also provides an industrial control system anti-misoperation device, including at least one processor and a memory communicatively connected to the at least one processor; the memory stores instructions executable by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the technical method for preventing misoperation of an industrial control system as described above.

[0065] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0066] 1. The technical method for preventing misoperation in an industrial control system described in this invention can effectively identify the control objects that need to be developed with anti-misoperation functions, and can also greatly reduce the probability of misoperation accidents and reduce production and operation risks.

[0067] 2. The method provided by this invention can comprehensively, in real time and accurately grasp the operating status of industrial control systems, bringing great benefits to the safe and stable operation of production equipment; at the same time, it also has great promotional value. Attached Figure Description

[0068] Figure 1 This is a flowchart of the industrial control system anti-misoperation technology method of Embodiment 1;

[0069] Figure 2 This is the evaluation index system for the ease of misoperation of the control loop in Embodiment 1. Detailed Implementation

[0070] The present invention will be further described in detail below with reference to experimental examples and specific embodiments. However, this should not be construed as limiting the scope of the above-mentioned subject matter of the present invention to the following embodiments; all technologies implemented based on the content of the present invention fall within the scope of the present invention.

[0071] Example 1

[0072] like Figure 1 As shown, the technical steps for preventing misoperation in the industrial control system of a high-sulfur natural gas purification plant are as follows:

[0073] Step S1: Collect basic data of all control loops under the control system to form a control loop misoperation dataset and establish a control loop information database;

[0074] Step S2: Establish a reliable evaluation model, input the control loop misoperation dataset into the evaluation model, obtain the probability and ease of control loop misoperation, and screen out the key control loops that require secondary function development.

[0075] Step S3: Analyze the automatic control equipment such as regulating valves, shut-off valves, and generator units under the control of the key control loop in sequence to determine the specific research objects that need secondary function development;

[0076] Step S4: Determine the secondary development functions required for each specific research object and propose specific functional requirements;

[0077] Step S5: Design the corresponding program flow according to the specific functional requirements;

[0078] Step S6: Based on the designed program flow, build a configuration program for each specific research object and compile the underlying logic code;

[0079] Step S7: Design the function panel to include: prompts, alarms, and secondary confirmation for whether to make changes;

[0080] Step S8: The operator gives an operation command or changes the input value to meet the alarm logic requirements, and tests the developed application function;

[0081] Step S9: Based on the feedback from the test results, return to step S3 to make corrections. Once no further feedback is received, end the loop and refine the operational techniques.

[0082] Step S101: Through qualitative and quantitative analysis, select easily quantifiable evaluation indicators that can assist in evaluating the susceptibility of control loop misoperation, such as cumulative number of misoperations, cumulative operation time, annual number of misoperations, monthly operation frequency, frequency of relevant professional knowledge assessments, number of skilled operators, number of nighttime operations, and cumulative losses caused by misoperation, and establish an evaluation indicator system. Figure 2 As shown;

[0083] Step S102: Collect indicator data for each control loop according to the indicators in the evaluation indicator system, and construct a data sample matrix X = (x ij ) m×n This refers to the control loop misoperation dataset. Here, m represents the total number of underlying evaluation indicators, and n represents the total number of control loops; x ij This represents the index data corresponding to the i-th index and the j-th control loop, where i = 1 to m, j = 1 to n, and here, m = 8 and n = 504.

[0084] Step S2, establishing the evaluation model, specifically includes the following steps:

[0085] Step S201: By standardizing the data sample matrix composed of individual underlying indicator data, the dimensional effect of each evaluation indicator is eliminated, and a relative membership matrix R = (r ij ) m×n , where r ijThis represents the relative membership value corresponding to the i-th index and the j-th control loop;

[0086] To preserve the changes in the values ​​of each evaluation indicator as much as possible, the normalization method used here is as follows:

[0087] The standardization formula for larger indicators, which are more prone to errors, is as follows:

[0088]

[0089] The standardization formula for larger indicators, where smaller data points are more prone to errors, is as follows:

[0090]

[0091] The standardized processing formula for larger indicators (such as the frequency of operation of each control loop should not be too high or too low) is as follows:

[0092]

[0093] Where, r ij x represents the standardized evaluation index value. imin x imax x imid These represent the minimum, maximum, and intermediate optimal values ​​corresponding to the i-th index in the relative membership matrix, respectively.

[0094] Among them, when the indicator and the score result are positively correlated, the larger the data, the easier it is to make a mistake. When the indicator and the score result are negatively correlated, the smaller the data, the easier it is to make a mistake. When the indicator and the score result are neither positively nor negatively correlated, the larger the data, the easier it is to make a mistake.

[0095] The standardized evaluation index values ​​can form a relative membership matrix R = (r ij ) m×n .

[0096] Step S202: Construct a judgment matrix B = (b...) to determine the index weights using the relative membership matrix. ij ) m×n The formula for constructing the judgment matrix is:

[0097]

[0098] Among them, s i s represents the standard deviation of the i-th row of the relative membership matrix. j This represents the standard deviation of the j-th column. s represents the average value of the data for each evaluation indicator. max smin They are s i The maximum and minimum values; b m b is a parameter indicating relative importance. m =min{9,int[s max / s min +0.5]};

[0099] Step S203: Use an accelerated genetic algorithm to correct the consistency of the judgment matrix so that it meets the consistency test. The consistency test, correction, and weight calculation of the judgment matrix satisfy the requirement ω. i >0 and Where, ω i This represents the weight of the i-th indicator, according to the definition of the judgment matrix:

[0100]

[0101] Where i,j=1,2,…,m.

[0102] At this point, matrix B has the following properties:

[0103]

[0104]

[0105]

[0106] Property ① is called the identity property of the judgment matrix; property ② is called the reciprocal property (reciprocity) of the judgment matrix; and property ③ is called the consistency condition of the judgment matrix, which indicates that the relationship between them can be quantitatively transmitted. Property ③ is also a sufficient condition for properties ① and ②.

[0107] After obtaining the judgment matrix B, the weight values ​​{ω} of each evaluation index can be derived. i |i=1,2,…,n}. If the judgment matrix B has complete consistency, then:

[0108]

[0109] Due to the complexity of actual evaluation systems, the diversity of people's understanding, and the subjective bias and instability, the incomplete satisfaction of the consistency condition of judgment matrix B is an objective reality that cannot be completely eliminated in practical applications. If B does not have satisfactory consistency, it needs to be modified.

[0110] Let the corrected judgment matrix of B be Y = {y ij} m×m The weights of each element in Y are still denoted as {ω}. iIf |i=1,2,…,m}, then the formula for calculating the optimal consistency judgment matrix of B, which is also the minimum Y matrix, is:

[0111]

[0112] sty ii =1 (i = 1, 2, ..., m)

[0113]

[0114] ω>0 (i=1,2,…,m)

[0115]

[0116] In the formula, the objective function CIC(n) is called the Consistency Index Coefficient; d∈(0,0.5] is a non-negative parameter. Wherein, ω i Let ω be the weight value of the i-th indicator, i = 1, 2, ..., m. i and the corrected judgment matrix Y = {y ij} m×m The elements of the upper triangular matrix are optimization variables, and they have complete consistency with the n-order judgment matrix B. Furthermore, according to the constraints... It can be seen that the global minimum value is unique.

[0117] Accelerated Genetic Algorithm (AGA), which simulates the survival-of-the-fittest rules and chromosome information exchange mechanisms within a population, is a general global optimization method. It is relatively simple and effective to use it to optimize and solve the above equation.

[0118] The consistency index coefficient CIC(n) values ​​differ for judgment matrices of different orders n. To measure whether a judgment matrix has satisfactory consistency, we introduce the average random consistency index coefficient RIC(n) value. Using a random simulation method, we construct 500 random judgment matrices for each order from 3 to n. These matrices satisfy the unity and reciprocal properties of judgment matrices, but do not guarantee that they meet the consistency condition. We calculate the consistency index coefficient values ​​of these random matrices and then average them to obtain the RIC(n) value.

[0119] When the consistency coefficient CIC(n) of the judgment matrix is ​​less than 0.10, the judgment matrix can be considered to have satisfactory consistency. The weight values ​​ω of each evaluation index are calculated accordingly. i This is acceptable; otherwise, the parameter d needs to be increased until satisfactory consistency is achieved.

[0120] Step S204: Based on the judgment matrix obtained in step S203, the index weights are calculated using the summation method. The formulas for calculating each weight are as follows:

[0121]

[0122] Step S205: Select an appropriate synthesis operator, and calculate the comprehensive index value, which is the final score, using the fuzzy evaluation matrix and index weights. Set the weight value ω of the i-th evaluation index... i Membership degree r with the corresponding evaluation index ij Multiplying and adding the corresponding values ​​yields the comprehensive index value representing the final score, denoted as z. j :

[0123]

[0124] z j The larger the value, the more easily the control loop is misoperated, and the more necessary it is to develop anti-misoperation technology.

[0125] Step 206: Select an appropriate comprehensive index threshold. Control loops with scores greater than the threshold are considered to be control loops prone to malfunctions, and secondary function development will be carried out for the equipment in these control loops. Here, based on the actual situation of the overall score slope, the threshold is selected as 0.5. Secondary function development will be carried out for the 82 control loops with comprehensive index values ​​greater than 0.5.

[0126] Step 207: Analyze each device in the control loop determined in Step 206, and further screen out the key devices that require secondary function development, mainly valves, units, etc. The screening results should include various devices and modules with strict design requirements and selected based on the experience of actual operators.

[0127] The implementation process of proposing specific functional requirements in step S4 specifically includes the following steps:

[0128] Step S401: Based on the existing functional modules, analyze and improve the conventional operation methods and habits of existing equipment, such as control valves, shut-off valves, and key units, by expanding or adding basic functions and using programming configuration. At the same time, take into account the equipment operation process in emergency or special situations, and adopt scientific and effective methods to avoid operator misoperation. The proposed functional requirements include three categories: automatic valve position limiting function, key valve self-locking function, and process parameter early warning function.

[0129] Step S402: For the automatic valve position limiting function, based on the actual situation of the operating system, the functional requirements are further refined into three categories: valve deviation value limiting function, valve position limiting function for key units and process pipeline regulating valves, and SP value limiting function for key control loops.

[0130] The detailed functional configuration proposed in step S402 is as follows:

[0131] 1. Add a deviation value limit function to the valve:

[0132] The valves with this function are the turbine inlet regulating valve, the inlet valve of the tail furnace blower, the air regulating valve of the tail furnace, the air regulating valve of the hydrogenation furnace, the outlet liquid level regulating valve of the rich solvent flash tank, the fuel gas regulating valve of the tail furnace, the inlet air valve of the power station blower, the inlet air valve of the power station induced draft fan, the fire vent valve of the power station, and the main air valve / micro air valve of the Claus furnace. For the main air valve / micro air valve of the Claus furnace, limit the deviation of the micro air valve, and set the limit value to 10%. When the deviation between the given value and the measured value is greater than 10%, the system prompts: "The adjustment amplitude is too large. Do you want to execute this operation?"; for other valves, set the limit value to 5%. When the deviation between the given value and the measured value is greater than 5%, the system prompts: "The adjustment amplitude is too large. Do you want to execute this operation?"

[0133] 2. Valve position limit function for key units and process pipeline regulating valves:

[0134] The valve with this function is the outlet regulating valve of the semi-rich liquid pump. According to the design requirements, when the semi-rich liquid pump is in the startup and running state, the valve position of the pump outlet regulating valve should be between 18% and 35%. Otherwise, it will cause the unit to trip. Therefore, this function is set to prompt the system when the valve position of the pump outlet regulating valve is lower than 20% / higher than 33%: "The valve position of the outlet regulating valve of the semi-rich liquid pump is too low / too high. Please pay attention to adjustment."

[0135] 3. SP value limit function for key control loops:

[0136] This function is for control loops with given design value requirements, specifically including 4 given process control logics of the turbine split-range control loop (65 < SP < 80), the air distribution ratio of the Claus furnace (1.1 < SP < 1.4), the intake air ratio of the first and second zones of the Claus furnace (2 < SP < 4), and the air distribution ratio of the hydrogenation furnace (7 < SP < 8). If the operator gives an SP value outside the above design range, the system is set to prompt: "The given deviation of the SP value is large. Please verify."

[0137] Step S403: For the key valve self-locking function, further refine the functional requirements into 3 categories based on the actual situation of the operating system: the self-locking function of the shut-off valve when the pump is running, the logical control function of the opening and closing of the shut-off valve / regulating valve with process parameters, and the self-locking function of the pump running state and the opening and closing of the regulating valve;

[0138] The detailed function configuration for step S43 is as follows:

[0139] 1. Self-locking function of the shut-off valve when the pump is running:

[0140] The valves configured with this function are mainly the inlet and outlet shut-off valves of the pump. When the pump is running, the inlet and outlet valves should be in the open state. When one or more inlet and outlet valves are manually closed, the system prompts: "The XX equipment is in the running state and cannot be closed".

[0141] 2. Logic control function for the on / off switching of shut-off valves and regulating valves in relation to process parameters:

[0142] This functional module is developed for process media with specific design specifications, in conjunction with the designed control logic. For example, the design specification for a certain emergency drain valve is that during normal production operation, if the liquid level in the waste heat boiler drum is below 45%, the emergency drain valve should not be opened. If it is forcibly opened at this time, the system will prompt: "The liquid level of XX equipment is also too low, please confirm whether to open." The design specification for the inlet valve of the second zone of a Claus furnace is that during normal production operation, when the inlet flow rate of the second zone of the Claus furnace is below 1000 m³ / h... 3 When the flow rate is / h, backfire is likely to occur. If the valve is forcibly closed at this time, the system will prompt: "The inlet flow rate of the Claus furnace zone 2 of a certain unit is too low. It is forbidden to continue to shut down the XX equipment."

[0143] 3. The pump's operating status and the control valve's opening and closing are self-locking:

[0144] This function module is designed for pumps with reflux valves. The main components for this function are the inlet and outlet regulating valves or return valves of these pumps. When the valve status changes, the system checks whether the inlet and outlet regulating valves and reflux valves are all closed. If they are all closed, the system will display the message: "Pump XX of the combined unit is in the running state. It is forbidden to close the outlet regulating valve and reflux valve completely."

[0145] Step S404: For the process parameter early warning function, based on the actual situation of the operating system, the functional requirements are further refined into 4 categories: process parameter sudden change early warning function, process parameter trend change and valve action early warning function, motor status monitoring early warning function, and complex control loop operation indication function.

[0146] The detailed functional configuration proposed in step S404 is as follows:

[0147] 1. Early warning function for sudden changes in process parameters:

[0148] The devices equipped with this function include the desulfurization tower level control valve, the waste heat boiler drum level control valve, the desulfurization tower differential pressure gauge, and the wet purified gas hydrogen sulfide content analyzer. For the desulfurization tower level control valve and the waste heat boiler drum level control valve, when the level fluctuates by more than 3% within 300 seconds, the system will prompt: "Equipment XX has suddenly risen / fallen significantly, please check and confirm." For the desulfurization tower differential pressure gauge, when the desulfurization tower differential pressure increases by more than 8 kPa within 600 seconds, the system will prompt: "Desulfurization tower differential pressure has suddenly increased significantly, please check and confirm." For the wet purified gas hydrogen sulfide content analyzer, when the wet purified gas hydrogen sulfide content increases by more than 3 mg / m³ within 600 seconds... 3 At that time, the system prompted: "The hydrogen sulfide content in the wet purification gas of a certain unit has suddenly increased significantly. Please check and confirm."

[0149] 2. Early warning function for process parameter trend changes and valve action:

[0150] The valves equipped with this function include the desulfurization tower liquid level valve, the hydrogenation furnace air distribution valve, and the hydrogenation furnace air valve. For the desulfurization tower liquid level valve, in manual control mode, when the desulfurization tower liquid level is less than 45%, the valve should be closed slightly according to the process requirements. If it continues to be opened, the system will prompt: The current desulfurization tower liquid level is below 50%. Please close the valve and adjust the liquid level in time. When the desulfurization tower liquid level is greater than 55%, the valve should be opened wider according to process requirements. If it continues to be closed, the system will prompt: "The current desulfurization tower liquid level is higher than 50%. Please open the valve wider and adjust the liquid level in time." For the hydrogenation furnace air distribution valve, in manual control mode, when the air distribution ratio is less than 7.5, the inlet air valve should be opened wider or the outlet air valve closed narrower according to process requirements. If the inlet air valve continues to be closed narrower or the outlet air valve opened wider, the system will prompt: "Hydrogenation furnace air distribution is too low. Please open the inlet air valve wider or close the outlet air valve narrower." For the hydrogenation furnace air valve, in automatic control mode, when the actual air distribution is less than or greater than the given value, the inlet air valve needs to be opened wider or closed narrower. However, due to valve malfunction, the valve may not operate for a short time, resulting in a constant air volume. During the continued opening or closing of the valve, if the valve suddenly opens or closes, the air volume may be too high or too low, potentially extinguishing the furnace or causing insufficient air supply. Specifically, if the valve is opened wider or closed narrower by 5% or more, the change in inlet air flow rate should be less than 100 m³ / s after 60 seconds. 3 / h (the required comparison sampling period is 10s), the system alarm prompts: "Inlet air valve malfunction, unable to operate normally".

[0151] 3. Motor status monitoring and early warning function:

[0152] By comparing the parameter variation range under normal operating conditions, the loop control strategy was analyzed, and a dynamic monitoring and alarm function for the temperature status parameters of some motors in the device was developed and set. When the temperature parameter rises by more than 15°C within 5 minutes, the system prompts: "Temperature rises significantly".

[0153] 4. Complex control loop operation indication function:

[0154] There are a total of 7 control loops for this function, namely turbine split-range control, Claus furnace air distribution control, hydrogenation furnace distribution control, tail furnace temperature control, waste heat boiler drum three-impulse control, tail gas waste heat boiler drum three-impulse control, and power station boiler three-impulse control loop.

[0155] Step S405: Based on the 10 functional requirements proposed in S402, S403, and S404, and combined with the design and operational experience of each key device, further propose specific functional requirements down to the setpoint. Specifically, for all cases requiring system prompts, limits, or monitoring alarm thresholds, the design and specified value values ​​should be prioritized. If neither the design nor the specifications specify such requirements, the field operator should provide the values ​​based on design specifications or operational experience, which will then be reviewed and approved by technical management personnel.

[0156] Furthermore, the design process flow and compilation of the underlying logic code in steps S5 and S6 are both designed and implemented based on the specific requirements of each key device proposed in step S45.

[0157] Based on the same concept, the present invention also provides an industrial control system anti-misoperation device, including at least one processor and a memory communicatively connected to the at least one processor; the memory stores instructions executable by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the technical method for preventing misoperation of an industrial control system as described above.

[0158] The technical method for preventing misoperation in industrial control systems described in this invention can effectively identify the control objects that require the development of anti-misoperation technology; it can also greatly reduce the probability of misoperation accidents and lower production and operation risks; it can also comprehensively, in real time, and accurately grasp the operating status of industrial control systems, bringing great benefits to the safe and stable operation of production equipment; at the same time, it also has great promotional value.

[0159] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for preventing misoperation in an industrial control system, characterized in that, Includes the following steps: S1: Collect basic data of all control loops under the control system to form a control loop misoperation dataset and establish a control loop information database. S2: Establish a reliable evaluation model, input the control loop misoperation dataset into the evaluation model, obtain the probability and ease of control loop misoperation, and screen out the key control loops that require secondary function development. Establishing the evaluation model includes the following steps: S201. By standardizing the data sample matrix composed of individual underlying indicator data, the dimensional effect of each evaluation indicator is eliminated, and a relative membership matrix is ​​established. ,in, Indicates the first The first indicator The relative membership values ​​corresponding to each control loop, and the standardized evaluation index values, can form a relative membership matrix. ; This represents the total number of underlying evaluation indicators. Indicates the total number of control loops; S202. Construct a judgment matrix for determining indicator weights using the relative membership matrix. ; S203. Use an accelerated genetic algorithm to correct the consistency of the judgment matrix so that it meets the consistency test. The consistency test, correction, and weight calculation of the judgment matrix must meet the requirements. and ,in Indicates the first The weights of each indicator are determined; the weight values ​​of each evaluation indicator are obtained based on the judgment matrix. At this point, matrix B has complete consistency; Let the correction judgment matrix of B be... The weights of each element in Y are still denoted as ; S204. Based on the judgment matrix obtained in step S203, use the summation method to calculate the index weights. S205. Select an appropriate synthesis operator, and calculate the comprehensive index value using the fuzzy evaluation matrix and index weights. The weight values ​​of each evaluation indicator Membership degree with the corresponding evaluation indicators The corresponding values ​​are multiplied and added together to obtain the comprehensive index value representing the final score. ; S206. Select a suitable comprehensive index threshold. Control loops with scores greater than the threshold are considered to be control loops that are prone to malfunctions. Secondary functional development will be carried out on the equipment in the control loop. S207. Analyze each device in the control loop determined in step S206, and screen out the key devices that need secondary function development. The screening results include devices and modules selected based on the design index requirements of the control valve and the experience of actual operators. S3: Analyze the automatic control equipment under the jurisdiction of the key control loop in sequence to determine the specific research objects that need secondary function development; S4: Determine the secondary development functions required for each specific research object and propose specific functional requirements; Based on existing functional modules, this paper analyzes and improves the conventional operation methods and habits of existing equipment by expanding or adding basic functions and using programming configuration. The proposed functional requirements include: automatic valve position limiting function, critical valve self-locking function, and process parameter early warning function. For automatic valve position limiting functions, the following are included: valve deviation value limiting function, valve position limiting function for control valves in key units and process pipelines, and SP value limiting function for key control loops; For the self-locking function of key valves, including: the self-locking function of shut-off valves when pumps are running, the logic control function of shut-off valves / regulating valves on and off with process parameters, and the self-locking function of pump running status and regulating valve on and off. For process parameter early warning functions, the functions include: process parameter early warning function, process parameter trend change and valve action early warning function, motor status monitoring early warning function, and control loop operation indication function. S5: Design corresponding program flows according to specific functional requirements; S6: Based on the designed program flow, build configuration programs for each specific research object and compile the underlying logic code; S7: The design function panel includes: prompts, alarms, and secondary confirmation for whether to modify; S8: The operator gives an operation command or changes the input value to meet the alarm logic requirements, and tests the developed application function; S9: Based on the test results, report any issues and return to step S3 to make corrections. The loop ends when no issues are reported.

2. The method for preventing misoperation in an industrial control system according to claim 1, characterized in that, In step S1, establishing the control loop malfunction dataset includes the following steps: S101. Through qualitative and quantitative analysis, select evaluation indicators that are easy to quantify and can help evaluate the ease of control loop misoperation, and establish an evaluation indicator system. S102. Collect index data for each control loop according to the indicators in the evaluation index system, and construct a data sample matrix. That is, the control loop misoperation dataset, in which, This represents the total number of underlying evaluation indicators. Indicates the total number of control loops. Indicates the first The first indicator The index data corresponding to each control loop.

3. The method for preventing misoperation in an industrial control system according to claim 1, characterized in that, In step S202, the formula for constructing the judgment matrix is: in, Represents the relative membership matrix. Standard deviation of rows Indicates the first The standard deviation of the column, The average value of the data for each evaluation indicator. , They are The maximum and minimum values; It is a parameter of relative importance. .

4. The method for preventing misoperation in an industrial control system according to claim 1, characterized in that, In step S201, the data sample matrix composed of individual underlying indicator data is standardized, and the method includes: The standardization formula for larger indicators, which are more prone to errors, is as follows: The standardization formula for larger indicators, where smaller data points are more prone to errors, is as follows: The standardized formula for handling data with a higher probability of error, where the frequency of operation in each control loop should not be too high or too low, is as follows: In the formula, This represents the standardized evaluation index value. , , These represent the nth element in the relative membership matrix. The minimum, maximum, and optimal intermediate values ​​for each indicator; Among them, when the indicator and the score result are positively correlated, the larger the data, the easier it is to make a mistake. When the indicator and the score result are negatively correlated, the smaller the data, the easier it is to make a mistake. When the indicator and the score result are neither positively nor negatively correlated, the larger the data, the easier it is to make a mistake.

5. The method for preventing misoperation in an industrial control system according to claim 1, characterized in that, In step S203, the matrix It has the following properties: ① ；② ；③ Among them, property ① is called the identity property of the judgment matrix; property ② is called the reciprocal property (reciprocity) of the judgment matrix; property ③ is called the consistency condition of the judgment matrix, indicating that the relationship between them can be quantitatively transmitted, and property ③ is also a sufficient condition for property ① and property ②.

6. The method for preventing misoperation in an industrial control system according to claim 1, characterized in that, In step S203, the average random consistency index coefficient RIC(n) of the judgment matrix is ​​introduced, and a random simulation method is used to evaluate the consistency of the judgment matrix. Construct 500 random judgment matrices for each order, calculate the consistency index coefficient of the random matrices, and average them to obtain the result. value.

7. The method for preventing misoperation in an industrial control system according to claim 6, characterized in that, The objective function is called the objective function. This is the consistency index coefficient; The objective function is expressed as: in, d For active variables with non-negative parameters, the values ​​satisfy... , y ii 、y ij To correct the elements of the judgment matrix, b ij To determine the elements of a matrix, ω To evaluate the weights of the indicators, ω i Let be the weight of the i-th evaluation indicator; When judging the consistency coefficient of the matrix At this point, the judgment matrix exhibits satisfactory consistency, and the weight values ​​of each evaluation index are calculated accordingly. Otherwise, the parameters need to be increased. This continues until satisfactory consistency is achieved.

8. An anti-misoperation device for an industrial control system, characterized in that, The system includes at least one processor and a memory communicatively connected to the at least one processor; the memory stores instructions executable by the at least one processor, which, when executed by the at least one processor, enable the at least one processor to perform a method for preventing misoperation in an industrial control system according to any one of claims 1 to 7.

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