Hazardous chemical production safety management system based on dynamic risk assessment

Abstract

This invention relates to a hazardous chemical production safety management system based on dynamic risk assessment, belonging to the field of production safety management technology. It includes: a risk factor quantification module for collecting process parameters and equipment status parameters of the hazardous chemical production process and generating a set of component risk values; a dynamic risk assessment module for calculating a comprehensive risk index; a risk level early warning and decision support module for comparing the comprehensive risk index with a preset risk level threshold to generate the current risk level and outputting decision support instructions based on the current risk level; and a safety strategy adaptive optimization module for adjusting the production process in response to the decision support instructions and optimizing the dynamic weighting coefficients based on the comprehensive risk index of historical production batches. This invention makes the originally abstract and dispersed safety status intuitive and quantifiable, forming a forward-looking, automated safety management closed loop from early warning to decision-making.

Description

Technical Field

[0001] This invention relates to the field of production safety management technology, specifically a hazardous chemical production safety management system based on dynamic risk assessment. Background Technology

[0002] In the production of hazardous chemicals, especially in the synthesis of highly reactive compounds such as xenon difluoride, existing safety management technologies generally have several deficiencies. The production process of xenon difluoride involves reacting high-purity xenon gas with highly corrosive fluorine gas under specific conditions. The safety of this process depends on the precise control of several stringent process conditions, such as:

[0003] Risk identification is lagging and mostly reactive. The production process involves high-temperature and high-pressure raw materials. Traditional safety management relies on fixed threshold alarms. However, by the time the system detects an anomaly in this single parameter, the risk may have already developed to a high level, resulting in safety management being mostly reactive rather than proactive.

[0004] Risk assessment is often limited by a single dimension and lacks comprehensive integration. The safety of xenon difluoride synthesis is a multivariate coupled system. Its risks not only stem from over-temperature and over-pressure during the reaction stage, but are also closely related to multiple aspects: whether the dew point in the pipeline is up to standard before start-up, whether the molar ratio of fluorine to xenon is accurate during the feed stage, and the integrity of the reactor and valves in a highly corrosive environment. Existing technologies often monitor a single parameter in isolation, lacking comprehensive integration and quantitative assessment of multi-source and heterogeneous parameters such as start-up preparation, material ratio, reaction conditions, and equipment status, making it difficult to accurately reflect the true safety status of the entire system.

[0005] Safety strategies are static and cannot be dynamically adapted. The production process has distinct phased characteristics. In the start-up preparation phase, the core risk is moisture in the system; in the feeding phase, the key lies in the accuracy of material ratio; and in the reaction phase, it shifts to strict monitoring of temperature and pressure. Existing safety strategies are usually static, and their risk monitoring focus and assessment weight cannot be dynamically adjusted according to the characteristics of these different phases, resulting in insufficient pertinence and effectiveness of assessments, thus limiting further improvement in the inherent safety level of the production process.

[0006] Therefore, in response to the specific problems existing in the production of hazardous chemicals such as xenon difluoride, there is an urgent need for an advanced safety management system that can achieve comprehensive, dynamic, and forward-looking risk assessment and decision-making.

[0007] The information disclosed in the background section above is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0008] The purpose of this invention is to provide a safety management system for the production of hazardous chemicals based on dynamic risk assessment, so as to solve the problems mentioned in the background art.

[0009] The technical solution of this invention is a hazardous chemical production safety management system based on dynamic risk assessment, comprising:

[0010] The risk factor quantification module is used to collect process parameters and equipment status parameters of the hazardous chemical production process, and quantify them based on the process parameters and equipment status parameters to generate a set of component risk values; the component risk values ​​include at least the operating environment risk value, material ratio risk value, reaction condition risk value, and equipment status risk value;

[0011] The dynamic risk assessment module is used to obtain the dynamic weight coefficients corresponding to the preset process stages, and calculate the comprehensive risk index by combining the dynamic weight coefficients and the group of component risk values.

[0012] The risk level warning and decision support module is used to compare the comprehensive risk index with the preset risk level threshold, generate the current risk level, and output decision support instructions based on the current risk level.

[0013] The safety strategy adaptive optimization module is used to adjust the production process in response to the decision support instructions and optimize the dynamic weighting coefficients based on the comprehensive risk index of historical production batches.

[0014] Preferably, the environmental risk value for commencement of construction in the group of risk values ​​is generated in the following ways:

[0015] The measured dew point temperature of the data collection pipeline system was recorded.

[0016] The measured dew point temperature is compared with the preset upper limit of the qualified dew point temperature;

[0017] If the measured dew point temperature is higher than the upper limit of the qualified dew point temperature, the operating environment risk value is calculated and generated based on the deviation between the measured dew point temperature and the upper limit of the qualified dew point temperature, and the preset dew point risk sensitivity coefficient.

[0018] If the measured dew point temperature is lower than or equal to the upper limit of the qualified dew point temperature, then the risk value of the operating environment is determined to be zero.

[0019] Preferably, the material proportion risk value in the group of component risk values ​​is generated in the following ways:

[0020] Obtain the real-time molar ratio of fluorine to xenon;

[0021] The real-time monitored molar ratio of fluorine to xenon is compared with the preset target molar ratio to determine the molar ratio deviation.

[0022] The molar ratio deviation value is normalized to the preset total allowable deviation range of the process to obtain the relative deviation value;

[0023] Based on the relative deviation value and the preset risk sensitivity index, the material ratio risk value is calculated and generated.

[0024] Preferably, the reaction condition risk value in the group of component risk values ​​is generated in the following ways:

[0025] Collect real-time temperature and pressure inside the reactor;

[0026] Based on the comparison between the real-time temperature and the preset upper limit of the normal reaction temperature, the temperature exceedance value is determined, and based on the temperature exceedance value and the preset temperature risk weighting coefficient, a temperature risk item is calculated and generated.

[0027] Based on the comparison between the real-time pressure and the preset normal response pressure operating upper limit, the pressure over-limit value is determined, and based on the pressure over-limit value and the preset pressure risk weighting coefficient, a pressure risk item is calculated and generated.

[0028] The risk values ​​for the reaction conditions are generated by weighted summation of the temperature risk term and the pressure risk term.

[0029] Preferably, the equipment status risk value in the group of risk values ​​is generated in the following ways:

[0030] For each pre-defined key equipment component, determine its total risk level;

[0031] Based on the preset risk weight coefficients of each key equipment component, the total risk of each key equipment component is weighted and summed to generate the equipment status risk value.

[0032] Preferably, the method for determining the total risk level of the component includes:

[0033] The response time of the key equipment components is obtained, and a real-time status risk is calculated and generated based on the response time.

[0034] Obtain the cumulative number of working cycles of the key equipment components, and calculate the cumulative aging risk based on the cumulative number of working cycles;

[0035] The total risk level of the component is determined by combining the real-time status risk and the cumulative aging risk.

[0036] Preferably, the risk level early warning and decision support module is specifically used for:

[0037] Preset risk thresholds, high-risk risk thresholds, and emergency risk thresholds;

[0038] If the comprehensive risk index is lower than the risk threshold, then the current risk level is determined to be a safe level;

[0039] If the comprehensive risk index is higher than or equal to the risk threshold of concern and lower than the high-risk threshold, then the current risk level is determined to be a level of concern, and a highlighting parameter instruction is output.

[0040] If the comprehensive risk index is higher than or equal to the high-risk threshold and lower than the emergency risk threshold, then the current risk level is determined to be high-risk, and a command to reduce heating power is output.

[0041] If the comprehensive risk index is higher than or equal to the emergency risk threshold, the current risk level is determined to be an emergency level, and a chain shutdown command is output.

[0042] Preferably, the risk level early warning and decision support module is further used for:

[0043] If the risk value of the operating environment is non-zero, then during the start-up preparation stage, the current risk level is determined to be a prohibited start-up level, and a command to forcibly lock the feed valve is output.

[0044] Preferably, the security policy adaptive optimization module includes:

[0045] The stage adaptive unit is used to record the material ratio risk value generated at the end of the raw material feeding stage, and to correct the dynamic weight coefficient of the subsequent heating reaction stage based on the material ratio risk value.

[0046] The periodic adaptive unit is used to store the comprehensive risk index data stream of historical production batches, and to perform long-term optimization of the dynamic weight coefficients through statistical analysis of the data stream.

[0047] This invention provides an improved safety management system for hazardous chemical production based on dynamic risk assessment, which has the following improvements and advantages compared to existing technologies:

[0048] 1. This invention overcomes the shortcomings of traditional methods that rely on a single assessment dimension. By collecting process parameters and equipment status parameters from the production process, it quantifies these multi-source and heterogeneous parameters into standardized sub-risk values, ultimately merging them into a comprehensive risk index. This approach makes the originally abstract and fragmented safety status intuitive and quantifiable, providing managers with a comprehensive and accurate understanding of the overall system safety status.

[0049] 2. This invention introduces a dynamic weighting coefficient, which allows the system to automatically adjust the importance of different sub-risks in the comprehensive assessment based on the specific process stage at present. This enables the focus of risk monitoring to be dynamically focused on the most critical link at the current stage, greatly improving the pertinence and effectiveness of early warning.

[0050] 3. This invention changes the passive situation of delayed risk response in the past. By setting multiple risk thresholds such as attention, high risk, and emergency, the comprehensive risk index is compared with the preset level in real time. The system can not only issue early warnings, but also automatically output emergency handling instructions from reminders to preventive interventions and even chain shutdowns according to the risk level, forming a forward-looking automated safety management closed loop from early warning to decision-making.

[0051] 4. By establishing a safety strategy adaptive optimization module, this invention enables the system to have the ability to learn and evolve on its own. The system can not only adjust the evaluation weight of the subsequent stage based on the risk performance of the previous stage within a single production batch, but also span multiple production cycles. Through statistical analysis of massive historical risk data, it can optimize the risk assessment model over a long period of time. This dual-dimensional adaptive learning mechanism ensures that the safety strategy can continuously improve itself and become more and more in line with actual working conditions. Attached Figure Description

[0052] The present invention will be further explained below with reference to the accompanying drawings and embodiments:

[0053] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions of the present invention will be described in detail below. It should be noted that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0055] Example 1

[0056] Please see Figure 1 A hazardous chemical production safety management system based on dynamic risk assessment, characterized in that it includes:

[0057] The risk factor quantification module is used to collect process parameters and equipment status parameters of the hazardous chemical production process, and quantify them to generate a set of component risk values; the component risk values ​​include at least the operating environment risk value, material ratio risk value, reaction condition risk value, and equipment status risk value;

[0058] The dynamic risk assessment module is used to obtain the dynamic weight coefficients corresponding to the preset process stages, and calculate the comprehensive risk index by combining the dynamic weight coefficients and a set of component risk values.

[0059] The risk level early warning and decision support module is used to compare the comprehensive risk index with the preset risk level threshold, generate the current risk level, and output decision support instructions based on the current risk level.

[0060] The safety strategy adaptive optimization module is used to adjust the production process in response to decision support instructions and optimize the dynamic weighting coefficients based on the comprehensive risk index of historical production batches.

[0061] This invention provides a safety management system for the production of hazardous chemicals based on dynamic risk assessment, which can be applied to the production process of high-risk chemicals such as the synthesis of xenon difluoride. The system aims to overcome the shortcomings of existing technologies, such as lagging risk identification, single assessment dimensions, and inability to dynamically adapt to changes in process stages.

[0062] In this embodiment, the system is deployed on a hardware platform that includes an industrial computer, a programmable logic controller / distributed control system, and various sensors. The system's functionality relies on a series of algorithm modules running within the industrial computer. These modules work together to form a complete technical closed loop.

[0063] The system's risk factor quantification module aims to transform the multi-source, heterogeneous raw parameters collected during the production process into unified, comparable risk metrics. In this embodiment, the module continuously collects process parameters (such as temperature, pressure, and flow rate) and equipment status parameters (such as valve response time and equipment operating cycle) from the hardware platform for the production of hazardous chemicals, and performs quantification calculations based on these parameters to generate a set of component risk values. Specifically, this set of component risk values ​​includes at least the operating environment risk value, which will be discussed in detail later. Material proportion risk value Risk value of reaction conditions and equipment condition risk value ;

[0064] The system's dynamic risk assessment module aims to comprehensively evaluate various sub-risks in a prioritized and focused manner based on different stages of production, deriving a quantitative index that represents the system's current overall safety status. This module obtains predefined dynamic weighting coefficients corresponding to preset process stages (e.g., start-up preparation, raw material feeding, heating and reaction stages), and combines these with a set of sub-risk values ​​calculated by the risk factor quantification module. Finally, it uses a top-level comprehensive risk assessment formula to calculate the comprehensive risk index.

[0065] ;

[0066] in: The comprehensive risk index of the system at time t is a normalized dimensionless value. The larger the value, the higher the risk. The calculation result is output to the risk level warning and decision support module. Let be the quantified risk value of the i-th sub-item risk at time t, dimensionless, derived from the calculation output of the risk factor quantification module. In this scheme, it specifically includes... , , and ; Let be the dynamic weight coefficient of the i-th sub-item risk at time t, which is dimensionless and satisfies . Its source is preset by the main control system based on the current process stage. For example, in the feeding stage, The weight is highest during the reaction phase. The weight is the highest; This represents the total number of individual risks included in the assessment.

[0067] The system's risk level early warning and decision support module aims to transform abstract risk indices into instructions that operators can understand and execute. This module compares the comprehensive risk index calculated by the dynamic risk assessment module with the preset risk level threshold, generates the current risk level, and outputs corresponding decision support instructions based on the current risk level. For example, when the risk level is high, the module outputs an instruction to reduce the heating power.

[0068] The system's safety strategy adaptive optimization module aims to endow the system with the ability to learn and evolve, enabling its safety strategy to be continuously optimized. On the one hand, this module responds to decision support instructions and coordinates with the control system to adjust the production process; on the other hand, it performs long-term statistical analysis and optimization of the dynamic weight coefficients used by the dynamic risk assessment module based on the comprehensive risk index data stream of historical production batches, thereby making the risk model increasingly consistent with actual working conditions.

[0069] This embodiment constructs a safety management closed loop that enables proactive early warning, comprehensive assessment, process self-adaptation, and scientific decision-making through the collaborative work of the aforementioned modules. It quantifies complex production states into intuitive risk indices, not only predicting risks in advance but also dynamically adjusting monitoring priorities according to process stages. Furthermore, it continuously learns and optimizes itself, fundamentally improving the inherent safety level of hazardous chemical production processes.

[0070] Example 2

[0071] The environmental risk value for commencement of construction, which is part of a set of risk items, is generated in the following ways:

[0072] The measured dew point temperature of the data collection pipeline system was recorded.

[0073] Compare the measured dew point temperature with the preset upper limit of the qualified dew point temperature;

[0074] If the measured dew point temperature is higher than the upper limit of the qualified dew point temperature, the operating environment risk value is calculated and generated based on the deviation between the measured dew point temperature and the upper limit of the qualified dew point temperature, as well as the preset dew point risk sensitivity coefficient.

[0075] If the measured dew point temperature is lower than or equal to the upper limit of the qualified dew point temperature, the risk value of the operating environment is determined to be zero.

[0076] This embodiment further illustrates Embodiment 1. To ensure that the critical safety condition of cleanliness and dryness of the pipeline system is met before the production process starts, the quantification logic of the start-up environment risk is as follows:

[0077] The module uses a high-precision dew point sensor deployed in the pipeline system to collect the measured dew point temperature of the pipeline system. ,Will With respect to the preset upper limit of the qualified dew point temperature In comparison, the upper limit of the acceptable dew point temperature is a constant set according to the process safety regulations, representing the highest moisture content that the process can tolerate.

[0078] like This indicates that the pipeline dryness is unqualified, posing a safety risk. In this case, the module determines the dryness based on the deviation between the two values. ), and the preset dew point risk sensitivity coefficient. The environmental risk value for construction commencement is calculated using the following custom saturation effect exponential function model:

[0079]

[0080] in: The environmental risks at the start of construction are dimensionless, and their calculation results are a prerequisite for all subsequent operations. The dew point risk sensitivity coefficient ensures that the power term of the index is dimensionless. Its source is either empirically determined or calibrated using experimental data. The calibration goal is to ensure that the calculated value reflects historically minor process anomalies caused by pipeline dampness. The value can effectively trigger a warning at the level of concern, reflecting the sensitivity of the process to moisture.

[0081] The risk increases dramatically and non-linearly with the degree of dew point exceedance; even a slight exceedance can generate a sufficiently strong risk signal.

[0082] Conversely, if If the environment meets the safety requirements, the module directly determines that the risk value of the working environment is zero.

[0083] Compared to simple threshold alarms, the exponential model used in this embodiment can non-linearly amplify the risk signal caused by exceeding the standard deviation. This allows the system to not only determine whether something is qualified or unqualified, but also quantify the severity of the unqualified behavior, providing a more refined input for risk assessment. Simultaneously, through... The function ensures that the risk is absolutely zero under qualified conditions, and its rigorous logic provides a clear and reliable basis for subsequent decisions such as prohibiting construction.

[0084] Example 3

[0085] The material proportion risk value in a group of risk values ​​is generated in the following ways:

[0086] Obtain the real-time molar ratio of fluorine to xenon;

[0087] The molar ratio of fluorine to xenon gas monitored in real time is compared with the preset target molar ratio to determine the deviation value of the molar ratio;

[0088] The molar ratio deviation is normalized to the preset total allowable deviation range of the process to obtain the relative deviation value;

[0089] Based on the relative deviation value and the preset risk sensitivity index, the material proportion risk value is calculated and generated.

[0090] This embodiment generates material ratio risk values ​​using the risk factor quantification module in Embodiment 1. One specific implementation of this is the quantification of material ratio risk, which aims to accurately monitor the deviation of the reactant molar ratio, which is the key to ensuring a stable, efficient, and safe reaction.

[0091] The module acquires the real-time molar ratio of fluorine to xenon. The parameter is obtained by measuring the instantaneous flow rates of fluorine (F2) and xenon (Xe) through a mass flow meter on the raw material pipeline, and calculating the real-time molar ratio based on their respective molar masses. It is a dimensionless value.

[0092] Will Compared with the preset target molar ratio Compare them to determine the molar ratio deviation. It is derived from the process formulation database and represents the theoretically optimal reaction ratio.

[0093] To ensure standardized comparability of this deviation value, the absolute value of the molar ratio deviation is normalized to a preset total allowable deviation range for the process, thus obtaining a relative deviation value. Here, the total deviation range is determined by the upper limit of the allowable molar ratio for the process. and lower limit The difference was determined by the results of process safety analyses, such as hazard and operability analyses.

[0094] Based on this relative deviation value and the preset risk sensitivity index The material proportion risk value is calculated using the following formula. :

[0095]

[0096] in: For material proportioning risk, dimensionless, input to the top level. formula; This is a risk sensitivity index, dimensionless, typically taking a value greater than 1. It is derived from statistical analysis based on historical data or simulation experiments; for example, regression analysis is used to find the index that best fits the severity of risk events caused by historical mismatches. Values ​​are used to optimize the shape of the risk curve; when At that time, the risk value generated by small deviations is low, while the risk value generated by large deviations increases sharply;

[0097] By normalizing the data, the influence of dimensions is eliminated, making the risk values ​​universally comparable. More importantly, an adjustable risk sensitivity index is introduced. This makes the risk assessment model no longer linear, but customizable according to process characteristics, allowing it to exhibit differentiated sensitivity to different degrees of process deviation, greatly improving the accuracy and practicality of risk quantification.

[0098] Example 4

[0099] The reaction condition risk value in a component of the risk value set is generated in the following ways:

[0100] Collect real-time temperature and pressure inside the reactor;

[0101] Based on the comparison between the real-time temperature and the preset upper limit of the normal reaction temperature, the temperature exceedance value is determined, and based on the temperature exceedance value and the preset temperature risk weighting coefficient, a temperature risk item is calculated and generated.

[0102] Based on the comparison between real-time pressure and the preset normal response pressure operating limit, the pressure over-limit value is determined, and based on the pressure over-limit value and the preset pressure risk weight coefficient, a pressure risk item is calculated and generated.

[0103] The risk values ​​for temperature and pressure are weighted and summed to generate the risk values ​​for reaction conditions.

[0104] The purpose of quantifying the risk of reaction conditions in this embodiment is to monitor core reaction parameters, especially the risk of runaway due to overheating and overpressure in exothermic reactions such as the synthesis of xenon difluoride.

[0105] The module collects real-time temperature data from thermocouples and pressure sensors deployed within the reactor. and real-time pressure ;

[0106] To address temperature risks, the module is based on Operating at the preset normal reaction temperature upper limit By comparing the values, the temperature exceeding the limit is determined, which is the upper limit of operation here. Derived from process operating procedures or detailed process design documents; used here The function aims to focus only on cases where the temperature exceeds the limit, filtering out safe conditions below the upper limit; this is based on the temperature exceedance value and a preset temperature risk weighting coefficient. The temperature risk term is calculated and generated through normalization and square amplification.

[0107] To address stress risks, the module is based on Operating upper limit of the preset normal reaction pressure By comparing the values, the pressure exceeding the limit can be determined. Based on the pressure exceedance value and the preset pressure risk weighting coefficient, the pressure is calculated. Calculate and generate stress risk items;

[0108] The module performs a weighted summation of the temperature and pressure risk terms, and generates the final reaction condition risk value using the following formula. :

[0109]

[0110] in: The overall risk value for the reaction conditions is dimensionless. These are the extreme temperature and pressure thresholds for interlocking shutdowns, in °C and MPa, derived from safety design parameters such as the material tolerance limits of the equipment or the setting values ​​of safety valves, and used for normalization. The risk weighting coefficients for temperature and pressure are dimensionless, and This is derived from HAZOP analysis, determined after assessing the severity of the consequences of both getting out of control, for example... ;

[0111] pass The function model precisely focuses on the more serious risks of exceeding limits, meeting the core requirements of chemical safety management; the use of squared terms to amplify deviations reflects the nonlinear characteristic of risk deteriorating rapidly with increasing deviations, enabling earlier and stronger early warning signals; through and The coefficient allows for flexible adjustment of its contribution to overall risk based on the different levels of risk of temperature and pressure runaway in a specific process, making the assessment more targeted.

[0112] Example 5

[0113] The equipment status risk value in a set of component risk values ​​is generated in the following ways:

[0114] For each pre-defined key equipment component, determine its total risk level;

[0115] Based on the preset risk weight coefficients of each key equipment component, the total risk of each key equipment component is weighted and summed to generate the equipment status risk value.

[0116] The methods for determining the total risk level of a component include:

[0117] Obtain the response time of key equipment components and calculate and generate real-time status risks based on the response time;

[0118] Obtain the cumulative number of working cycles for key equipment components, and calculate the cumulative aging risk based on the cumulative number of working cycles;

[0119] The total risk level of a component is determined by combining real-time status risk and cumulative aging risk.

[0120] This embodiment details the method for determining the risk level of key components, with the aim of integrating predictive maintenance concepts and incorporating equipment health status as a continuous background risk into the overall assessment.

[0121] The method for generating equipment status risk values ​​involves determining the total risk level of each pre-defined critical equipment component, such as an emergency shut-off valve or a circulating pump. Based on the preset risk weight coefficients of each key equipment component The risk levels of all key components are weighted and summed to generate the overall equipment status risk value. :

[0122]

[0123] in: Let be the risk weight coefficient of the j-th component, which is dimensionless and This is based on the results of failure mode and effects analysis, with critical safety components having a higher weight. Let be the normalized total risk of the j-th critical equipment or component at time t, which is dimensionless and its value is between [0,1]. The total number of key equipment components included in the assessment;

[0124] Total risk of components The determination method integrates real-time state risk and cumulative aging risk, including:

[0125] Obtain the response time of key equipment components Taking a valve as an example, and calculating and generating real-time status risk based on this response time. , It reflects the immediate degradation of equipment performance, and its calculation formula is as follows:

[0126]

[0127] in: This is the normal response time of the component. To characterize the response time of its failure, these two parameters are derived from the equipment manual or online testing;

[0128] Obtain the cumulative number of working cycles for this critical equipment component. The cumulative aging risk is calculated based on this cumulative number of work cycles. , This reflects the natural wear and tear of equipment over its service life, and its calculation formula is as follows:

[0129]

[0130] in: The design life cycle count is derived from the equipment design specifications. It is a constant that adjusts the shape of the aging curve and can be determined based on the Weibull distribution reliability model of the component;

[0131] Based on the above real-time status risk and cumulative aging risk, the total risk level of the component is determined. :

[0132]

[0133] As long as either the real-time risk or the aging risk approaches 1, the total component risk approaches 1. Only when both risks are low will the total risk be low.

[0134] This embodiment achieves an in-depth assessment of equipment risks, through... Detect early warning signs of sudden malfunctions, such as valve jamming causing slow response, through... Quantitative progressive aging, and then through The formula organically combines the two, and ultimately, The formula aggregates the health status of all key components into a unified, dynamically updated equipment risk index, providing crucial and predictive background input for overall risk assessment.

[0135] Example 6

[0136] The risk level early warning and decision support module is specifically used for:

[0137] Preset risk thresholds, high-risk risk thresholds, and emergency risk thresholds;

[0138] If the overall risk index is lower than the risk threshold, the current risk level is determined to be safe.

[0139] If the comprehensive risk index is higher than or equal to the risk threshold of concern but lower than the high-risk threshold, the current risk level is determined to be the risk level of concern, and the parameter highlighting instruction is output.

[0140] If the comprehensive risk index is higher than or equal to the high-risk threshold but lower than the emergency risk threshold, the current risk level is determined to be high-risk, and a command to reduce heating power is output.

[0141] If the comprehensive risk index is higher than or equal to the emergency risk threshold, the current risk level is determined to be emergency level, and a chain shutdown command is output.

[0142] The risk level early warning and decision support module is also used for:

[0143] If the environmental risk value is non-zero, then during the start-up preparation phase, the current risk level is determined to be the prohibited start-up level, and a forced lock command for the feed valve is output.

[0144] The purpose of this embodiment is to establish a tiered, automated risk response mechanism;

[0145] The Risk Level Early Warning and Decision Support module is specifically used for:

[0146] Multiple risk level thresholds are preset within the system. In this embodiment, they are specifically the risk threshold of concern, the risk threshold of high risk, and the risk threshold of emergency. These thresholds can be set based on historical data statistical analysis. For example, specific percentile values ​​of the comprehensive risk index in historical normal production batches, such as 75%, 90%, and 95%, can be defined as the risk thresholds of concern, high risk, and emergency, respectively.

[0147] During system operation, the module continuously... Compare with these thresholds:

[0148] like If the risk level is below the threshold for risk of concern, the current risk level is determined to be a safe level.

[0149] like If the risk level is higher than or equal to the risk threshold of concern but lower than the risk threshold of high risk, the current risk level is determined to be the risk level of concern, and a highlighting parameter instruction is output to the human-machine interface to remind the operator to pay attention to the main sub-risks that cause the risk index to rise.

[0150] like If the risk level is higher than or equal to the high-risk threshold but lower than the emergency risk threshold, the current risk level is determined to be high-risk, and a command to reduce heating power is automatically sent to the PLC / DCS for preventive intervention.

[0151] like If the risk level is higher than or equal to the emergency risk threshold, the current risk level is determined to be an emergency level, and a chain shutdown command is automatically output to execute the emergency shutdown procedure.

[0152] In addition, the risk level early warning and decision support module also integrates a special, highest-priority judgment logic; specifically, this module is also used for:

[0153] During the start-up preparation phase of the production process, if the start-up environment risk value calculated in Example 2... If the value is non-zero, the module will ignore the current value. The value directly determines the current risk level as the prohibited operation level, and immediately outputs a forced locking command to the actuator for the feed valve, and issues a clear alarm message to the operator;

[0154] This design constructs a three-dimensional decision-making system that combines conventional tiered responses with special pre-emptive vetoes. This embodiment enables the system to take progressive and matched responses, from alerts and interventions to shutdowns, based on the severity of the risk, avoiding overreaction or underreaction. It ensures that the entire security system will never start if the basic conditions are not met, embodying the security design concept of defense in depth and greatly enhancing the robustness of the system.

[0155] Example 7

[0156] The security policy adaptive optimization module includes:

[0157] The stage adaptive unit is used to record the material ratio risk value generated at the end of the raw material feeding stage, and to correct the dynamic weight coefficient of the subsequent heating reaction stage based on the material ratio risk value.

[0158] The periodic adaptive unit is used to store the comprehensive risk index data stream of historical production batches and to perform long-term optimization of the dynamic weight coefficients through statistical analysis of the data stream.

[0159] This embodiment details how its internal units achieve short-term and long-term adaptive optimization, with the aim of enabling the system to learn from experience and continuously evolve risk models and control strategies.

[0160] In this embodiment, the module specifically includes two core units:

[0161] Stage Adaptive Unit: This unit is responsible for dynamically adjusting the risk assessment strategy for subsequent stages within a single production batch based on the execution status of the previous process stage; the unit monitors and records in real time the final material ratio risk value generated at the end of the raw material feeding stage. If the If the value exceeds an internally set excellent threshold, which is determined based on statistical analysis of historical high-quality production batch data or expert experience, the unit will determine that there is potential instability in this feed; therefore, it will base its decision on this threshold. The value automatically adjusts the dynamic weighting coefficients for the upcoming heating reaction phase; for example, it adjusts the weighting of reaction condition risk. The value was temporarily increased from the default 0.7 to 0.75, thus giving greater attention to fluctuations in temperature and pressure in subsequent stages;

[0162] Cycle Adaptive Unit: This unit is responsible for long-term, strategic model optimization across multiple production batches; the unit stores a complete comprehensive risk index data stream for each historical production batch, including... and all sub-risks The unit collects continuous data; after accumulating enough data, it performs statistical analysis on these massive data streams, for example, analyzing which sub-risk contributes the most and occurs most frequently among all high-risk events; based on these statistical insights, the unit can make suggestions to system engineers, or automatically optimize dynamic weight coefficients or deeper model parameters over a long period of time with authorization.

[0163] This embodiment endows the system with dual learning capabilities by setting two adaptive units with different time scales; the stage adaptive unit enables rapid response, allowing the system to more intelligently cope with process fluctuations in a single production run; the cycle adaptive unit achieves deep optimization, continuously iterating the risk model through big data analysis to more accurately reflect the real risk characteristics of specific equipment; this dual-modal adaptive mechanism constitutes a complete "perception-analysis-decision-learning" closed loop, enabling the entire safety management system to continuously improve itself;

[0164] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the technical solutions of the present invention.

Claims

1. A hazardous chemical production safety management system based on dynamic risk assessment, characterized in that: include: The risk factor quantification module is used to collect process parameters and equipment status parameters of the hazardous chemical production process, and quantify them based on the process parameters and equipment status parameters to generate a set of component risk values; The sub-risk values ​​include at least the operating environment risk value, material ratio risk value, reaction condition risk value, and equipment status risk value; The dynamic risk assessment module is used to obtain the dynamic weight coefficients corresponding to the preset process stages, and calculate the comprehensive risk index by combining the dynamic weight coefficients and the group of component risk values. The risk level warning and decision support module is used to compare the comprehensive risk index with the preset risk level threshold, generate the current risk level, and output decision support instructions based on the current risk level. The safety strategy adaptive optimization module is used to adjust the production process in response to the decision support instructions and optimize the dynamic weight coefficient based on the comprehensive risk index of historical production batches. The equipment status risk value in the group of risk values ​​is generated in the following ways: For each pre-defined key equipment component, determine its total risk level; Based on the preset risk weight coefficients of each key equipment component, the total risk of each key equipment component is weighted and summed to generate the equipment status risk value. The methods for determining the total risk of the component include: The response time of the key equipment components is obtained, and a real-time status risk is calculated and generated based on the response time. It reflects the immediate degradation of equipment performance, and its calculation formula is as follows: ； in: This is the normal response time of the component. To characterize the response time of its failure, these two parameters are derived from the equipment manual or online testing; Obtain the cumulative number of working cycles for the key equipment components, and calculate the cumulative aging risk based on the cumulative number of working cycles. ; This reflects the natural wear and tear of equipment over its service life, and its calculation formula is as follows: ； in: The design life cycle count is derived from the equipment design specifications. It is a constant that adjusts the shape of the aging curve and can be determined based on the Weibull distribution reliability model of the component; The total risk level of the component is determined by combining the real-time status risk and the cumulative aging risk. ; ； The risk levels of all key components are weighted and summed to generate the overall equipment condition risk value. : ； in: Let be the risk weight coefficient of the j-th component, which is dimensionless and This is based on the results of failure mode and effects analysis, with critical safety components having a higher weight. Let be the normalized total risk of the j-th critical equipment or component at time t, which is dimensionless and its value is between [0,1]. The total number of key equipment components included in the assessment; The environmental risk value for commencement of construction, which is one of the group of risk values, is generated in the following ways: The measured dew point temperature of the data collection pipeline system was recorded. The measured dew point temperature is compared with the preset upper limit of the qualified dew point temperature; If the measured dew point temperature is higher than the upper limit of the qualified dew point temperature, the operating environment risk value is calculated and generated based on the deviation between the measured dew point temperature and the upper limit of the qualified dew point temperature, and the preset dew point risk sensitivity coefficient. If the measured dew point temperature is lower than or equal to the upper limit of the qualified dew point temperature, then the risk value of the operating environment is determined to be zero.

2. The hazardous chemical production safety management system based on dynamic risk assessment according to claim 1, characterized in that, The material proportion risk value in the aforementioned group of risk values ​​is generated in the following ways: Obtain the real-time molar ratio of fluorine to xenon; The real-time monitored molar ratio of fluorine to xenon is compared with the preset target molar ratio to determine the molar ratio deviation. The molar ratio deviation value is normalized to the preset total allowable deviation range of the process to obtain the relative deviation value; Based on the relative deviation value and the preset risk sensitivity index, the material ratio risk value is calculated and generated.

3. The hazardous chemical production safety management system based on dynamic risk assessment according to claim 1, characterized in that, The reaction condition risk value in the group of component risk values ​​is generated in the following ways: Collect real-time temperature and pressure inside the reactor; Based on the comparison between the real-time temperature and the preset upper limit of the normal reaction temperature, the temperature exceedance value is determined, and based on the temperature exceedance value and the preset temperature risk weighting coefficient, a temperature risk item is calculated and generated. Based on the comparison between the real-time pressure and the preset normal response pressure operating upper limit, the pressure over-limit value is determined, and based on the pressure over-limit value and the preset pressure risk weight coefficient, a pressure risk item is calculated and generated. The risk values ​​for the reaction conditions are generated by weighted summation of the temperature risk term and the pressure risk term.

4. The hazardous chemical production safety management system based on dynamic risk assessment according to claim 1, characterized in that, The risk level early warning and decision support module is specifically used for: Preset risk thresholds, high-risk risk thresholds, and emergency risk thresholds; If the comprehensive risk index is lower than the risk threshold, then the current risk level is determined to be a safe level; If the comprehensive risk index is higher than or equal to the risk threshold of concern and lower than the high-risk threshold, then the current risk level is determined to be a level of concern, and a highlighting parameter instruction is output. If the comprehensive risk index is higher than or equal to the high-risk threshold and lower than the emergency risk threshold, then the current risk level is determined to be high-risk, and a command to reduce heating power is output. If the comprehensive risk index is higher than or equal to the emergency risk threshold, the current risk level is determined to be an emergency level, and a chain shutdown command is output.

5. The hazardous chemical production safety management system based on dynamic risk assessment according to claim 1, characterized in that, The risk level early warning and decision support module is also used for: If the risk value of the operating environment is non-zero, then during the start-up preparation stage, the current risk level is determined to be a prohibited start-up level, and a command to forcibly lock the feed valve is output.

6. The hazardous chemical production safety management system based on dynamic risk assessment according to claim 2, characterized in that, The security policy adaptive optimization module includes: The stage adaptive unit is used to record the material ratio risk value generated at the end of the raw material feeding stage, and to correct the dynamic weight coefficient of the subsequent heating reaction stage based on the material ratio risk value. The periodic adaptive unit is used to store the comprehensive risk index data stream of historical production batches, and to perform long-term optimization of the dynamic weight coefficients through statistical analysis of the data stream.

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