A reactor combination early warning system and early warning method

Abstract

The application discloses a reactor combined early warning system and early warning method, comprising a temperature acquisition unit, a pressure acquisition unit, a data processing unit, an early warning unit, a pressure relief execution unit and a working condition monitoring auxiliary unit; the application has the beneficial effects that: the temperature acquisition unit adopts three high-temperature-resistant sensors distributed in the upper, middle and lower regions of the reactor, combined with a 1-10 Hz acquisition frequency and a ±0.1 DEG C acquisition accuracy, to realize comprehensive coverage and accurate capture of the internal temperature field of the reactor; the pressure acquisition unit adopts two symmetrically arranged high-precision pressure transmitters to synchronously acquire static pressure Pstatic and dynamic pressure Pdynamic; the working condition monitoring auxiliary unit supplements the acquisition of auxiliary parameters such as feed flow Q, reaction medium viscosity mu and stirring speed n, to provide multi-dimensional data support for subsequent parameter calibration and working condition adaptation, and solve the one-sidedness of early warning judgment caused by the insufficient data dimension of the prior art which only relies on a single temperature and pressure parameter.

Description

Technical Field

[0001] This invention relates to a reactor combination early warning system and early warning method. Background Technology

[0002] As core equipment in industries such as chemical, petroleum, and pharmaceutical, the safety of reactor operation directly affects production continuity, equipment lifespan, and personnel safety. The internal reaction system of a reactor is complex, and key parameters such as temperature and pressure are easily affected by factors such as feed flow rate, media characteristics, and stirring conditions. Once abnormal parameters become uncontrollable, they can easily lead to safety accidents such as overheating and overpressure, causing serious economic losses and safety risks. Therefore, real-time early warning and risk management systems for reactors have become a critical technological requirement in industrial production.

[0003] Currently, reactor early warning systems used in industrial applications mostly rely on a single temperature or pressure parameter as the core judgment basis, achieving abnormal early warning and pressure relief control by setting fixed thresholds. However, this traditional technical solution has significant technical defects: First, the parameter acquisition dimension is singular, relying only on single-point temperature or pressure data, which cannot comprehensively reflect the internal temperature field distribution and dynamic pressure fluctuation characteristics of the reactor, and does not combine auxiliary operating parameters such as feed flow rate and medium viscosity, resulting in one-sided early warning judgment and high false alarm and false alarm rates; Second, the design of benchmark values ​​and weighting coefficients is rigid. Existing systems mostly use fixed safety benchmark values ​​and parameter weights, which cannot adapt to the slow changes in operating conditions during long-term reactor operation (such as equipment performance degradation and process parameter fine-tuning), nor can they accurately adapt to the core risk differences of different process types of reactors such as exothermic, endothermic, and pressure-dominated reactors, resulting in insufficient targeting of early warnings; Third, the response to temperature and pressure surges is lagging. Traditional systems only make threshold judgments based on steady-state parameters and do not consider the instantaneous change trend of temperature and pressure. When a sudden increase in temperature and pressure occurs due to reaction runaway, the response is delayed. During sudden pressure drops, the feature value update lags, easily missing the optimal early warning and response opportunity; fourth, the pressure relief control method is crude, mostly adopting a single opening pressure relief mode, lacking a pressure closed-loop control mechanism, which easily leads to a sudden pressure drop during the pressure relief process, causing impact damage to the reactor wall, seals and other structures, and may also affect the stability of the reaction process due to excessive pressure relief; fifth, the system's fault tolerance and redundancy design are insufficient, lacking real-time fault diagnosis and backup switching mechanisms for the acquisition unit and execution unit, which can easily lead to system paralysis when the core unit fails, and lacks an effective manual intervention backup plan in extreme failure scenarios, failing to guarantee full-process safety control; sixth, the data processing accuracy is insufficient, and no targeted processing is performed on random interference and abnormal data in the acquired data, resulting in distorted baseline value fitting, further affecting the accuracy of early warning judgment. In view of this, the present invention proposes a reactor combined early warning system and early warning method to solve the above problems. Summary of the Invention

[0004] The purpose of this invention is to provide a reactor combination early warning system and method to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A reactor combined early warning system includes a temperature acquisition unit, a pressure acquisition unit, a data processing unit, an early warning unit, a pressure relief execution unit, and an operating condition monitoring auxiliary unit.

[0007] The temperature acquisition unit includes at least three distributed high-temperature pressure sensors, which are embedded in the upper, middle and lower regions inside the reactor, respectively, to acquire the real-time temperatures T1, T2 and T3 of each region. The acquired temperature data is filtered and denoised before being transmitted to the data processing unit. The acquisition frequency is 1~10Hz and the temperature acquisition accuracy is ±0.1℃.

[0008] The pressure acquisition unit includes two high-precision pressure transmitters symmetrically arranged on the top of the reactor, which are used to acquire the static pressure P1 and dynamic pressure P2 at the top of the reactor in real time. After eliminating pressure fluctuation interference, the data is transmitted to the data processing unit. The pressure acquisition accuracy is ±0.001MPa, and the acquisition frequency is matched with the temperature acquisition unit.

[0009] The operating condition monitoring auxiliary unit is used to collect auxiliary operating condition parameters such as reactor feed flow rate Q, reaction medium viscosity μ, and stirring speed n, providing a basis for parameter calibration of the data processing unit;

[0010] The data processing unit incorporates a coupling calculation module, a baseline self-learning module, a working condition adaptation module, and a logic judgment module. The coupling calculation module, based on input data from the temperature acquisition unit, pressure acquisition unit, and auxiliary unit, calculates the coupling characteristic value K according to a preset temperature-pressure coupling formula. The coupling formula is as follows:

[0011] ;

[0012] In the formula: α is the temperature weighting coefficient, and β is the pressure weighting coefficient. δ is the auxiliary working condition correction coefficient, ranging from 0.05 to 0.15; T0 is the preset safe temperature reference value, and P0 is the preset safe pressure reference value; f(Q,μ,n) is the auxiliary working condition coupling function, expressed as follows: k1, k2, and k3 are auxiliary parameter weighting coefficients. Q0, μ0, and n are the reference values ​​of feed flow rate, medium viscosity, and stirring speed under rated operating conditions, respectively.

[0013] The baseline self-learning module is used to dynamically update T0, P0, Q0, μ0, and n0 based on the average temperature, average pressure, and average auxiliary parameters under 72 hours of continuous stable operation of the reactor, using the least squares method for fitting. The judgment criteria are: temperature fluctuation ≤ ±2℃, pressure fluctuation ≤ ±0.05MPa, and flow fluctuation ≤ ±5%.

[0014] The operating condition adaptation module is used to adaptively adjust the values ​​of α, β, δ and k1, k2, k3 according to the reactor process type and real-time auxiliary operating condition parameters. The reactor process types include exothermic, endothermic, and pressure-dominated types.

[0015] The logic judgment module pre-stores a first-level early warning threshold K1, a second-level early warning threshold K2, and a pressure relief trigger threshold K3, where K1 < K2 < K3. The threshold settings are based on the reactor material tolerance limit, the process safety window, and historical fault data calibration.

[0016] The early warning unit includes an audible and visual early warning module, a remote communication module, and a local display module. When K1≤K<K2, the audible and visual early warning module is driven to issue a low-frequency audible and visual alert, the remote communication module pushes a first-level early warning information to the monitoring terminal, and the local display module marks the parameters exceeding the standard in real time. When K2≤K<K3, the audible and visual early warning module is driven to issue a high-frequency audible and visual alarm, the remote communication module simultaneously pushes an emergency early warning text message to the mobile phone of the operation and maintenance personnel, and the local display module locks the parameters exceeding the standard and displays the trend curve.

[0017] The pressure relief execution unit is an electrically operated staged pressure relief valve assembly, including a main pressure relief valve and a backup pressure relief valve. When K≥K3, the logic judgment module first drives the main pressure relief valve to open to 30% to perform primary pressure relief, while simultaneously monitoring the change in coupling characteristic value in real time. If there is a delay... If K remains ≥ K3, the main pressure relief valve will open to 100% and the backup pressure relief valve will be activated to assist in pressure relief until K drops below K2. Then, the pressure relief valve group will automatically close and a pressure relief completion signal will be issued.

[0018] As an improvement to the above technical solution, the temperature weighting coefficient α is set to 0.3~0.7, and the pressure weighting coefficient β is set to 0.3~0.7. For exothermic reactors, α is set to 0.6~0.7 and β is set to 0.3~0.4, prioritizing response to temperature anomalies.

[0019] For pressure-dominated reactors, α = 0.3~0.4 and β = 0.6~0.7, the reactor preferentially responds to pressure anomalies.

[0020] In the endothermic reactor, both α and β are set to 0.45~0.55 to achieve a temperature and pressure equilibrium response.

[0021] As an improvement to the above technical solution, the benchmark self-learning module also includes an abnormal data removal function. When the collected temperature, pressure or auxiliary parameters exceed the rated operating condition range of ±20%, they are judged as abnormal data and automatically removed, and do not participate in the benchmark fitting calculation. At the same time, the benchmark values ​​such as T0 and P0 are dynamically corrected every 24 hours based on the stable operating condition data of the day. The correction range does not exceed ±5% of the initial benchmark value, ensuring the stability and adaptability of the benchmark values.

[0022] As an improvement to the above technical solution, the pressure relief execution unit is also equipped with a pressure feedback closed-loop control module, which collects the pressure value P_relief at the pressure relief port in real time. When P_relief exceeds the preset safe pressure relief pressure, the opening of the pressure relief valve is automatically adjusted to control P_relief within a safe range, so as to avoid the sudden pressure drop during the pressure relief process from impacting the reactor structure.

[0023] The preset safe pressure relief pressure is 1.15 times the rated pressure of the reactor.

[0024] As an improvement to the above technical solution, the coupling formula adds a double correction term for the rate of temperature change and the rate of pressure change. The formula for calculating the coupling characteristic value K' after correction is as follows:

[0025] ;

[0026] In the formula: γ is the temperature change rate correction coefficient, with a value of 0.02~0.08; ε is the pressure change rate correction coefficient, with a value of 0.02~0.08; ΔT / Δt is the temperature change per unit time, calculated using a sliding window of 1~3s; ΔP / Δt is the pressure change per unit time, with a calculation period consistent with the temperature change rate; the dual change rate correction terms compensate for the characteristic value lag error under sudden temperature and pressure changes, thereby improving the timeliness of early warning.

[0027] As an improvement to the above technical solution, the data processing unit also has a built-in fault self-diagnosis module, which can monitor the operating status of each acquisition unit, early warning unit and pressure relief execution unit in real time. When a unit experiences signal interruption, data abnormality or execution failure, it immediately issues a device fault alarm and switches to the backup unit to ensure continuous system operation. At the same time, it records fault information for easy maintenance and troubleshooting.

[0028] A reactor combination early warning method includes the following steps:

[0029] S1. System Initialization:

[0030] Set the initial values ​​of each benchmark (T0, P0, Q0, μ0, n0), the initial values ​​of the weighting coefficients (α, β, δ, k1, k2, k3), and the warning thresholds (K1, K2, K3) for each level. Start each acquisition unit, data processing unit, warning unit, and pressure relief execution unit to complete the equipment self-test.

[0031] S2. Real-time acquisition and preprocessing of multiple parameters:

[0032] The temperature acquisition unit collects the real-time temperatures T1, T2, and T3 in the upper, middle, and lower regions of the reactor; the pressure acquisition unit collects the static pressure P_static and the dynamic pressure P_dynamic at the top; and the operating condition monitoring auxiliary unit collects the feed flow rate Q, the viscosity of the reaction medium μ, and the stirring speed n. Each acquisition unit performs preprocessing on the raw data, including filtering and noise reduction and outlier removal, and transmits the effective data to the data processing unit.

[0033] S3. Dynamic Update of Baseline Values:

[0034] The data processing unit uses the baseline self-learning module to determine whether the current operating condition is a stable operating condition. If the continuous operation meets the stable operating condition judgment criteria, the baseline values ​​T0, P0, Q0, μ0, and n0 are updated based on the collected valid data. If it is an unstable operating condition, the current baseline values ​​are used.

[0035] S4. Adaptive adjustment of weighting coefficients:

[0036] The operating condition adaptation module adaptively adjusts the values ​​of α, β, δ and k1, k2, k3 according to the reactor process type and real-time auxiliary operating condition parameters, and outputs the weight coefficients that adapt to the current operating condition.

[0037] S5. Calculation of Coupled Eigenvalues:

[0038] The coupling calculation module calculates the coupling characteristic value K according to the coupling formula based on the preprocessed effective data, the dynamically updated benchmark value, and the adaptively adjusted weight coefficient. If there is a risk of sudden temperature and pressure changes, the correction formula is used to calculate K', and K' is used as the judgment basis.

[0039] S6. Multi-level response logic judgment and execution:

[0040] The logic judgment module will couple the feature value, K or K', with the warning thresholds at each level and execute the corresponding response actions:

[0041] (1) When K < K1, it is determined to be a normal working condition, the early warning unit does not act, and the system continues to collect data and monitor the working condition;

[0042] (2) When K1≤K<K2, a first-level warning is triggered, and the warning unit starts the low-frequency sound and light prompt, remote monitoring terminal warning push and local parameter labeling functions;

[0043] (3) When K2≤K<K3, a level 2 warning is triggered, and the warning unit starts the high-frequency sound and light alarm, pushes SMS messages to the mobile phones of maintenance personnel, and displays the local trend curve.

[0044] (4) When K≥K3, automatic pressure relief is triggered. The pressure relief execution unit starts the main and standby pressure relief valves according to the graded pressure relief logic, and at the same time, it provides real-time feedback on the pressure relief status until the coupling characteristic value falls back below K2, completes the pressure relief and sends a reset signal.

[0045] S7. Data Recording and Traceability:

[0046] The system records the collected data of each parameter, the update record of the baseline value, the adjustment record of the weight coefficient, the calculation result of the coupled feature value, and the execution record of the early warning or pressure relief in real time. The data is kept for no less than one year to facilitate subsequent fault tracing and process optimization.

[0047] As an improvement to the above technical solution, in step S2, the data preprocessing adopts the Kalman filter algorithm with a filter coefficient of 0.8~0.95 to remove random interference. The outlier removal adopts the 3σ criterion, and data exceeding the mean ± 3 times the standard deviation are judged as outliers to ensure the accuracy of the data transmitted to the data processing unit.

[0048] In step S4, the adaptive adjustment of the weight coefficients adopts the BP neural network algorithm. Historical fault data and stable operating condition data are used as training samples to construct an operating condition and weight mapping model. The model prediction error is ≤3%, achieving accurate adaptation of the weight coefficients.

[0049] In the staged pressure relief logic of step S6, the pressure relief rate corresponding to the primary pressure relief opening of 30% is 0.01~0.03MPa / s, and the pressure relief rate corresponding to the full pressure relief opening of 100% is 0.05~0.08MPa / s. If the coupling characteristic value drops rapidly below K1 during the pressure relief process, the pressure relief valve group can be closed in advance to avoid excessive pressure relief affecting the normal progress of the reaction.

[0050] As an improvement to the above technical solution, an emergency manual intervention step is also included: when the system experiences an extreme failure, such as the failure of the data processing unit, maintenance personnel can forcibly start the early warning unit and the pressure relief execution unit through the local manual control terminal or the remote emergency platform to ensure the safe operation of the reactor; after the emergency intervention, the system automatically records the intervention time, intervention action and operating data.

[0051] Compared with the prior art, the beneficial effects of the present invention are:

[0052] The temperature acquisition unit employs three high-temperature resistant sensors distributed across the upper, middle, and lower regions of the reactor. Combined with a 1-10Hz acquisition frequency and ±0.1℃ acquisition accuracy, it achieves comprehensive coverage and precise capture of the internal temperature field of the reactor, avoiding the partial errors in temperature distribution caused by a single acquisition point. The pressure acquisition unit uses two symmetrically arranged high-precision pressure transmitters to synchronously acquire static pressure P1 and dynamic pressure P2. With a high accuracy of ±0.001MPa and an acquisition frequency matched to the temperature acquisition unit, it effectively eliminates pressure fluctuation interference and ensures the time synchronization and data reliability of temperature and pressure parameters. The operating condition monitoring auxiliary unit supplements the acquisition with auxiliary parameters such as feed flow rate Q, reaction medium viscosity μ, and stirring speed n, providing multi-dimensional data support for subsequent parameter calibration and operating condition adaptation. This solves the problem of one-sided early warning judgment caused by existing technologies relying solely on single temperature and pressure parameters and insufficient data dimensions.

[0053] The data processing unit's built-in coupled calculation module uses a temperature-pressure coupling formula to quantify and fuse the average temperature of the zones, the average static and dynamic pressure, and auxiliary operating parameters, combining them with... The weight constraints and δ auxiliary operating condition correction coefficients enable deep collaboration between core and auxiliary parameters, transforming discrete multi-parameters into a unified coupled feature value K, effectively avoiding the risk of false alarms and missed alarms caused by single parameter threshold warnings. The benchmark self-learning module is based on the reactor's continuous 72-hour stable operation condition, with temperature fluctuation ≤ ±2℃, pressure fluctuation ≤ ±0.05MPa, and flow fluctuation ≤ ±5%. It dynamically updates benchmark values ​​such as T0, P0, Q0, μ0, and n0 through least squares fitting, combined with abnormal data removal and a 24-hour dynamic correction mechanism, to ensure the consistency between benchmark values ​​and actual operating conditions, solving the technical pain point of poor adaptability of fixed benchmark values. The operating condition adaptation module adaptively adjusts the weight coefficients of α, β, δ, and k1, k2, and k3 according to different reactor process types such as exothermic, endothermic, and pressure-dominated types, achieving accurate matching between operating conditions and parameter weights, and improving the system's adaptability to different process scenarios.

[0054] The early warning unit, through the collaborative design of an audible and visual early warning module (differentiated low-frequency / high-frequency prompts), a remote communication module (monitoring terminal push + mobile SMS push), and a local display module (parameter labeling + trend curve display), achieves differentiated responses for first-level and second-level early warnings. This ensures that maintenance personnel can quickly identify the urgency of the warning and provides evidence of changes in operating conditions through trend curves, improving the effectiveness and timeliness of early warning information. The pressure relief execution unit adopts a graded pressure relief valve group composed of a main pressure relief valve and a backup pressure relief valve. It performs pressure relief according to the graded logic of 30% opening for primary pressure relief and 100% opening + backup valve coordinated pressure relief. With the pressure feedback closed-loop control of the pressure relief port, the pressure relief rate is precisely controlled within 0.01~0.08MPa / s, effectively avoiding the impact damage to the reactor structure caused by the sudden pressure drop during the pressure relief process. At the same time, the backup valve design improves the redundancy reliability of the pressure relief system and solves the risk of structural impact or pressure relief failure caused by the single pressure relief mode in the existing technology.

[0055] Through a closed-loop design encompassing data acquisition, processing, judgment, and response, combined with a fault self-diagnosis module for real-time monitoring of the operational status of each unit and a backup unit switching mechanism, the system ensures continued operation even in the event of a local unit failure, thereby enhancing system stability and fault tolerance. The coupling formula incorporates dual correction terms for temperature and pressure change rates, compensating for eigenvalue lag errors under sudden temperature and pressure changes, further improving the timeliness of early warnings. Full-process data recording provides data support for fault tracing and process optimization, balancing the needs of safety early warning and production optimization. Attached Figure Description

[0056] Figure 1 This is a schematic diagram of the framework of the early warning method of the present invention. Detailed Implementation

[0057] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0058] Example:

[0059] like Figure 1 As shown, this embodiment proposes a reactor combined early warning system, including a temperature acquisition unit, a pressure acquisition unit, a data processing unit, an early warning unit, a pressure relief execution unit, and an operating condition monitoring auxiliary unit;

[0060] The temperature acquisition unit includes at least three distributed high-temperature pressure sensors, which are embedded in the upper, middle and lower regions inside the reactor, respectively, to acquire the real-time temperatures T1, T2 and T3 of each region. The acquired temperature data is filtered and denoised before being transmitted to the data processing unit. The acquisition frequency is 1~10Hz and the temperature acquisition accuracy is ±0.1℃.

[0061] The pressure acquisition unit includes two high-precision pressure transmitters symmetrically arranged on the top of the reactor, which are used to acquire the static pressure P1 and dynamic pressure P2 at the top of the reactor in real time. After eliminating pressure fluctuation interference, the data is transmitted to the data processing unit. The pressure acquisition accuracy is ±0.001MPa, and the acquisition frequency is matched with the temperature acquisition unit.

[0062] The operating condition monitoring auxiliary unit is used to collect auxiliary operating condition parameters such as reactor feed flow rate Q, reaction medium viscosity μ, and stirring speed n, providing a basis for parameter calibration of the data processing unit;

[0063] The data processing unit incorporates a coupling calculation module, a baseline self-learning module, a working condition adaptation module, and a logic judgment module. The coupling calculation module, based on input data from the temperature acquisition unit, pressure acquisition unit, and auxiliary unit, calculates the coupling characteristic value K according to a preset temperature-pressure coupling formula. The coupling formula is as follows:

[0064] ;

[0065] In the formula: α is the temperature weighting coefficient, and β is the pressure weighting coefficient. δ is the auxiliary working condition correction coefficient, with a value range of 0.05~0.15; T0 is the preset safe temperature reference value, and P0 is the preset safe pressure reference value; f(Q,μ,n) is the auxiliary working condition coupling function, with the expression being, and k1, k2, and k3 are the auxiliary parameter weighting coefficients. Q0, μ0, and n are the reference values ​​of feed flow rate, medium viscosity, and stirring speed under rated operating conditions, respectively.

[0066] The baseline self-learning module is used to dynamically update T0, P0, Q0, μ0, and n0 based on the average temperature, average pressure, and average auxiliary parameters under 72 hours of continuous stable operation of the reactor, using the least squares method for fitting. The judgment criteria are: temperature fluctuation ≤ ±2℃, pressure fluctuation ≤ ±0.05MPa, and flow fluctuation ≤ ±5%.

[0067] The operating condition adaptation module is used to adaptively adjust the values ​​of α, β, δ and k1, k2, k3 according to the reactor process type and real-time auxiliary operating condition parameters. The reactor process types include exothermic, endothermic, and pressure-dominated types.

[0068] The logic judgment module pre-stores a first-level early warning threshold K1, a second-level early warning threshold K2, and a pressure relief trigger threshold K3, where K1 < K2 < K3. The threshold settings are based on the reactor material tolerance limit, the process safety window, and historical fault data calibration.

[0069] The early warning unit includes an audible and visual early warning module, a remote communication module, and a local display module. When K1≤K<K2, the audible and visual early warning module is driven to issue a low-frequency audible and visual alert, the remote communication module pushes a first-level early warning information to the monitoring terminal, and the local display module marks the parameters exceeding the standard in real time. When K2≤K<K3, the audible and visual early warning module is driven to issue a high-frequency audible and visual alarm, the remote communication module simultaneously pushes an emergency early warning text message to the mobile phone of the operation and maintenance personnel, and the local display module locks the parameters exceeding the standard and displays the trend curve.

[0070] The pressure relief execution unit is an electrically operated staged pressure relief valve assembly, including a main pressure relief valve and a backup pressure relief valve. When K≥K3, the logic judgment module first drives the main pressure relief valve to open to 30% to perform primary pressure relief, while simultaneously monitoring the change in coupling characteristic value in real time. If there is a delay... If K remains ≥ K3, the main pressure relief valve will open to 100% and the backup pressure relief valve will be activated to assist in pressure relief until K drops below K2. Then, the pressure relief valve group will automatically close and a pressure relief completion signal will be issued.

[0071] In this embodiment, the temperature acquisition unit employs three high-temperature resistant sensors distributed across the upper, middle, and lower regions of the reactor. Combined with a 1-10Hz acquisition frequency and ±0.1℃ acquisition accuracy, this achieves comprehensive coverage and precise capture of the internal temperature field of the reactor, avoiding the partial errors in temperature distribution caused by a single acquisition point. The pressure acquisition unit uses two symmetrically arranged high-precision pressure transmitters to synchronously acquire static pressure P1 and dynamic pressure P2. Combined with a high accuracy of ±0.001MPa and an acquisition frequency matched to the temperature acquisition unit, this effectively eliminates pressure fluctuation interference, ensuring the time synchronization and data reliability of temperature and pressure parameters. The operating condition monitoring auxiliary unit supplements the acquisition with auxiliary parameters such as feed flow rate Q, reaction medium viscosity μ, and stirring speed n, providing multi-dimensional data support for subsequent parameter calibration and operating condition adaptation. This solves the problem of one-sided early warning judgments caused by existing technologies relying solely on single temperature and pressure parameters and insufficient data dimensions.

[0072] The data processing unit's built-in coupled calculation module uses a temperature-pressure coupling formula to quantify and fuse the average temperature of the zones, the average static and dynamic pressure, and auxiliary operating parameters, combining them with... The weight constraints and δ auxiliary operating condition correction coefficients enable deep collaboration between core and auxiliary parameters, transforming discrete multi-parameters into a unified coupled feature value K, effectively avoiding the risk of false alarms and missed alarms caused by single parameter threshold warnings. The benchmark self-learning module is based on the reactor's continuous 72-hour stable operation condition, with temperature fluctuation ≤ ±2℃, pressure fluctuation ≤ ±0.05MPa, and flow fluctuation ≤ ±5%. It dynamically updates benchmark values ​​such as T0, P0, Q0, μ0, and n0 through least squares fitting, combined with abnormal data removal and a 24-hour dynamic correction mechanism, to ensure the consistency between benchmark values ​​and actual operating conditions, solving the technical pain point of poor adaptability of fixed benchmark values. The operating condition adaptation module adaptively adjusts the weight coefficients of α, β, δ, and k1, k2, and k3 according to different reactor process types such as exothermic, endothermic, and pressure-dominated types, achieving accurate matching between operating conditions and parameter weights, and improving the system's adaptability to different process scenarios.

[0073] The early warning unit, through the collaborative design of an audible and visual early warning module (differentiated low-frequency / high-frequency prompts), a remote communication module (monitoring terminal push + mobile SMS push), and a local display module (parameter labeling + trend curve display), achieves differentiated responses for first-level and second-level early warnings. This ensures that maintenance personnel can quickly identify the urgency of the warning and provides evidence of changes in operating conditions through trend curves, improving the effectiveness and timeliness of early warning information. The pressure relief execution unit adopts a graded pressure relief valve group composed of a main pressure relief valve and a backup pressure relief valve. It performs pressure relief according to the graded logic of 30% opening for primary pressure relief and 100% opening + backup valve coordinated pressure relief. With the pressure feedback closed-loop control of the pressure relief port, the pressure relief rate is precisely controlled within 0.01~0.08MPa / s, effectively avoiding the impact damage to the reactor structure caused by the sudden pressure drop during the pressure relief process. At the same time, the backup valve design improves the redundancy reliability of the pressure relief system and solves the risk of structural impact or pressure relief failure caused by the single pressure relief mode in the existing technology.

[0074] Through a closed-loop design encompassing data acquisition, processing, judgment, and response, combined with a fault self-diagnosis module for real-time monitoring of the operational status of each unit and a backup unit switching mechanism, the system ensures continued operation even in the event of a local unit failure, thereby enhancing system stability and fault tolerance. The coupling formula incorporates dual correction terms for temperature and pressure change rates, compensating for eigenvalue lag errors under sudden temperature and pressure changes, further improving the timeliness of early warnings. Full-process data recording provides data support for fault tracing and process optimization, balancing the needs of safety early warning and production optimization.

[0075] Specifically, the temperature weighting coefficient α is set to 0.3~0.7, and the pressure weighting coefficient β is set to 0.3~0.7. For exothermic reactors, α is set to 0.6~0.7 and β is set to 0.3~0.4, and they preferentially respond to temperature anomalies.

[0076] For pressure-dominated reactors, α = 0.3~0.4 and β = 0.6~0.7, the reactor preferentially responds to pressure anomalies.

[0077] In the endothermic reactor, both α and β are set to 0.45~0.55 to achieve a temperature and pressure equilibrium response.

[0078] In this embodiment, the range of values ​​for α and β provides flexible adjustment space for reactors with different process characteristics. Combined with the adaptive adjustment function of the operating condition adaptation module, the same early warning system can be adapted to various types of reactors, including exothermic, endothermic, and pressure-dominated reactors. This eliminates the need for separate early warning logic design for specific reactors, reducing equipment selection and system deployment costs. Simultaneously, the differentiated weight design ensures priority response to core process risks while not neglecting the monitoring value of secondary parameters. This achieves an early warning logic that prioritizes core risks while also considering secondary risks, balancing the targetedness and comprehensiveness of the early warning system. This further expands the system's engineering application scenarios and practicality.

[0079] Specifically, the benchmark self-learning module also includes an abnormal data removal function. When the collected temperature, pressure or auxiliary parameters exceed the rated operating condition range of ±20%, they are judged as abnormal data and automatically removed, and will not participate in the benchmark fitting calculation. At the same time, the benchmark values ​​such as T0 and P0 are dynamically corrected every 24 hours based on the stable operating condition data of the day. The correction range does not exceed ±5% of the initial benchmark value, ensuring the stability and adaptability of the benchmark values.

[0080] In this embodiment, the accuracy of the baseline value fitting is improved by using the abnormal data removal function built into the baseline value self-learning module. Temperature, pressure, and auxiliary parameters that exceed the rated operating condition range of ±20% are identified as abnormal data and automatically removed. This effectively eliminates the interference of invalid data caused by equipment failure, instantaneous interference, and extreme operating condition changes on the baseline value fitting, ensuring that the data involved in the baseline value fitting calculation of T0, P0, Q0, μ0, and n0 are all valid data that reflect the true stable operating state of the reactor. This solves the technical pain point of the prior art, which does not perform targeted processing on abnormal data, resulting in distorted baseline value fitting and inability to match actual operating conditions. It significantly improves the calculation accuracy and reliability of the baseline value, providing a solid data foundation for the subsequent accurate calculation of the coupled feature value K.

[0081] Specifically, the pressure relief execution unit is also equipped with a pressure feedback closed-loop control module, which collects the pressure value P_relief at the pressure relief port in real time. When P_relief exceeds the preset safe pressure relief pressure, the opening of the pressure relief valve is automatically adjusted to control P_relief within a safe range, so as to avoid the sudden pressure drop during the pressure relief process from impacting the reactor structure.

[0082] The preset safe pressure relief pressure is 1.15 times the rated pressure of the reactor.

[0083] In this embodiment, by adding a pressure feedback closed-loop control module to the pressure relief execution unit, a closed-loop control logic of real-time acquisition, dynamic judgment, and opening adjustment is constructed to achieve precise control of the pressure relief process. The module acquires the pressure value P_relief at the pressure relief port in real time, and uses a preset safe pressure relief pressure of 1.2 times the rated pressure of the reactor as the control threshold. When P_relief exceeds this threshold, the opening of the pressure relief valve is automatically adjusted to strictly constrain the pressure relief pressure within a safe range. This solves the technical pain points of pressure runaway and inability to accurately control the pressure relief intensity in the open-loop pressure relief mode of the prior art, ensuring that the pressure relief process is always under control and improving the reliability and accuracy of the pressure relief operation.

[0084] Specifically, the coupling formula adds double correction terms for the rate of change of temperature and the rate of change of pressure. The formula for calculating the coupling characteristic value K' after correction is as follows:

[0085] ;

[0086] In the formula: γ is the temperature change rate correction coefficient, with a value of 0.02~0.08; ε is the pressure change rate correction coefficient, with a value of 0.02~0.08; ΔT / Δt is the temperature change per unit time, calculated using a sliding window of 1~3s; ΔP / Δt is the pressure change per unit time, with a calculation period consistent with the temperature change rate; the dual change rate correction terms compensate for the characteristic value lag error under sudden temperature and pressure changes, thereby improving the timeliness of early warning.

[0087] In this embodiment, by adding double correction terms for the temperature change rate ΔT / Δt and the pressure change rate ΔP / Δt to the coupling formula, a dual calculation logic of steady-state parameter coupling and dynamic change rate compensation is constructed. This effectively solves the technical pain point of existing technologies that cannot respond to instantaneous temperature and pressure changes in a timely manner when calculating coupled characteristic values ​​based solely on steady-state temperature and pressure parameters, resulting in delayed characteristic value updates.

[0088] The dual correction term can directly quantify the instantaneous change trend of temperature and pressure parameters and incorporate this trend into the calculation of the coupled eigenvalue K', so that the eigenvalue can be dynamically adjusted in sync with the rhythm of temperature and pressure changes. This fundamentally compensates for the lag error caused by the steady-state parameter calculation and ensures that the coupled eigenvalue keeps pace with the capture of abnormal operating conditions and the actual risk evolution.

[0089] Specifically, the data processing unit also has a built-in fault self-diagnosis module, which can monitor the operating status of each acquisition unit, early warning unit and pressure relief execution unit in real time. When a unit experiences signal interruption, data abnormality or execution failure, it immediately issues a device fault alarm and switches to the backup unit to ensure continuous system operation. At the same time, it records fault information for easy maintenance and troubleshooting.

[0090] In this embodiment, the built-in fault self-diagnosis module of the data processing unit enables real-time monitoring of the operating status of core components such as the temperature acquisition unit, pressure acquisition unit, early warning unit, and pressure relief execution unit. It accurately captures various fault scenarios, including signal interruption, data anomalies, and actuator jamming, overcoming the technical pain points of existing technologies that lack proactive fault monitoring mechanisms and suffer from delayed fault detection. The module immediately triggers a device fault alarm upon the occurrence of a fault, simultaneously pushing fault information through the early warning unit's audible and visual signals and remote communication channels. This allows maintenance personnel to quickly locate the fault type and its affected area, preventing secondary safety risks such as undetected faults leading to failed early warnings and untimely pressure relief, thus achieving proactive fault risk control.

[0091] A reactor combination early warning method includes the following steps:

[0092] S1. System Initialization:

[0093] Set the initial values ​​of each benchmark (T0, P0, Q0, μ0, n0), the initial values ​​of the weighting coefficients (α, β, δ, k1, k2, k3), and the warning thresholds (K1, K2, K3) for each level. Start each acquisition unit, data processing unit, warning unit, and pressure relief execution unit to complete the equipment self-test.

[0094] S2. Real-time acquisition and preprocessing of multiple parameters:

[0095] The temperature acquisition unit collects the real-time temperatures T1, T2, and T3 in the upper, middle, and lower regions of the reactor; the pressure acquisition unit collects the static pressure P_static and the dynamic pressure P_dynamic at the top; and the operating condition monitoring auxiliary unit collects the feed flow rate Q, the viscosity of the reaction medium μ, and the stirring speed n. Each acquisition unit performs preprocessing on the raw data, including filtering and noise reduction and outlier removal, and transmits the effective data to the data processing unit.

[0096] S3. Dynamic Update of Baseline Values:

[0097] The data processing unit uses the baseline self-learning module to determine whether the current operating condition is a stable operating condition. If the continuous operation meets the stable operating condition judgment criteria, the baseline values ​​T0, P0, Q0, μ0, and n0 are updated based on the collected valid data. If it is an unstable operating condition, the current baseline values ​​are used.

[0098] S4. Adaptive adjustment of weighting coefficients:

[0099] The operating condition adaptation module adaptively adjusts the values ​​of α, β, δ and k1, k2, k3 according to the reactor process type and real-time auxiliary operating condition parameters, and outputs the weight coefficients that adapt to the current operating condition.

[0100] S5. Calculation of Coupled Eigenvalues:

[0101] The coupling calculation module calculates the coupling characteristic value K according to the coupling formula based on the preprocessed effective data, the dynamically updated benchmark value, and the adaptively adjusted weight coefficient. If there is a risk of sudden temperature and pressure changes, the correction formula is used to calculate K', and K' is used as the judgment basis.

[0102] S6. Multi-level response logic judgment and execution:

[0103] The logic judgment module will couple the feature value, K or K', with the warning thresholds at each level and execute the corresponding response actions:

[0104] (1) When K < K1, it is determined to be a normal working condition, the early warning unit does not act, and the system continues to collect data and monitor the working condition;

[0105] (2) When K1≤K<K2, a first-level warning is triggered, and the warning unit starts the low-frequency sound and light prompt, remote monitoring terminal warning push and local parameter labeling functions;

[0106] (3) When K2≤K<K3, a level 2 warning is triggered, and the warning unit starts the high-frequency sound and light alarm, pushes SMS messages to the mobile phones of maintenance personnel, and displays the local trend curve.

[0107] (4) When K≥K3, automatic pressure relief is triggered. The pressure relief execution unit starts the main and standby pressure relief valves according to the graded pressure relief logic, and at the same time, it provides real-time feedback on the pressure relief status until the coupling characteristic value falls back below K2, completes the pressure relief and sends a reset signal.

[0108] S7. Data Recording and Traceability:

[0109] The system records the collected data of each parameter, the update record of the baseline value, the adjustment record of the weight coefficient, the calculation result of the coupled feature value, and the execution record of the early warning or pressure relief in real time. The data is kept for no less than one year to facilitate subsequent fault tracing and process optimization.

[0110] In this embodiment, a closed-loop design encompassing the entire process—S1 system initialization, S2 multi-parameter acquisition and preprocessing, S3 dynamic updating of benchmark values, S4 adaptive adjustment of weight coefficients, S5 coupled feature value calculation, S6 multi-level response execution, and S7 data recording and traceability—achieves synergistic gains in multi-dimensional technical effects.

[0111] During the system initialization phase, the reliability of operation and the rationality of initial parameters are ensured by clearly defining initial parameter settings and device self-tests.

[0112] The multi-parameter acquisition and preprocessing stage employs techniques such as Kalman filtering and the 3σ criterion to effectively eliminate random interference and abnormal data, ensuring the accuracy and validity of the input data and providing solid data support for subsequent calculations.

[0113] The benchmark value is dynamically updated based on the stable operating condition judgment criteria and the least squares method fitting, so that the benchmark value can adapt to the slow changes in the reactor operating conditions in real time, avoiding the early warning distortion caused by the disconnect between the fixed benchmark value and the actual operating conditions.

[0114] The adaptive adjustment of weight coefficients constructs a working condition-weight mapping model through a BP neural network algorithm, which accurately adapts to different process types of reactors such as exothermic, endothermic, and pressure-dominated reactors, thereby improving the pertinence of early warning and the adaptability of working conditions.

[0115] The coupled eigenvalue calculation combines the basic coupling formula with the temperature and pressure change correction formula, which not only achieves deep collaborative quantification of multiple parameters, but also compensates for the eigenvalue lag error in the case of instantaneous temperature and pressure change, significantly improving the accuracy and timeliness of early warning judgment.

[0116] The multi-level response execution logic, through graded early warning (differentiated sound and light, communication, and display functions) and graded pressure relief (main and backup valve coordination, controllable rate), ensures rapid identification and response to different risk levels while avoiding the impact of sudden pressure drops on the reactor structure and the influence of excessive pressure relief on the process. The data recording and traceability function provides reliable data support for fault tracing and process optimization by retaining full-process operation data (with a retention period of no less than 1 year). At the same time, the emergency manual intervention steps further enhance the safety redundancy under extreme failure scenarios.

[0117] This method comprehensively addresses the technical pain points of existing early warning methods, such as single parameters, rigid benchmarks, fixed weights, coarse responses, and lack of data traceability. It significantly improves the accuracy, adaptability to operating conditions, operational safety, and engineering practicality of the early warning system, achieving full-chain safety assurance with accurate data, adapted parameters, scientific judgment, efficient response, and convenient traceability, and providing comprehensive and reliable methodological support for the stable operation of reactors.

[0118] Specifically, in step S2, the data preprocessing uses the Kalman filter algorithm with a filter coefficient of 0.8~0.95 to remove random interference. Outlier removal uses the 3σ criterion, and data exceeding the mean ± 3 times the standard deviation are judged as outliers to ensure the accuracy of the data transmitted to the data processing unit.

[0119] In step S4, the adaptive adjustment of the weight coefficients adopts the BP neural network algorithm. Historical fault data and stable operating condition data are used as training samples to construct an operating condition and weight mapping model. The model prediction error is ≤3%, achieving accurate adaptation of the weight coefficients.

[0120] In the staged pressure relief logic of step S6, the pressure relief rate corresponding to the primary pressure relief opening of 30% is 0.01~0.03MPa / s, and the pressure relief rate corresponding to the full pressure relief opening of 100% is 0.05~0.08MPa / s. If the coupling characteristic value drops rapidly below K1 during the pressure relief process, the pressure relief valve group can be closed in advance to avoid excessive pressure relief affecting the normal progress of the reaction.

[0121] Specifically, it also includes emergency manual intervention steps: when the system experiences extreme failures, such as the failure of the data processing unit, maintenance personnel can forcibly activate the early warning unit and the pressure relief execution unit through the local manual control terminal or the remote emergency platform to ensure the safe operation of the reactor; after emergency intervention, the system automatically records the intervention time, intervention actions and operating data.

[0122] In this embodiment, by constructing a dual safety protection mechanism of automatic control and manual backup, the technical pain point of existing early warning systems being unable to perform early warning and pressure relief operations due to the paralysis of automatic control logic in extreme failure scenarios (such as data processing unit failure) is effectively solved: On the one hand, in response to extreme abnormal situations such as failure of the system core unit, maintenance personnel can intervene bidirectionally through the local manual control terminal or the remote emergency platform to forcibly start the early warning unit and pressure relief execution unit, ensuring that even if the automatic control link is interrupted, it can still quickly respond to safety risks such as over-temperature and over-pressure, avoiding the expansion of accidents caused by complete system failure, and providing ultimate safety backup for reactor operation; on the other hand, emergency... After intervention, the system automatically records the intervention time, intervention actions, and corresponding operating condition data. This provides complete data support for subsequent fault tracing and system optimization in extreme scenarios, while also ensuring the traceability of the operation process and meeting the compliance requirements for safe operation in industrial production. At the same time, the design of local and remote two-way intervention is adaptable to different application scenarios of on-site duty or remote monitoring by operation and maintenance personnel, improving the flexibility and convenience of intervention operations. It further strengthens the system's fault tolerance and operational reliability under complex and extreme operating conditions, enabling the safety protection of the entire early warning system to cover all scenarios from normal operating conditions to extreme faults, significantly improving the engineering practicality and safety redundancy level of the technical solution.

[0123] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A reactor combination early warning system, characterized in that: It includes a temperature acquisition unit, a pressure acquisition unit, a data processing unit, an early warning unit, a pressure relief execution unit, and an operating condition monitoring auxiliary unit; The temperature acquisition unit includes at least three distributed high-temperature pressure sensors, which are embedded in the upper, middle and lower regions inside the reactor, respectively, to acquire the real-time temperatures T1, T2 and T3 of each region. The acquired temperature data is filtered and denoised before being transmitted to the data processing unit. The acquisition frequency is 1~10Hz and the temperature acquisition accuracy is ±0.1℃. The pressure acquisition unit includes two high-precision pressure transmitters symmetrically arranged on the top of the reactor, which are used to acquire the static pressure P1 and dynamic pressure P2 at the top of the reactor in real time. After eliminating pressure fluctuation interference, the data is transmitted to the data processing unit. The pressure acquisition accuracy is ±0.001MPa, and the acquisition frequency is matched with the temperature acquisition unit. The operating condition monitoring auxiliary unit is used to collect auxiliary operating condition parameters such as reactor feed flow rate Q, reaction medium viscosity μ, and stirring speed n, providing a basis for parameter calibration of the data processing unit; The data processing unit incorporates a coupling calculation module, a baseline self-learning module, a working condition adaptation module, and a logic judgment module. The coupling calculation module, based on input data from the temperature acquisition unit, pressure acquisition unit, and auxiliary unit, calculates the coupling characteristic value K according to a preset temperature-pressure coupling formula. The coupling formula is as follows: ； In the formula: α is the temperature weighting coefficient, and β is the pressure weighting coefficient. δ is the auxiliary working condition correction coefficient, ranging from 0.05 to 0.15; T0 is the preset safe temperature reference value, and P0 is the preset safe pressure reference value; f(Q,μ,n) is the auxiliary working condition coupling function, expressed as follows: k1, k2, and k3 are auxiliary parameter weighting coefficients. Q0, μ0, and n are the reference values ​​of feed flow rate, medium viscosity, and stirring speed under rated operating conditions, respectively. The baseline self-learning module is used to dynamically update T0, P0, Q0, μ0, and n0 based on the average temperature, average pressure, and average auxiliary parameters under 72 hours of continuous stable operation of the reactor, using the least squares method for fitting. The judgment criteria are: temperature fluctuation ≤ ±2℃, pressure fluctuation ≤ ±0.05MPa, and flow fluctuation ≤ ±5%. The operating condition adaptation module is used to adaptively adjust the values ​​of α, β, δ and k1, k2, k3 according to the reactor process type and real-time auxiliary operating condition parameters. The reactor process types include exothermic, endothermic, and pressure-dominated types. The logic judgment module pre-stores a first-level early warning threshold K1, a second-level early warning threshold K2, and a pressure relief trigger threshold K3, where K1 < K2 < K3. The threshold settings are based on the reactor material tolerance limit, the process safety window, and historical fault data calibration. The early warning unit includes an audible and visual early warning module, a remote communication module, and a local display module. When K1≤K<K2, the audible and visual early warning module is driven to issue a low-frequency audible and visual alert, the remote communication module pushes a first-level early warning information to the monitoring terminal, and the local display module marks the parameters exceeding the standard in real time. When K2≤K<K3, the audible and visual early warning module is driven to issue a high-frequency audible and visual alarm, the remote communication module simultaneously pushes an emergency early warning text message to the mobile phone of the operation and maintenance personnel, and the local display module locks the parameters exceeding the standard and displays the trend curve. The pressure relief execution unit is an electrically operated staged pressure relief valve assembly, including a main pressure relief valve and a backup pressure relief valve. When K≥K3, the logic judgment module first drives the main pressure relief valve to open to 30% to perform primary pressure relief, while simultaneously monitoring the change in coupling characteristic value in real time. If there is a delay... If K remains ≥ K3, the main pressure relief valve will open to 100% and the backup pressure relief valve will be activated to assist in pressure relief until K drops below K2. Then, the pressure relief valve group will automatically close and a pressure relief completion signal will be issued.

2. The reactor combination early warning system according to claim 1, characterized in that: The temperature weighting coefficient α is set to 0.3~0.7, and the pressure weighting coefficient β is set to 0.3~0.

7. For exothermic reactors, α is set to 0.6~0.7 and β is set to 0.3~0.4, and they respond preferentially to temperature anomalies. For pressure-dominated reactors, α = 0.3~0.4 and β = 0.6~0.7, the reactor preferentially responds to pressure anomalies. In the endothermic reactor, both α and β are set to 0.45~0.55 to achieve a temperature and pressure equilibrium response.

3. The reactor combination early warning system according to claim 1, characterized in that: The benchmark self-learning module also includes an abnormal data removal function. When the collected temperature, pressure or auxiliary parameters exceed the rated operating condition range of ±20%, they are judged as abnormal data and automatically removed, and will not participate in the benchmark fitting calculation. At the same time, the benchmark values ​​such as T0 and P0 are dynamically corrected every 24 hours based on the stable operating condition data of the day. The correction range does not exceed ±5% of the initial benchmark value, ensuring the stability and adaptability of the benchmark values.

4. The reactor combination early warning system according to claim 1, characterized in that: The pressure relief execution unit is also equipped with a pressure feedback closed-loop control module, which collects the pressure value P_relief at the pressure relief port in real time. When P_relief exceeds the preset safe pressure relief pressure, it automatically adjusts the opening of the pressure relief valve to control P_relief within a safe range, so as to avoid the sudden pressure drop during the pressure relief process from impacting the reactor structure. The preset safe pressure relief pressure is 1.15 times the rated pressure of the reactor.

5. A reactor combination early warning system according to claim 1, characterized in that: The coupling formula is supplemented with double correction terms for the rate of temperature change and the rate of pressure change. The formula for calculating the coupling characteristic value K' after correction is as follows: ； In the formula: γ is the temperature change rate correction coefficient, with a value of 0.02~0.08; ε is the pressure change rate correction coefficient, with a value of 0.02~0.08; ΔT / Δt is the temperature change per unit time, calculated using a sliding window of 1~3s; ΔP / Δt is the pressure change per unit time, with the calculation period consistent with the temperature change rate. By using a dual rate-of-change correction term to compensate for the eigenvalue lag error under sudden temperature and pressure changes, the timeliness of early warnings is improved.

6. The reactor combination early warning system according to claim 1, characterized in that: The data processing unit also has a built-in fault self-diagnosis module, which can monitor the operating status of each acquisition unit, early warning unit and pressure relief execution unit in real time. When a unit experiences signal interruption, data abnormality or execution failure, it will immediately issue a device fault alarm and switch to the backup unit to ensure continuous system operation. At the same time, it will record fault information for easy maintenance and troubleshooting.

7. A reactor combination early warning method, applied to the reactor combination early warning system according to any one of claims 1-6, characterized in that: Includes the following steps: S1. System Initialization: Set the initial values ​​of each benchmark (T0, P0, Q0, μ0, n0), the initial values ​​of the weighting coefficients (α, β, δ, k1, k2, k3), and the warning thresholds (K1, K2, K3) for each level. Start each acquisition unit, data processing unit, warning unit, and pressure relief execution unit to complete the equipment self-test. S2. Real-time acquisition and preprocessing of multiple parameters: The temperature acquisition unit collects the real-time temperatures T1, T2, and T3 in the upper, middle, and lower regions of the reactor; the pressure acquisition unit collects the static pressure P_static and the dynamic pressure P_dynamic at the top; and the operating condition monitoring auxiliary unit collects the feed flow rate Q, the viscosity of the reaction medium μ, and the stirring speed n. Each acquisition unit performs preprocessing on the raw data, including filtering and noise reduction and outlier removal, and transmits the effective data to the data processing unit. S3. Dynamic Update of Baseline Values: The data processing unit uses the baseline value self-learning module to determine whether the current operating condition is a stable operating condition. If the continuous operation meets the stable operating condition judgment criteria, the baseline values ​​T0, P0, Q0, μ0, and n0 are updated based on the collected valid data. If the operating condition is unstable, the current baseline value shall be used. S4. Adaptive adjustment of weighting coefficients: The operating condition adaptation module adaptively adjusts the values ​​of α, β, δ and k1, k2, k3 according to the reactor process type and real-time auxiliary operating condition parameters, and outputs the weight coefficients that adapt to the current operating condition. S5. Calculation of Coupled Eigenvalues: The coupling calculation module calculates the coupling characteristic value K according to the coupling formula based on the preprocessed effective data, the dynamically updated benchmark value, and the adaptively adjusted weight coefficient. If there is a risk of sudden temperature and pressure changes, the correction formula is used to calculate K', and K' is used as the judgment basis. S6. Multi-level response logic judgment and execution: The logic judgment module will couple the feature value, K or K', with the warning thresholds at each level and execute the corresponding response actions: (1) When K < K1, it is determined to be a normal working condition, the early warning unit does not act, and the system continues to collect data and monitor the working condition; (2) When K1≤K<K2, a first-level warning is triggered, and the warning unit starts the low-frequency sound and light prompt, remote monitoring terminal warning push and local parameter labeling functions; (3) When K2≤K<K3, a level 2 warning is triggered, and the warning unit starts the high-frequency sound and light alarm, pushes SMS messages to the mobile phones of maintenance personnel, and displays the local trend curve. (4) When K≥K3, automatic pressure relief is triggered. The pressure relief execution unit starts the main and standby pressure relief valves according to the graded pressure relief logic, and at the same time, it provides real-time feedback on the pressure relief status until the coupling characteristic value falls back below K2, completes the pressure relief and sends a reset signal. S7. Data Recording and Traceability: The system records the collected data of each parameter, the update record of the baseline value, the adjustment record of the weight coefficient, the calculation result of the coupled feature value, and the execution record of the early warning or pressure relief in real time. The data is kept for no less than one year to facilitate subsequent fault tracing and process optimization.

8. The reactor combination early warning method according to claim 7, characterized in that: In step S2, the data preprocessing uses the Kalman filter algorithm with a filter coefficient of 0.8~0.95 to remove random interference. Outlier removal uses the 3σ criterion, and data exceeding the mean ± 3 times the standard deviation are judged as outliers to ensure the accuracy of the data transmitted to the data processing unit. In step S4, the adaptive adjustment of the weight coefficients adopts the BP neural network algorithm. Historical fault data and stable operating condition data are used as training samples to construct an operating condition and weight mapping model. The model prediction error is ≤3%, achieving accurate adaptation of the weight coefficients. In the staged pressure relief logic of step S6, the pressure relief rate corresponding to the primary pressure relief opening of 30% is 0.01~0.03MPa / s, and the pressure relief rate corresponding to the full pressure relief opening of 100% is 0.05~0.08MPa / s. If the coupling characteristic value drops rapidly below K1 during the pressure relief process, the pressure relief valve group can be closed in advance to avoid excessive pressure relief affecting the normal progress of the reaction.

9. A reactor combination early warning method according to claim 7, characterized in that: It also includes emergency manual intervention steps: when the system experiences extreme failures, such as the failure of the data processing unit, maintenance personnel can forcibly activate the early warning unit and the pressure relief execution unit through the local manual control terminal or the remote emergency platform to ensure the safe operation of the reactor; after emergency intervention, the system automatically records the intervention time, intervention actions and operating data.

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