A risk warning method for chemical equipment

Abstract

This invention provides a risk warning method for chemical equipment, relating to the field of chemical equipment safety management technology. Based on equipment information, environmental information, and management information corresponding to a first chemical equipment, an equipment score, an environmental score, and a management score are determined, respectively. Based on the equipment score, environmental score, and management score, as well as their respective weights, a health score for the first chemical equipment is determined. Based on the health score, the risk level of the first chemical equipment is determined. Based on the risk level, a warning message characterizing the risk level of the first chemical equipment is displayed. This invention improves the accuracy of risk warnings for chemical equipment through multi-source heterogeneous data fusion, dynamic weight modeling, and a self-evolutionary mechanism.

Description

Technical Field

[0001] This application relates to the field of intelligent industrial safety management and control technology, and in particular to a risk warning method for chemical equipment. Background Technology

[0002] Risk warning for chemical equipment is a core element in ensuring safe industrial production.

[0003] Mainstream risk warning methods for chemical equipment are primarily based on fixed rules from a single sensor. This type of technology collects operating parameters of chemical equipment (such as temperature and pressure), sets fixed thresholds for exceeding limits, and triggers alarms. Its core logic relies on threshold comparison using single-dimensional data to make a preliminary judgment on abnormal conditions of chemical equipment, providing basic safety warning functions for chemical production.

[0004] However, since the early warning logic of the above technologies is based only on single-dimensional operating data or static parameters of chemical equipment, it lacks the ability to analyze the correlation of multiple factors in complex industrial scenarios. Furthermore, the fixed rules cannot dynamically adapt to dynamic conditions such as changes in equipment operating conditions and environmental interference. This results in insufficient ability to identify potential risks of chemical equipment, difficulty in accurately distinguishing between normal fluctuations and real faults, and ultimately leads to the problem of low early warning accuracy. It cannot meet the reliability and accuracy requirements of risk management for chemical equipment. Summary of the Invention

[0005] This application provides a risk warning method for chemical equipment. By using multi-source heterogeneous data fusion, dynamic weight modeling, and a self-evolution mechanism, the accuracy of risk warning for chemical equipment can be improved.

[0006] To achieve the above objectives, the embodiments of this application adopt the following technical solutions:

[0007] In a first aspect, the present invention provides a risk warning method for chemical equipment, the method comprising:

[0008] Determine the equipment score, environmental score, and management score for the first chemical equipment. The equipment score is determined based on the equipment information corresponding to the first chemical equipment. The environmental score is determined based on the environmental information corresponding to the first chemical equipment. The management score is determined based on the management information corresponding to the first chemical equipment. Equipment information includes equipment attribute data, operating status data, and historical fault data for the first chemical equipment. Environmental information includes environmental data of the environment in which the first chemical equipment is located, and the correlation data between the first and second chemical equipment. The second chemical equipment is connected to the first chemical equipment. Management information includes personnel data for the target operators, as well as historical maintenance data, spare parts inventory data, equipment change records, historical hazard rectification data, and historical inspection data for the first chemical equipment. The target operators are the personnel operating the first chemical equipment.

[0009] The health score of the first chemical equipment is determined based on its equipment score, environmental score, and management score, as well as the weights of these scores. The weights for the equipment score, environmental score, and management score are all determined based on these scores.

[0010] Based on the health score of the first chemical equipment, the risk level of the first chemical equipment is determined.

[0011] Based on the risk level of the first chemical equipment, early warning information is provided to characterize the risk level of the first chemical equipment.

[0012] Based on the above technical solution, the present invention can be further improved as follows.

[0013] Furthermore, the equipment attribute data includes equipment type data, equipment material data, equipment structure data, equipment usage date data, and equipment validity period data for the first chemical equipment. Operating status data includes the pressure, temperature, and vibration spectrum of the first chemical equipment during operation, as well as the safety limits of the monitoring equipment. The monitoring equipment is used to monitor the pressure, temperature, and vibration spectrum of the first chemical equipment during operation. Historical fault data includes the fault time, fault type, and fault hazard level of the first chemical equipment.

[0014] Furthermore, the environmental data includes the temperature, humidity, and corrosive gas concentration of the environment in which the first chemical equipment is located. The correlation data between the first and second chemical equipment includes the process correlation between them and the physical distance between them. The process correlation between the first and second chemical equipment is determined based on the total number of interfaces and the number of connected interfaces between them.

[0015] Furthermore, personnel data includes the qualification level of the target operators, training completion rate, and operational success rate within the target time period. Historical maintenance data includes the maintenance types and on-time maintenance rates for the first chemical equipment within the target time period. Spare parts inventory data includes the quantity of spare parts in stock for the first chemical equipment. Equipment change records include change data for the first chemical equipment within the target time period. This change data includes location relocation data, equipment parameter change data, and parts replacement data for the first chemical equipment. Historical hazard rectification data includes the number of hazards, hazard levels, and on-time rectification rate for the first chemical equipment within the target time period. Historical inspection data includes the actual number of inspections, expected number of inspections, number of handled anomalies, and total number of discovered anomalies for the first chemical equipment within the target time period.

[0016] Furthermore, based on the equipment attribute data and historical fault data corresponding to the first chemical equipment, the basic health status of the first chemical equipment is determined. Based on the operating status data corresponding to the first chemical equipment, the dynamic anomaly coefficients of the first chemical equipment are determined. The dynamic anomaly coefficients include the pressure anomaly coefficient, the temperature anomaly coefficient, and the vibration spectrum anomaly coefficient. Based on the basic health status, dynamic anomaly coefficients, and dynamic anomaly weights of the first chemical equipment, the equipment score corresponding to the first chemical equipment is determined. The dynamic anomaly weights include the pressure anomaly weight corresponding to the pressure anomaly coefficient, the temperature anomaly weight corresponding to the temperature anomaly coefficient, and the vibration spectrum anomaly weight corresponding to the vibration spectrum anomaly coefficient.

[0017] Furthermore, the safety limits of the monitoring equipment include upper and lower limits. When the alignment value corresponding to the operating parameter of the first chemical equipment is greater than or equal to the lower limit and less than or equal to the upper limit, the dynamic anomaly coefficient corresponding to the operating parameter of the first chemical equipment is determined to be 0. The operating parameter of the first chemical equipment is any one of pressure, temperature, or vibration spectrum during operation. When the operating parameter of the first chemical equipment is pressure, the dynamic anomaly coefficient corresponding to the operating parameter is the pressure anomaly coefficient. When the operating parameter of the first chemical equipment is temperature, the dynamic anomaly coefficient corresponding to the operating parameter is the temperature anomaly coefficient. When the operating parameter of the first chemical equipment is a vibration spectrum, the dynamic anomaly coefficient corresponding to the operating parameter is the vibration spectrum anomaly coefficient.

[0018] If the alignment value corresponding to the operating parameters of the first chemical equipment is greater than the upper limit value, the value of the dynamic anomaly coefficient corresponding to the operating parameters of the first chemical equipment is determined based on the alignment value, the upper limit value, and the preset threshold upper limit of the operating parameters of the first chemical equipment.

[0019] When the alignment value corresponding to the operating parameter of the first chemical equipment is less than the lower limit value, the value of the dynamic anomaly coefficient corresponding to the operating parameter of the first chemical equipment is determined based on the alignment value, the lower limit value and the preset threshold lower limit of the operating parameter of the first chemical equipment.

[0020] Furthermore, based on the environmental data corresponding to the first chemical equipment, the environmental risk value of the environment in which the first chemical equipment is located is determined. Based on the correlation data between the first and second chemical equipment and the health score of the second chemical equipment, the risk transmission value of the second chemical equipment is determined. The health score of the second chemical equipment is determined based on the equipment score, environmental score, and management score corresponding to the second chemical equipment, as well as the weights of the equipment score, environmental score, and management score. Based on the environmental risk value of the environment in which the first chemical equipment is located and the risk transmission value of the second chemical equipment, the environmental score corresponding to the first chemical equipment is determined.

[0021] Furthermore, based on the qualification level of the target operators, the training completion rate and operation success rate within the target time period, the personnel capability score corresponding to the first chemical equipment is determined. Based on the maintenance type and on-time maintenance rate for the first chemical equipment within the target time period, as well as the spare parts inventory adequacy rate and equipment change records, the maintenance change score corresponding to the first chemical equipment is determined. The spare parts inventory adequacy rate for the first chemical equipment is determined based on the quantity of spare parts in the corresponding inventory. Based on the number of hidden dangers, the level of hidden dangers, and the on-time rectification rate of hidden dangers for the first chemical equipment within the target time period, the hidden danger rectification score corresponding to the first chemical equipment is determined. Based on the inspection attendance rate and anomaly handling rate for the first chemical equipment within the target time period, the inspection score corresponding to the first chemical equipment is determined. The inspection attendance rate is determined based on the actual number of inspections and the expected number of inspections for the first chemical equipment within the target time period. The anomaly handling rate is determined based on the number of anomalies handled and the total number of anomalies discovered for the first chemical equipment within the target time period. Based on the personnel competence score, maintenance and change score, hidden danger rectification score, and inspection score corresponding to the first chemical equipment, as well as the personnel competence management weight corresponding to the personnel competence score, the maintenance and change management weight corresponding to the maintenance and change score, the hidden danger rectification management weight corresponding to the hidden danger rectification score, and the inspection management weight corresponding to the inspection score, the management score corresponding to the first chemical equipment is determined.

[0022] Furthermore, based on the first preset relationship, the equipment scoring weight is determined. The first preset relationship includes α=(1-H_phy) / D. Based on the second preset relationship, the environmental scoring weight is determined. The second preset relationship includes β=(1-H_env) / D. Based on the third preset relationship, the management scoring weight is determined. The third preset relationship includes γ=(1-H_mgmt) / D. Where, D=max ((3-(H_phy+H_env+H_mgmt)),0.1). α represents the equipment scoring weight, β represents the environmental scoring weight, and γ represents the management scoring weight. H_phy represents the equipment score, H_env represents the environmental score, and H_mgmt represents the management score.

[0023] Furthermore, based on the risk level of the first chemical equipment, decisions corresponding to the risk level of the first chemical equipment are executed.

[0024] The beneficial effects of this invention are:

[0025] This invention constructs a risk warning model through three core dimensions: equipment scoring, environmental scoring, and management scoring, overcoming the limitations of traditional single-dimensional assessments. The multi-dimensional data fusion of this invention makes risk assessment more closely reflect the actual operating scenarios of chemical equipment, avoiding misjudgments caused by overlooking a single factor, and comprehensively covering potential risks related to the equipment itself, the external environment, and management processes.

[0026] This invention achieves dynamic risk tracking through dynamic anomaly coefficient calculation and real-time data acquisition. The dynamic mechanism of this invention enables the early warning system to respond to equipment malfunctions in real time, shortening the risk detection cycle. It is particularly suitable for chemical scenarios with high real-time requirements, such as high-pressure and high-temperature environments, reducing the probability of sudden failures.

[0027] This invention incorporates the risk transmission of related equipment into the assessment system, breaking through the limitations of "single equipment assessment" and preventing chain accidents from the perspective of the entire chemical system. It is especially suitable for scenarios with dense equipment and complex processes in large chemical plants, and improves system-level safety protection capabilities.

[0028] This invention transforms abstract management behaviors into quantifiable indicators such as calculable personnel competence scores, maintenance and change scores, and hazard rectification scores, directly linking management level with risk. It provides users with actionable management optimization directions, achieving synergy between "technical prevention and control" and "management prevention and control," thereby reducing risks caused by human error and management loopholes from the source.

[0029] In a second aspect, the present invention provides a risk warning system for chemical equipment, used to execute the risk warning method for chemical equipment described in any of the first aspects above.

[0030] Thirdly, the present invention provides an electronic device, comprising: a memory and one or more processors; the memory and the processors are coupled; wherein the memory stores computer program code, the computer program code including computer instructions, and when the computer instructions are executed by the processor, the electronic device performs the risk warning method for chemical equipment described in any of the first aspects above.

[0031] Fourthly, a computer-readable storage medium is provided, including computer instructions that, when executed on an electronic device, cause the electronic device to perform the risk warning method for chemical equipment as described in any of the first aspects above.

[0032] Fifthly, a computer program product is provided, which, when run on a computer, causes the computer to execute the risk warning method for chemical equipment described in any of the first aspects above.

[0033] It is understood that the beneficial effects of the risk warning system for chemical equipment in the second aspect, the electronic equipment in the third aspect, the computer-readable storage medium in the fourth aspect, and the computer program product in the fifth aspect can be referred to the beneficial effects in the first aspect and any of its possible design embodiments, and will not be repeated here. Attached Figure Description

[0034] Figure 1A flowchart illustrating a risk warning method for chemical equipment provided in this application embodiment;

[0035] Figure 2 This is a schematic diagram of a risk warning system for chemical equipment provided in an embodiment of this application. Detailed Implementation

[0036] The technical solutions of the embodiments of this application will be described below with reference to the accompanying drawings. In the description of this application, unless otherwise stated, " / " indicates that the objects before and after are in an "or" relationship. For example, A / B can represent A or B. "And / or" in this application is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone, where A and B can be singular or plural. Furthermore, in the description of this application, unless otherwise stated, "multiple" refers to two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple. Furthermore, to facilitate a clear description of the technical solutions in the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish identical or similar items with substantially the same function and effect. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and that "first" and "second" are not necessarily different. Meanwhile, in the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is being used as an example, illustration, or description. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of terms such as "exemplary" or "for example" is intended to present related concepts in a concrete manner for ease of understanding.

[0037] In the chemical production sector, the safe operation of chemical equipment is crucial for ensuring production efficiency, personnel safety, and environmental safety, and accurate risk early warning is a core element of achieving equipment safety management. With the increasing complexity and scale of chemical plants, the risks faced by equipment are becoming more diverse. How to comprehensively and in real-time assess equipment risks and provide early warnings of potential hazards has become a pressing technical problem for the industry.

[0038] In existing technologies, risk warning for chemical equipment mainly revolves around the operating parameters of the equipment itself. This involves deploying sensors to collect data such as pressure, temperature, and vibration spectra, and combining this data with preset safety limits to determine anomalies. Some solutions also attempt to incorporate historical equipment failure data or simple environmental parameters (such as temperature and humidity) for risk assessment. These methods, with the equipment's condition at their core, construct a basic risk warning framework, achieving a certain level of monitoring and alarming for equipment malfunctions.

[0039] However, existing technologies have significant limitations: First, the assessment dimensions are singular, focusing only on the equipment's physical condition and ignoring the impact of corrosive gases in the environment, the process connections with adjacent equipment, and the risk transmission caused by physical distance. Furthermore, management factors such as personnel qualifications, maintenance efficiency, and the effectiveness of hazard rectification are not incorporated into the assessment system, making it difficult to comprehensively reflect the true risk status of the equipment. Second, the static assessment model, with fixed weight allocation and threshold settings, cannot dynamically adjust the assessment logic based on equipment health, environmental changes, or management levels, resulting in insufficient adaptability to the risk characteristics of different equipment. Third, the lack of quantitative modeling of risk transmission mechanisms between equipment makes it impossible to predict the chain reactions that may be triggered by a single equipment failure, limiting control capabilities in complex chemical systems. Fourth, the difficulty in quantifying management factors leads to a lack of data linkage between risk assessment and management improvement, preventing the formation of a closed loop of "assessment-rectification-optimization." Therefore, a new method that integrates multi-dimensional data, possesses dynamic adaptability, and has risk transmission early warning capabilities is urgently needed to address the shortcomings of existing technologies and improve the comprehensiveness, real-time nature, and systematic nature of risk early warning for chemical equipment.

[0040] To address the above problems, this invention provides a risk warning method for chemical equipment. See also... Figure 1 The present invention provides a risk warning method for chemical equipment, comprising the following steps S101-S104:

[0041] S101: Determine the equipment score, environmental score, and management score corresponding to the first chemical equipment.

[0042] The equipment score is determined based on the equipment information corresponding to the first chemical equipment. The equipment information includes equipment attribute data, operating status data, and historical fault data of the first chemical equipment.

[0043] The environmental score is determined based on the environmental information corresponding to the first chemical equipment. This environmental information includes environmental data of the location of the first chemical equipment and the correlation data between the first and second chemical equipment. The second chemical equipment is connected to the first chemical equipment.

[0044] The management score is determined based on the management information corresponding to the first chemical equipment. This management information includes personnel data for the target operators, as well as historical maintenance data, spare parts inventory data, equipment change records, historical hazard rectification data, and historical inspection data for the first chemical equipment. The target operators are the personnel responsible for operating the first chemical equipment.

[0045] In some embodiments, the equipment attribute data includes equipment type data, equipment material data (e.g., steel, iron, copper), equipment structure data (e.g., equipment wall thickness), equipment usage date data, and equipment validity period data for the first chemical equipment.

[0046] Since the device attribute data is all static, it can be obtained from a security control system or device management system that stores device attribute data. Alternatively, it can be obtained through manual user input.

[0047] In some embodiments, the operating status data includes the pressure, temperature, vibration spectrum of the first chemical equipment during operation, and the safety limits of the monitoring equipment.

[0048] The monitoring equipment is used to monitor the pressure, temperature, and vibration spectrum of the first chemical equipment during operation. The safety limits of the monitoring equipment include upper and lower limits. Operating status data can be acquired based on the data acquisition and monitoring control system (SCADA system), distributed control system (DCS system), and manufacturing execution system (MES system) related to the first chemical equipment.

[0049] In some embodiments, historical fault data includes the fault time, fault type, and fault hazard level of the first chemical equipment.

[0050] The hazard level of the first chemical equipment can be classified as Level 0, Level 1, Level 2, Level 3, etc. The types of failures of the first chemical equipment can include tower-related failures (e.g., scaling and blockage inside the tower, seal failure and leakage, structural damage), tank-related failures (e.g., corrosion and leakage, overpressure and safety valve failure, accessory failure), and pump-related failures (e.g., mechanical seal failure, bearing and shaft system failure, cavitation and abnormal flow). Furthermore, the types of failures of the first chemical equipment can also include more failures (e.g., loose connections), but this application does not specifically limit the types of failures of the first chemical equipment.

[0051] In some embodiments, the environmental data includes the temperature, humidity, and corrosive gas concentration of the environment in which the first chemical equipment is located. The temperature, humidity, and corrosive gas concentration of the environment in which the first chemical equipment is located can be detected using IoT sensors or a MES system. For example, a temperature sensor can detect the temperature of the environment in which the first chemical equipment is located; a humidity sensor can detect the humidity of the environment in which the first chemical equipment is located; and an MES system can detect the concentration of corrosive gases in the environment in which the first chemical equipment is located.

[0052] In some embodiments, the correlation data between the first chemical equipment and the second chemical equipment includes the process correlation between the first chemical equipment and the second chemical equipment, and the physical distance between the first chemical equipment and the second chemical equipment. The process correlation between the first chemical equipment and the second chemical equipment is determined based on the total number of interfaces and the number of connected interfaces between the first chemical equipment and the second chemical equipment.

[0053] For example, the process correlation degree between the first chemical equipment and the second chemical equipment = the number of connection interfaces between the first chemical equipment and the second chemical equipment / the total number of interfaces between the first chemical equipment and the second chemical equipment.

[0054] In some embodiments, personnel data includes the qualification level of the target personnel, the training completion rate and the operation success rate within the target time period.

[0055] The training completion rate of the target operators within the target time period is determined based on the ratio of the number of training sessions completed by the target operators within the target time period to the number of training sessions required. The operation success rate of the target operators within the target time period is determined based on the ratio of the number of times the target operators performed correct operations on the first chemical equipment within the target time period to the total number of operations performed.

[0056] In some embodiments, historical maintenance data includes the maintenance type and on-time maintenance rate for the first chemical equipment within a target time period. Spare parts inventory data includes the quantity of spare parts for the first chemical equipment in inventory. Equipment change records include change data for the first chemical equipment within the target time period. The change data for the first chemical equipment includes location relocation data, equipment parameter change data, and parts replacement data, etc.

[0057] The on-time repair rate for the first chemical equipment within the target time period is determined based on the ratio of the number of days of repair delay to the standard number of days of delay for the first chemical equipment within the target time period.

[0058] For example, the on-time repair rate of the first chemical equipment within the target time period = 1 - (the number of days of repair delay for the first chemical equipment within the target time period / the standard number of days of delay).

[0059] In some embodiments, historical hazard rectification data includes the number of hazards, hazard level, and on-time rectification rate of the first chemical equipment within the target time period.

[0060] The on-time rectification rate for the first chemical equipment within the target time period is determined based on the ratio of the overtime time for rectification of hidden dangers for the first chemical equipment within the target time period to the standard time for rectification of hidden dangers for the first chemical equipment within the target time period.

[0061] For example, the on-time rectification rate of the first chemical equipment within the target time period = 1 - (the overtime time for rectification of the first chemical equipment within the target time period / the standard time for rectification of the first chemical equipment within the target time period).

[0062] In some embodiments, historical inspection data includes the actual number of inspections, the expected number of inspections, the number of anomalies processed, and the total number of anomalies discovered for the first chemical equipment within a target time period.

[0063] "Abnormalities" can include equipment inherent abnormalities, operational parameter abnormalities, environmental risk abnormalities, management process abnormalities, safety protection abnormalities, and process-related abnormalities. Equipment inherent abnormalities refer to defects in the physical structure or materials of the equipment, directly affecting its safe operation. Operational parameter abnormalities refer to key parameters deviating from safety limits during equipment operation, triggering risk warnings. Environmental risk abnormalities refer to external risks arising from the environment in which the equipment is located or related equipment. Management process abnormalities refer to loopholes in personnel operation or management, leading to the failure of risk control. Safety protection abnormalities refer to the failure of equipment safety accessories or monitoring systems, resulting in uncontrollable risks. Process-related abnormalities refer to deviations in production process or flow parameters from design standards, triggering systemic risks.

[0064] In some embodiments, the basic health status of the first chemical equipment is determined based on its equipment attribute data and historical fault data. The dynamic anomaly coefficient of the first chemical equipment is determined based on its operating status data. Finally, the equipment score of the first chemical equipment is determined based on its basic health status, dynamic anomaly coefficient, and dynamic anomaly weight.

[0065] The dynamic anomaly coefficients include pressure anomaly coefficients, temperature anomaly coefficients, and vibration spectrum anomaly coefficients. The dynamic anomaly weights include the pressure anomaly weight corresponding to the pressure anomaly coefficient, the temperature anomaly weight corresponding to the temperature anomaly coefficient, and the vibration spectrum anomaly weight corresponding to the vibration spectrum anomaly coefficient. The basic health status of the first chemical equipment can be generated based on the equipment's knowledge graph, calculated by weighting material properties, structural parameters, and historical fault data using three-dimensional feature vectors.

[0066] In some embodiments, when the alignment value corresponding to the operating parameters of the first chemical equipment is greater than or equal to the lower limit and less than or equal to the upper limit, the dynamic anomaly coefficient corresponding to the operating parameters of the first chemical equipment can be determined as 0.

[0067] The operating parameters of the first chemical equipment are any one of the pressure, temperature, and vibration spectrum during its operation. When the operating parameter of the first chemical equipment is pressure, the corresponding dynamic anomaly coefficient is the pressure anomaly coefficient. When the operating parameter of the first chemical equipment is temperature, the corresponding dynamic anomaly coefficient is the temperature anomaly coefficient. When the operating parameter of the first chemical equipment is vibration spectrum, the corresponding dynamic anomaly coefficient is the vibration spectrum anomaly coefficient.

[0068] In some embodiments, when the alignment value corresponding to the operating parameter of the first chemical equipment is greater than the upper limit value, the value of the dynamic anomaly coefficient corresponding to the operating parameter of the first chemical equipment is determined based on the alignment value, the upper limit value and the preset threshold upper limit value corresponding to the operating parameter of the first chemical equipment.

[0069] In some embodiments, when the alignment value corresponding to the operating parameter of the first chemical equipment is less than the lower limit value, the value of the dynamic anomaly coefficient corresponding to the operating parameter of the first chemical equipment is determined based on the alignment value, the lower limit value, and the preset threshold lower limit.

[0070] For example, the equipment score H_phy corresponding to the first chemical equipment can be represented as:

[0071] H_phy = (1 - ∑w_i·D_i) × S_base;

[0072] D_i =0, x_safe_l≤ x_i ≤ x_safe_h;

[0073] D_i =(x_i - x_safe_h) / (x_threshold_h - x_safe_h),x_i > x_safe_h;

[0074] D_i = (x_safe_l- x_i ) / (x_safe_l - x_threshold_l),x_i < x_safe_l;

[0075] Where w_i represents the dynamic anomaly weight, D_i represents the dynamic anomaly coefficient, and S_base represents the basic health of the first chemical equipment. x_i represents the alignment value corresponding to the operating parameters of the first chemical equipment, x_safe_l represents the lower limit value, x_safe_h represents the upper limit value, x_threshold_h represents the preset upper limit value, and x_threshold_l represents the preset lower limit value. The preset upper limit value and the preset lower limit value are static attributes of the first chemical equipment.

[0076] In some embodiments, the alignment value corresponding to the operating parameters of the first chemical equipment is determined based on the values ​​of the operating parameters of the first chemical equipment at a first time and a second time, respectively. The first time is the sampling time preceding the target sampling time, and the second time is the sampling time following the target sampling time. The difference between the first time and the target sampling time and the difference between the second time and the target sampling time are the same.

[0077] For example, the alignment value Q corresponding to the operating parameters of the first chemical equipment can be expressed as:

[0078] Q=Q1×(1-Δt / τ)+Q2×(Δt / τ);

[0079] Where Q1 represents the value of the operating parameter of the first chemical equipment at the first time point, Q2 represents the value of the operating parameter of the first chemical equipment at the second time point, Δt represents the difference between the first time point and the target sampling time, and τ is the dynamic interpolation weight, which represents the smoothing window length of the interpolation algorithm when the operating parameters of the first chemical equipment change gradually. This directly affects the smoothness of data alignment and the ability to preserve abrupt changes. When the operating parameters of the first chemical equipment fluctuate drastically, it is necessary to shorten the interpolation window to preserve abrupt changes; therefore, a dynamic interpolation weight method is adopted. The formula for calculating the dynamic interpolation weight is as follows:

[0080] τ=τ_base / (1+|Δx / Δt| / x_range);

[0081] Where τ_base is the baseline value of the dynamic interpolation weight (e.g., 30 seconds); Δx = Q2 - Q1; and x_range represents the measurement range of the monitoring device (as mentioned above). The measurement range of the monitoring device is an inherent attribute value of the monitoring device. For example, if the measurement range of a household thermometer is 35-42℃, then x_range = 7. According to the formula, the larger Δx / Δt is, the smaller τ is.

[0082] In some embodiments, the environmental risk value of the environment in which the first chemical equipment is located is determined based on environmental data corresponding to the first chemical equipment. The risk transmission value of the second chemical equipment is determined based on the correlation data between the first and second chemical equipment and the health score of the second chemical equipment. The environmental score corresponding to the first chemical equipment is determined based on the environmental risk value of the environment in which the first chemical equipment is located and the risk transmission value of the second chemical equipment. The health score of the second chemical equipment is determined based on the equipment score, environmental score, and management score corresponding to the second chemical equipment, as well as the weights of the equipment score, environmental score, and management score.

[0083] For example, the environmental score H_env corresponding to the first chemical equipment can be represented as:

[0084] H_env=1-σ(E_local+E_neighbor+b);

[0085] E_neighbor=∑(ρ_ij×D_j);

[0086] σ(x) = 1 / (1+e^{-x});

[0087] D_j = (1 - H_j) / (1 + H_j)

[0088] x = E_local + E_neighbor + b;

[0089] Here, σ(x) is the Sigmoid function, used to map the input value x to the (0,1) interval to quantify the nonlinear impact of environmental risk on the health score of the first chemical equipment. E_local represents the environmental risk value of the environment in which the first chemical equipment is located, which can be calculated by linear normalization based on the concentration of corrosive gases, ambient temperature, and humidity. b represents the offset, which is obtained based on historical accidents and feedback learning, and is usually taken as b = -0.5 (to balance the sensitivity of risk transmission). This offset is dynamically adjusted according to the actual risk and the predicted risk. E_neighbor represents the risk transmission value of the second chemical equipment, ρ_ij represents the correlation strength between the first and second chemical equipment, which is determined based on the product of the process correlation between the first and second chemical equipment and the physical distance between the first and second chemical equipment; D_j represents the risk value of the second chemical equipment, and H_j represents the health score of the second chemical equipment.

[0090] In some embodiments, the personnel competence score corresponding to the first chemical equipment is determined based on the qualification level of the target operators, the training completion rate and operation success rate within the target time period. The maintenance change score corresponding to the first chemical equipment is determined based on the maintenance type and on-time maintenance rate for the first chemical equipment within the target time period, as well as the spare parts inventory adequacy rate and equipment change records of the first chemical equipment. The hazard rectification score corresponding to the first chemical equipment is determined based on the number of hazards, hazard level, and hazard rectification on-time rate of the first chemical equipment within the target time period. The inspection score corresponding to the first chemical equipment is determined based on the inspection attendance rate and anomaly handling rate of the first chemical equipment within the target time period. Finally, the management score corresponding to the first chemical equipment is determined based on the personnel competence score, maintenance change score, hazard rectification score, and inspection score, as well as the personnel competence management weight corresponding to the personnel competence score, the maintenance change management weight corresponding to the maintenance change score, the hazard rectification management weight corresponding to the hazard rectification score, and the inspection management weight corresponding to the inspection score.

[0091] The spare parts inventory adequacy rate for the first chemical equipment is determined based on the quantity of spare parts in the corresponding inventory. The inspection completion rate is determined based on the actual number of inspections and the expected number of inspections for the first chemical equipment within the target time period. The anomaly handling rate is determined based on the number of anomalies handled and the total number of anomalies discovered for the first chemical equipment within the target time period.

[0092] For example, the management score H_mgmt corresponding to the first chemical equipment can be expressed as:

[0093] H_mgmt=∏(1-μ_i·f_i);

[0094] Where μ_i represents the weight of the corresponding management dimension (e.g., personnel capability management weight, maintenance and change management weight, hazard rectification management weight, and inspection management weight), which can be determined based on the analytic hierarchy process (AHP). For example, personnel capability management weight = 0.2, maintenance and change management weight = 0.3, hazard rectification management weight = 0.3, and inspection management weight = 0.1. f_i represents the risk membership degree of the corresponding management dimension, where f_i = 1 - the risk score of the corresponding management dimension (e.g., personnel capability score, maintenance and change score, hazard rectification score, and inspection score).

[0095] S102: Based on the equipment score, environmental score, and management score corresponding to the first chemical equipment, as well as the weights of the equipment score, environmental score, and management score, determine the health score of the first chemical equipment.

[0096] The weights for equipment scoring, environmental scoring, and management scoring are all determined based on the equipment scoring, environmental scoring, and management scoring corresponding to the first chemical equipment.

[0097] For example, the health score H of the first chemical equipment can be expressed as:

[0098] H=α·H_phy+β·H_env+γ·H_mgmt.

[0099] Where α represents the equipment scoring weight, β represents the environmental scoring weight, and γ represents the management scoring weight.

[0100] In some embodiments, the device scoring weights are determined based on a first preset relationship.

[0101] The first presupposed relationship includes:

[0102] α = (1 - H_phy) / D;

[0103] Where D = max ((3-(H_phy+H_env+H_mgmt)), 0.1). H_phy represents the equipment score, H_env represents the environmental score, and H_mgmt represents the management score.

[0104] In some embodiments, environmental score weights are determined based on a second preset relationship.

[0105] The second presupposed relationship includes:

[0106] β=(1-H_env) / D.

[0107] In some embodiments, the management score weights are determined based on a third preset relationship.

[0108] The third pre-defined relationship includes:

[0109] γ=(1-H_mgmt) / D.

[0110] S103: Determine the risk level of the first chemical equipment based on its health score.

[0111] Among them, the higher the health score of the first chemical equipment, the lower the risk corresponding to the risk level of the first chemical equipment.

[0112] For example, the risk level of the first chemical equipment may include Level 1 (low), Level 2 (medium), Level 3 (higher), and Level 4 (high). Different risk levels correspond to different scoring ranges. The risk level of the first chemical equipment can be determined based on the scoring range in which its health score falls. The correspondence between the health score and the risk level of the first chemical equipment is shown in Table 1 below.

[0113]

[0114] S104: Based on the risk level of the first chemical equipment, provide early warning information to characterize the risk level of the first chemical equipment.

[0115] In some embodiments, decisions corresponding to the risk level of the first chemical equipment are made based on the risk level of the first chemical equipment.

[0116] For example, if the risk level of the first chemical equipment is determined to be Level 1, the following decision can be made regarding the first chemical equipment: observe its operation and maintain the routine inspection cycle.

[0117] If the risk level of the first chemical equipment is determined to be Level 2, the following decisions can be made for the first chemical equipment: strengthen inspections, and provide inspection suggestions for the equipment itself or related equipment in the surrounding area based on the weight of each contributing factor in the health score. For example, if the pressure of the storage tank C101 associated with this equipment is too high, resulting in excessive bearing pressure, please reduce the pressure of storage tank C101 in time, and increase the equipment inspection cycle from the current once / day to three times / day.

[0118] If the risk level of the first chemical equipment is determined to be Level 3, the following decision can be made for the first chemical equipment: maintenance within 48 hours + area isolation. Based on the weight of each contributing factor in the health score, specific maintenance suggestions for the equipment body or surrounding equipment can be given, such as: if the equipment shell is severely corroded, please take measures to replace the shell as soon as possible.

[0119] If the risk level of the first chemical equipment is determined to be Level 4, the following decisions can be made for the first chemical equipment: emergency shutdown, immediate isolation of the equipment, and activation of the emergency plan.

[0120] In some embodiments, the present invention can construct a data feedback loop by comparing decision-making methods with actual manual operations in real time. When a deviation is detected between the manual handling plan and the original decision (e.g., a worker shortens the seal inspection cycle from the recommended 7 days to 3 days), the operating parameters and result data are automatically recorded, the difference rate is calculated through an optimization algorithm, and the weight of the health score is dynamically adjusted (e.g., the weight of management behavior is increased by 1.57 times). This mechanism adopts a two-way learning logic: if the manual operation is more effective, the model is optimized by absorbing experience; if the execution deviation leads to losses (e.g., failure to replace bearings in time causes the failure to escalate), the warning rules are corrected in reverse. This achieves a self-evolving capability that becomes more accurate with use.

[0121] As can be seen, this invention fully utilizes the multi-source heterogeneous data accumulated by existing platforms such as chemical enterprise safety production control platforms, MES platforms, and equipment management platforms. It applies a health scoring assessment model with dynamic weights to comprehensively and dynamically measure equipment health scores, overcoming the limitations of traditional single-dimensional assessments. Based on the equipment health scores, a four-level early warning system is constructed, achieving a closed-loop process from "equipment status monitoring" to "assisted decision-making and handling."

[0122] Furthermore, this invention constructs a bidirectional learning engine of "operational feedback-model optimization" to overcome the problem of "rigid decision-making" in traditional systems. By comparing the effects of system suggestions and manual operations (such as adjusting detection cycles and spare parts replacement strategies) in real time, it dynamically calculates the difference rate and feeds it back into the model: when manual operations are better, the weight of management behaviors is automatically increased; when execution deviations cause losses, the warning threshold is corrected in reverse. This creates the unique advantage of "becoming smarter the more it is used".

[0123] This invention also provides a risk warning system for chemical equipment, see [link to relevant documentation]. Figure 2 The present invention provides a risk warning system for chemical equipment, comprising: a sub-score determination module, a total score determination module, a risk level determination module, and a warning module.

[0124] The sub-scoring determination module is used to determine the equipment score, environmental score, and management score corresponding to the first chemical equipment. The overall score determination module is used to determine the health score of the first chemical equipment based on its equipment score, environmental score, management score, and their respective weights. The risk level determination module is used to determine the risk level of the first chemical equipment based on its health score. The early warning module is used to provide early warning information characterizing the risk level of the first chemical equipment based on its risk level.

[0125] In some solutions, multiple embodiments of this application can be combined, and the combined solution can be implemented. Optionally, some operations in the processes of each method embodiment may be combined, and / or the order of some operations may be changed. Furthermore, the execution order between the steps of each process is merely exemplary and does not constitute a limitation on the execution order between steps; other execution orders are also possible. It is not intended to indicate that the execution order is the only possible order in which these operations can be performed. Those skilled in the art will conceive of various ways to reorder the operations described herein. In addition, it should be noted that the process details involved in one embodiment of this document are similarly applicable to other embodiments, or different embodiments may be combined.

[0126] Furthermore, some steps in the method embodiments can be equivalently replaced with other possible steps. Alternatively, some steps in the method embodiments may be optional and can be deleted in certain use cases. Or, other possible steps may be added to the method embodiments. Moreover, the various method embodiments can be implemented individually or in combination.

[0127] Through the above description of the implementation methods, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the system can be divided into different functional modules to complete all or part of the functions described above.

[0128] In the several embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between systems or units may be electrical, mechanical, or other forms.

[0129] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0130] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiments of this application, in essence, or the part that contributes, or all or part of the technical solution, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0131] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A risk warning method for chemical equipment, characterized in that, include: Determine the equipment score, environmental score, and management score corresponding to the first chemical equipment; The equipment score is determined based on the equipment information corresponding to the first chemical equipment; the environmental score is determined based on the environmental information corresponding to the first chemical equipment; the management score is determined based on the management information corresponding to the first chemical equipment; the equipment information includes equipment attribute data, operating status data, and historical fault data of the first chemical equipment; the environmental information includes environmental data of the environment in which the first chemical equipment is located, and correlation data between the first chemical equipment and the second chemical equipment; the second chemical equipment is connected to the first chemical equipment; the management information includes personnel data of the target operators, as well as historical maintenance data, spare parts inventory data, equipment change records, historical hidden danger rectification data, and historical inspection data for the first chemical equipment; the target operators are the operators of the first chemical equipment; Based on the equipment score, environmental score, and management score corresponding to the first chemical equipment, as well as the weights of the equipment score, environmental score, and management score, the health score of the first chemical equipment is determined; the weights of the equipment score, the environmental score, and the management score are all determined based on the equipment score, environmental score, and management score corresponding to the first chemical equipment. Based on the health score of the first chemical equipment, the risk level of the first chemical equipment is determined; Based on the risk level of the first chemical equipment, a warning message is provided to characterize the risk level of the first chemical equipment; The equipment score corresponding to the first chemical equipment is expressed as follows: H_phy = (1 - ∑w_i·D_i) × S_base; D_i =0, x_safe_l≤ x_i ≤ x_safe_h; D_i =(x_i - x_safe_h) / (x_threshold_h - x_safe_h),x_i > x_safe_h; D_i = (x_safe_l- x_i ) / (x_safe_l - x_threshold_l),x_i < x_safe_l; H_phy represents the equipment score corresponding to the first chemical equipment, w_i represents the dynamic anomaly weight, D_i represents the dynamic anomaly coefficient, S_base represents the basic health of the first chemical equipment, x_i represents the alignment value corresponding to the operating parameters of the first chemical equipment, x_safe_l represents the lower limit value of x_i, x_safe_h represents the upper limit value of x_i, x_threshold_h represents the preset upper limit value, x_threshold_l represents the preset lower limit value, and the preset upper limit value and preset lower limit value are the static attributes of the first chemical equipment; The environmental score corresponding to the first chemical equipment is expressed as follows: H_env=1-σ(E_local+E_neighbor+b); E_neighbor=∑(ρ_ij×D_j); σ(x) = 1 / (1+e^{-x}); D_j = (1 - H_j) / (1 + H_j) x = E_local + E_neighbor + b; H_env represents the environmental score corresponding to the first chemical equipment, σ(x) is the Sigmoid function used to map the input value x to the (0,1) interval, E_local represents the environmental risk value of the environment in which the first chemical equipment is located, b represents the offset, E_neighbo represents the risk transmission value of the second chemical equipment, ρ_ij represents the correlation strength between the first chemical equipment and the second chemical equipment, D_j represents the risk value of the second chemical equipment, and H_j represents the health score of the second chemical equipment. The management score corresponding to the first chemical equipment is expressed as follows: H_mgmt=∏(1-μ_i·f_i); H_mgmt represents the management score corresponding to the first chemical equipment, μ_i represents the weight of the corresponding management dimension, f_i represents the risk membership degree of the corresponding management dimension, and f_i = 1 - the risk score of the corresponding management dimension.

2. The method according to claim 1, characterized in that, The equipment attribute data includes equipment type data, equipment material data, equipment structure data, equipment usage date data, and equipment validity period data of the first chemical equipment; the operating status data includes the pressure, temperature, and vibration spectrum of the first chemical equipment during operation, as well as the safety limits of the monitoring equipment; the monitoring equipment is a device used to monitor the pressure, temperature, and vibration spectrum of the first chemical equipment during operation; the historical fault data includes the fault time, fault type, and fault hazard level of the first chemical equipment.

3. The method according to claim 2, characterized in that, The environmental data includes the temperature, humidity, and corrosive gas concentration of the environment in which the first chemical equipment is located; the correlation data between the first chemical equipment and the second chemical equipment includes the process correlation between the first chemical equipment and the second chemical equipment, and the physical distance between the first chemical equipment and the second chemical equipment; the process correlation between the first chemical equipment and the second chemical equipment is determined based on the total number of interfaces and the number of connected interfaces between the first chemical equipment and the second chemical equipment.

4. The method according to claim 3, characterized in that, The personnel data includes the qualification level of the target operators, the training completion rate and operation success rate within the target time period; the historical maintenance data includes the maintenance type and on-time maintenance rate for the first chemical equipment within the target time period; the spare parts inventory data includes the quantity of spare parts for the first chemical equipment in inventory; the equipment change records include change data for the first chemical equipment within the target time period; the change data for the first chemical equipment includes location movement data, equipment parameter change data, and parts replacement data; the historical hazard rectification data includes the number of hazards, hazard level, and on-time rectification rate for the first chemical equipment within the target time period; the historical inspection data includes the actual number of inspections, the expected number of inspections, the number of anomalies handled, and the total number of anomalies discovered for the first chemical equipment within the target time period.

5. The method according to claim 4, characterized in that, The determination of the equipment score corresponding to the first chemical equipment includes: Based on the equipment attribute data and historical fault data corresponding to the first chemical equipment, the basic health status of the first chemical equipment is determined. Based on the operating status data corresponding to the first chemical equipment, the dynamic anomaly coefficient of the first chemical equipment is determined; the dynamic anomaly coefficient includes the pressure anomaly coefficient, the temperature anomaly coefficient, and the vibration spectrum anomaly coefficient. Based on the basic health status, dynamic anomaly coefficient, and dynamic anomaly weight of the first chemical equipment, the equipment score corresponding to the first chemical equipment is determined; the dynamic anomaly weight includes the pressure anomaly weight corresponding to the pressure anomaly coefficient, the temperature anomaly weight corresponding to the temperature anomaly coefficient, and the vibration spectrum anomaly weight corresponding to the vibration spectrum anomaly coefficient.

6. The method according to claim 5, characterized in that, The safety limits of the monitoring equipment include an upper limit and a lower limit; determining the dynamic anomaly coefficient of the first chemical equipment based on its operating status data includes: When the alignment value corresponding to the operating parameter of the first chemical equipment is greater than or equal to the lower limit and less than or equal to the upper limit, the dynamic anomaly coefficient corresponding to the operating parameter of the first chemical equipment is determined to be 0; the operating parameter of the first chemical equipment is any one of pressure, temperature, and vibration spectrum during the operation of the first chemical equipment; when the operating parameter of the first chemical equipment is pressure, the dynamic anomaly coefficient corresponding to the operating parameter of the first chemical equipment is the pressure anomaly coefficient; when the operating parameter of the first chemical equipment is temperature, the dynamic anomaly coefficient corresponding to the operating parameter of the first chemical equipment is the temperature anomaly coefficient; when the operating parameter of the first chemical equipment is vibration spectrum, the dynamic anomaly coefficient corresponding to the operating parameter of the first chemical equipment is the vibration spectrum anomaly coefficient. If the alignment value corresponding to the operating parameter of the first chemical equipment is greater than the upper limit value, the value of the dynamic anomaly coefficient corresponding to the operating parameter of the first chemical equipment is determined based on the alignment value corresponding to the operating parameter of the first chemical equipment, the upper limit value, and the preset threshold upper limit. If the alignment value corresponding to the operating parameters of the first chemical equipment is less than the lower limit value, the value of the dynamic anomaly coefficient corresponding to the operating parameters of the first chemical equipment is determined based on the alignment value corresponding to the operating parameters of the first chemical equipment, the lower limit value, and the preset threshold lower limit.

7. The method according to claim 6, characterized in that, The determination of the environmental score corresponding to the first chemical equipment includes: Based on the environmental data corresponding to the first chemical equipment, the environmental risk value of the environment in which the first chemical equipment is located is determined. Based on the correlation data between the first chemical equipment and the second chemical equipment, and the health score of the second chemical equipment, the risk transmission value of the second chemical equipment is determined; the health score of the second chemical equipment is determined based on the equipment score, environmental score, and management score corresponding to the second chemical equipment, as well as the weights of the equipment score, environmental score, and management score. Based on the environmental risk value of the environment in which the first chemical equipment is located and the risk transmission value of the second chemical equipment, the environmental score corresponding to the first chemical equipment is determined.

8. The method according to claim 7, characterized in that, The determination of the management score corresponding to the first chemical equipment includes: Based on the qualification level of the target operators, the training completion rate and operation success rate within the target time period, the personnel capability score corresponding to the first chemical equipment is determined. Based on the maintenance type and on-time maintenance rate of the first chemical equipment during the target time period, as well as the spare parts inventory adequacy rate and equipment change records of the first chemical equipment, the maintenance change score corresponding to the first chemical equipment is determined; the spare parts inventory adequacy rate of the first chemical equipment is determined based on the number of spare parts in the inventory corresponding to the first chemical equipment. Based on the number of hidden dangers, the level of hidden dangers and the on-time rate of hidden danger rectification of the first chemical equipment during the target time period, the hidden danger rectification score corresponding to the first chemical equipment is determined. Based on the inspection completion rate and anomaly handling rate of the first chemical equipment within the target time period, the inspection score corresponding to the first chemical equipment is determined; the inspection completion rate is determined based on the actual number of inspections and the expected number of inspections for the first chemical equipment within the target time period; the anomaly handling rate is determined based on the number of anomalies that have been handled and the total number of anomalies that have been discovered for the first chemical equipment within the target time period. Based on the personnel capability score, maintenance and change score, hidden danger rectification score, and inspection score corresponding to the first chemical equipment, as well as the personnel capability management weight corresponding to the personnel capability score, the maintenance and change management weight corresponding to the maintenance and change score, the hidden danger rectification management weight corresponding to the hidden danger rectification score, and the inspection management weight corresponding to the inspection score, the management score corresponding to the first chemical equipment is determined.

9. The method according to claim 8, characterized in that, Also includes: The device scoring weights are determined based on a first preset relationship; the first preset relationship includes α=(1-H_phy) / D; The environmental scoring weights are determined based on a second preset relationship; the second preset relationship includes β=(1-H_env) / D; The management scoring weights are determined based on a third preset relationship; the third preset relationship includes γ=(1-H_mgmt) / D; Where D = max((3-(H_phy+H_env+H_mgmt)),0.1); α represents the equipment scoring weight, β represents the environmental scoring weight, γ represents the management scoring weight; H_phy represents the equipment score, H_env represents the environmental score, and H_mgmt represents the management score.

10. The method according to claim 9, characterized in that, After determining the risk level of the first chemical equipment based on its health score, the method further includes: Based on the risk level of the first chemical equipment, a decision corresponding to the risk level of the first chemical equipment is executed.

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