Risk early warning method for chemical equipment

Abstract

The invention provides a risk early warning method for chemical equipment, relates to the technical field of chemical equipment safety management, and respectively determines an equipment score, an environment score and a management score based on equipment information, environment information and management information corresponding to first chemical equipment. And determining a health score of the first chemical equipment based on the equipment score, the environment score, the management score, the equipment score weight, the environment score weight and the management score weight. And determining a risk level of the first chemical equipment based on the health score of the first chemical equipment. And based on the risk level of the first chemical equipment, prompting early warning information for representing the risk level of the first chemical equipment. Through multi-source heterogeneous data fusion, a dynamic weight reconstruction model and a self-evolution mechanism, the accuracy of chemical equipment risk early warning is improved.

Description

Technical Field

[0001] The present application relates to the technical field of intelligent industrial safety management and control, and in particular to a risk warning method for chemical equipment. Background Art

[0002] Risk warning for chemical equipment is the core link in ensuring industrial safety production.

[0003] Mainstream chemical equipment risk warning methods are primarily based on fixed rules implemented using a single sensor. These technologies collect operational parameters (such as temperature and pressure) from chemical equipment and set fixed thresholds for over-limit alarms. Their core logic relies on threshold comparisons based on single-dimensional data to provide a preliminary assessment of abnormal chemical equipment conditions, providing a fundamental safety warning function for chemical production.

[0004] However, since the warning logic of the above-mentioned technology is only based on the single-dimensional operating data or static parameters of chemical equipment, it lacks the ability to analyze the correlation between multiple factors in complex industrial scenarios, and the fixed rules cannot dynamically adapt to dynamic conditions such as changes in equipment operating conditions and environmental interference. As a result, the ability to identify potential risks of chemical equipment is insufficient, and it is difficult to accurately distinguish normal fluctuations from real failures, which ultimately leads to the problem of low warning accuracy and cannot meet the reliability and accuracy requirements of chemical equipment risk management. Summary of the Invention

[0005] The embodiment of the present application provides a risk warning method for chemical equipment, which can improve the accuracy of risk warning for chemical equipment through multi-source heterogeneous data fusion, dynamic weight modeling and self-evolution mechanism.

[0006] To achieve the above objectives, the embodiments of the present application adopt the following technical solutions: In a first aspect, the present invention provides a risk early warning method for chemical equipment, the method comprising: 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 first chemical equipment 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 operator, 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 operator is the operator of the first chemical equipment.

[0007] The health score of the first chemical equipment is determined based on the equipment score, environmental score, and management score corresponding to the first chemical equipment, as well as the equipment score weight, environmental score weight, and management score weight. The equipment score weight, environmental score weight, and management score weight are all determined based on the equipment score, environmental score, and management score corresponding to the first chemical equipment.

[0008] Based on the health score of the first chemical equipment, a risk level of the first chemical equipment is determined.

[0009] Based on the risk level of the first chemical equipment, early warning information representing the risk level of the first chemical equipment is prompted.

[0010] On the basis of the above technical solution, the present invention can also be improved as follows.

[0011] Furthermore, the equipment attribute data includes the equipment type, material, structure, usage date, and expiration date 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 used to monitor the pressure, temperature, and vibration spectrum of the first chemical equipment during operation. Historical fault data includes the time, type, and risk level of the first chemical equipment's faults.

[0012] 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 the first and second chemical equipment and the physical distance between the first and second chemical equipment. 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 the first and second chemical equipment.

[0013] Furthermore, the personnel data includes the qualification level of the target operating personnel, the training completion rate and the operation success rate within the target time period. The historical maintenance data includes the maintenance type and maintenance punctuality rate for the first chemical equipment within the target time period. The spare parts inventory data includes the number of spare parts for the first chemical equipment in inventory. The equipment change record includes the change data of the first chemical equipment within the target time period. The change data of the first chemical equipment includes the location movement data of the first chemical equipment, the equipment parameter change data and the accessories replacement data. The historical hidden danger rectification data includes the number of hidden dangers, the hidden danger level and the hidden danger rectification punctuality rate of the first chemical equipment within the target time period. The historical inspection data includes the actual number of inspections for the first chemical equipment within the target time period, the expected number of inspections, the number of handled anomalies and the total number of discovered anomalies.

[0014] Furthermore, based on the equipment attribute data and historical fault data corresponding to the first chemical equipment, the basic health 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 a pressure anomaly coefficient, a temperature anomaly coefficient, and a vibration spectrum anomaly coefficient. Based on the basic health of the first chemical equipment, the dynamic anomaly coefficient, and the dynamic anomaly weight, the equipment score corresponding to the first chemical equipment is determined. The dynamic anomaly weight includes a pressure anomaly weight corresponding to the pressure anomaly coefficient, a temperature anomaly weight corresponding to the temperature anomaly coefficient, and a vibration spectrum anomaly weight corresponding to the vibration spectrum anomaly coefficient.

[0015] Furthermore, the safety limit of the monitoring equipment includes an upper limit and a lower limit. 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 the pressure, temperature, and vibration spectrum of the first chemical equipment during operation. 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.

[0016] 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 abnormality 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 corresponding to the operating parameter of the first chemical equipment.

[0017] 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 abnormality 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 corresponding to the operating parameter of the first chemical equipment.

[0018] Furthermore, based on the environmental data corresponding to the first chemical equipment, an 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, a 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 equipment score weight, environmental score weight, and management score weight. 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, an environmental score corresponding to the first chemical equipment is determined.

[0019] Furthermore, a personnel capability score corresponding to the first chemical equipment is determined based on the qualification level of the target operator, the training completion rate, and the operation success rate within the target time period. A maintenance change score corresponding to the first chemical equipment is determined based on the maintenance type and maintenance on-time rate for the first chemical equipment within the target time period, as well as the spare parts inventory adequacy rate and equipment change records for the first chemical equipment. The spare parts inventory adequacy rate for the first chemical equipment is determined based on the number of spare parts in the inventory corresponding to the first chemical equipment. A hidden danger rectification score corresponding to the first chemical equipment is determined based on the number of hidden dangers, the hidden danger level, and the hidden danger rectification on-time rate within the target time period. An inspection score corresponding to the first chemical equipment is determined based on the inspection attendance rate and exception handling rate within the target time period. 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 exception handling rate is determined based on the number of exceptions handled and the total number of exceptions discovered for the first chemical equipment within the target time period. Based on the personnel capability score, maintenance 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 change management weight corresponding to the maintenance 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.

[0020] Further, based on the first preset relationship, the device score weight is determined. The first preset relationship includes α=(1-H_phy) / D. Based on the second preset relationship, the environment score weight is determined. The second preset relationship includes β=(1-H_env) / D. Based on the third preset relationship, the management score weight is determined. The third preset relationship includes γ=(1-H_mgmt) / D. Wherein, D=max ((3-(H_phy+H_env+H_mgmt)),0.1). α represents the device score weight, β represents the environment score weight, and γ represents the management score weight. H_phy represents the device score, H_env represents the environment score, and H_mgmt represents the management score.

[0021] Furthermore, based on the risk level of the first chemical equipment, a decision corresponding to the risk level of the first chemical equipment is executed.

[0022] The beneficial effects of the present invention are: This invention constructs a risk warning model based on three core dimensions: equipment scoring, environmental scoring, and management scoring. This model overcomes the limitations of traditional single-dimensional assessments. The multi-dimensional data fusion of this invention allows risk assessments to be more closely aligned with the actual operation of chemical equipment, avoiding misjudgments caused by the omission of a single factor. It comprehensively covers potential risks in the equipment itself, the external environment, and the management process.

[0023] This invention achieves dynamic risk tracking through dynamic anomaly coefficient calculation and real-time data collection. This dynamic mechanism enables the early warning system to respond to equipment operational anomalies in real time, shortening the risk discovery cycle. This is particularly applicable to chemical industry scenarios with high real-time requirements, such as high pressure and high temperature, and reduces the probability of sudden failures.

[0024] The present invention incorporates the risk transmission of related equipment into the assessment system, breaking through the limitations of "single-device assessment" and preventing chain accidents from the overall perspective of the chemical system. It is particularly suitable for scenarios with dense equipment and complex processes in large-scale chemical plants, and enhances system-level safety protection capabilities.

[0025] This invention converts abstract management behaviors into calculable quantitative indicators such as personnel capability scores, maintenance change scores, and hidden danger rectification scores, directly links management levels with risks, provides users with feasible management optimization directions, and realizes the coordination of "technical prevention and control" and "management prevention and control", which can reduce the risks caused by human errors and management loopholes from the source.

[0026] In a second aspect, the present invention provides a risk warning system for chemical equipment, which is used to execute the risk warning method for chemical equipment described in any one of the first aspects above.

[0027] In a third aspect, the present invention provides an electronic device comprising: a memory, one or more processors; the memory and the processor are coupled; wherein computer program code is stored in the memory, and the computer program code includes computer instructions, and when the computer instructions are executed by the processor, the electronic device executes the risk warning method for chemical equipment described in any one of the above-mentioned first aspects.

[0028] In a fourth aspect, a computer-readable storage medium is provided, comprising computer instructions. When the computer instructions are executed on an electronic device, the electronic device executes the risk warning method for chemical equipment as described in any one of the first aspects above.

[0029] In a fifth aspect, a computer program product is provided. When the computer program product is run on a computer, the computer is caused to execute the risk warning method for chemical equipment described in any one of the first aspects above.

[0030] It can be understood that the beneficial effects that can be achieved by the risk warning system for chemical equipment in the second aspect provided above, the electronic device described in the third aspect, the computer-readable storage medium described in the fourth aspect, and the computer program product described in the fifth aspect can be referred to the beneficial effects in the first aspect and any possible design method thereof, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1A schematic diagram of a process for a risk warning method for chemical equipment provided in an embodiment of the present application; Figure 2 A schematic structural diagram of a risk warning system for chemical equipment provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] The following describes the technical solutions in the embodiments of the present application in conjunction with the accompanying drawings. In the description of this application, unless otherwise specified, " / " indicates that the objects associated with each other are in an "or" relationship. For example, A / B can mean A or B. "And / or" in this application is simply a description of the association relationship between associated objects, indicating that three relationships can exist. For example, "A and / or B" can mean: A alone, A and B together, or B alone. A and B can be singular or plural. Furthermore, in the description of this application, unless otherwise specified, "multiple" means two or more. "At least one of the following" or similar expressions refers 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 mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or plural. In addition, in order to facilitate the clear description of the technical solutions of the embodiments of the present application, in the embodiments of the present application, words such as "first" and "second" are used to distinguish between identical or similar items with substantially the same functions and effects. Those skilled in the art will understand that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit differences. At the same time, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or design schemes. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way for easy understanding.

[0033] In the chemical production sector, the safe operation of chemical equipment is crucial to ensuring production efficiency, personnel safety, and environmental security. Accurate risk warnings are a core component of equipment safety management. As chemical plants become increasingly complex and large-scale, the risks they face are becoming more diverse. Comprehensive, real-time assessments of equipment risks and early warnings of potential hazards have become pressing technical challenges for the industry.

[0034] Existing risk warning systems for chemical equipment primarily focus on the equipment's operating parameters. Sensors are deployed to collect data such as pressure, temperature, and vibration spectrum, and then used to identify anomalies based on preset safety limits. Some solutions also attempt to incorporate historical equipment failure data or simple environmental parameters (such as temperature and humidity) into risk assessments. These approaches, centered around the equipment's status, establish a foundational risk warning framework, enabling a certain degree of monitoring and alerting for equipment operating anomalies.

[0035] However, existing technologies have significant limitations: First, their assessment dimensions are limited, focusing solely on the equipment's status. They ignore the impact of corrosive gases in the environment, process connections with adjacent equipment, and risk transmission due to physical proximity. Management factors such as personnel qualifications, maintenance efficiency, and the effectiveness of hazard remediation are also not incorporated into the assessment system, making it difficult to fully reflect the equipment's true risk profile. Second, they employ a static assessment model with fixed weights and thresholds. This prevents them from dynamically adjusting the assessment logic based on equipment health, environmental changes, or management levels, resulting in insufficient adaptability to the risk characteristics of different equipment. Third, they lack quantitative modeling of risk transmission mechanisms between equipment, making it impossible to warn of potential chain reactions caused by a single equipment failure, limiting their ability to prevent and control risks in complex chemical systems. Fourth, the difficulty in quantifying management factors results in a lack of data linkage between risk assessment and management improvements, preventing a closed loop of "assessment-rectification-optimization." Therefore, a new approach that integrates multi-dimensional data, exhibits dynamic adaptability, and provides risk transmission and early warning capabilities is urgently needed to address the shortcomings of existing technologies and enhance the comprehensiveness, real-time nature, and systematic nature of chemical equipment risk early warning.

[0036] In view of the above problems, the present invention provides a risk warning method for chemical equipment. Figure 1 The present invention provides a risk warning method for chemical equipment, comprising the following steps S101-S104: S101: Determine the equipment score, environment score, and management score corresponding to the first chemical equipment.

[0037] The equipment score is determined based on the equipment information corresponding to the first chemical equipment, which includes equipment attribute data, operating status data, and historical fault data of the first chemical equipment.

[0038] The environmental score is determined based on the environmental information corresponding to the first chemical equipment. The environmental information includes the environmental data of the first chemical equipment and the correlation data between the first chemical equipment and the second chemical equipment. The second chemical equipment is connected to the first chemical equipment.

[0039] The management score is determined based on the management information corresponding to the first chemical equipment. This management information includes the personnel data of the target operator, 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 operator is the operator of the first chemical equipment.

[0040] In some embodiments, the equipment attribute data includes equipment type data of the first chemical equipment, equipment material data (eg, steel, iron, copper), equipment structure data (eg, equipment wall thickness), equipment usage date data, and equipment validity period data.

[0041] Since device attribute data is static attribute data, the device attribute data can be obtained based on a security control system or device management system that stores the device attribute data. Alternatively, the device attribute data can be obtained based on manual user input.

[0042] In some embodiments, the operating status data includes pressure, temperature, vibration spectrum of the first chemical equipment during operation, and safety limits of the monitoring equipment.

[0043] 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 obtained from the Supervisory Control and Data Acquisition (SCADA) system, distributed control system (DCS) system, and manufacturing execution system (MES) system associated with the first chemical equipment.

[0044] In some embodiments, the historical fault data includes the fault time, fault type, and fault risk level of the first chemical equipment.

[0045] The failure risk levels of the first chemical equipment may include Level 0, Level 1, Level 2, and Level 3. Failure types of the first chemical equipment may include tower failures (e.g., scaling and blockage within the tower, seal failure and leakage, and structural damage), tank failures (e.g., corrosion and leakage, overpressure and safety valve failure, and accessory failure), and pump failures (e.g., mechanical seal failure, bearing and shafting failure, cavitation, and abnormal flow). Furthermore, the failure types of the first chemical equipment may include more types of failures (e.g., loose connectors). This embodiment of the present application does not specifically limit the failure types of the first chemical equipment.

[0046] 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 by an IoT sensor or an 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 corrosive gas concentration in the environment in which the first chemical equipment is located.

[0047] In some embodiments, the association data between the first chemical equipment and the second chemical equipment includes a process association between the first chemical equipment and the second chemical equipment and a physical distance between the first chemical equipment and the second chemical equipment. The process association 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.

[0048] Illustratively, the process correlation between the first chemical equipment and the second chemical equipment=the number of connected 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.

[0049] In some embodiments, the personnel data includes the qualification level of the target operating personnel, the training completion rate within the target time period, and the operation success rate.

[0050] The training completion rate of the target operator within the target time period is determined based on the ratio of the number of training sessions completed by the target operator within the target time period to the number of required training sessions. The operation success rate of the target operator within the target time period is determined based on the ratio of the number of non-violation operations performed by the target operator on the first chemical equipment within the target time period to the total number of operations performed.

[0051] In some embodiments, the historical maintenance data includes the maintenance type and on-time maintenance rate for the first chemical equipment during a target time period. The spare parts inventory data includes the number of spare parts in inventory for the first chemical equipment. The equipment change record includes change data for the first chemical equipment during the target time period. The change data for the first chemical equipment includes location movement data, equipment parameter change data, and component replacement data for the first chemical equipment.

[0052] The on-time maintenance rate of the first chemical equipment within the target time period is determined based on the ratio of the number of maintenance delay days of the first chemical equipment within the target time period to the standard number of maintenance delay days.

[0053] For example, the on-time maintenance rate for the first chemical equipment within the target time period = 1 - (the number of maintenance delay days for the first chemical equipment within the target time period / the standard delay days).

[0054] In some embodiments, the historical hidden danger rectification data includes the number of hidden dangers, the level of hidden dangers, and the on-time rate of hidden danger rectification of the first chemical equipment within the target time period.

[0055] The on-time rate of hidden danger rectification for the first chemical equipment within the target time period is determined based on the ratio of the hidden danger rectification timeout period for the first chemical equipment within the target time period to the hidden danger rectification standard time for the first chemical equipment within the target time period.

[0056] For example, the on-time rate of hidden danger rectification for the first chemical equipment within the target time period = 1-(the timeout for hidden danger rectification for the first chemical equipment within the target time period / the standard time for hidden danger rectification for the first chemical equipment within the target time period).

[0057] In some embodiments, the historical inspection data includes the actual number of inspections, the expected number of inspections, the number of handled anomalies, and the total number of discovered anomalies for the first chemical equipment within the target time period.

[0058] Among them, "abnormalities" may include abnormalities in the equipment itself, abnormalities in operating parameters, abnormalities in environmental risks, abnormalities in management processes, abnormalities in safety protection, abnormalities in process-related issues, etc. Abnormalities in the equipment itself refer to defects in the physical structure or materials of the equipment, which directly affect the safe operation of the equipment. Abnormalities in operating parameters refer to the deviation of key parameters from safety limits during the operation of the equipment, triggering risk warnings. Abnormalities in environmental risks refer to external risks caused by the environment in which the equipment is located or related equipment. Abnormalities in management processes refer to loopholes in personnel operations or management links, which lead to the failure of risk prevention and control. Abnormalities in safety protection refer to the failure of equipment safety accessories or monitoring systems, resulting in uncontrollable risks. Abnormalities in process-related issues refer to the deviation of production processes or process parameters from design standards, causing systemic risks.

[0059] In some embodiments, a basic health of the first chemical equipment is determined based on equipment attribute data and historical fault data corresponding to the first chemical equipment. A dynamic abnormality coefficient of the first chemical equipment is determined based on operating status data corresponding to the first chemical equipment. An equipment score corresponding to the first chemical equipment is determined based on the basic health of the first chemical equipment, the dynamic abnormality coefficient, and the dynamic abnormality weight.

[0060] The dynamic anomaly coefficients include the pressure anomaly coefficient, the temperature anomaly coefficient, and the vibration spectrum anomaly coefficient. 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 of the first chemical equipment can be generated based on the equipment's knowledge graph, calculated using a weighted three-dimensional feature vector based on material properties, structural parameters, and historical failure data.

[0061] In some embodiments, when the alignment value corresponding to the operating parameter of the first chemical equipment is greater than or equal to the lower limit value and less than or equal to the upper limit value, the dynamic abnormality coefficient corresponding to the operating parameter of the first chemical equipment can be determined to be 0.

[0062] The operating parameter of the first chemical equipment is any one of pressure, temperature, and vibration spectrum during 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.

[0063] 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 abnormality 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 corresponding to the operating parameter of the first chemical equipment.

[0064] 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 abnormality 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 corresponding to the operating parameter of the first chemical equipment.

[0065] For example, the equipment score H_phy corresponding to the first chemical equipment can be expressed as: 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; 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 parameter 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 preset lower limit value are static properties of the first chemical equipment.

[0066] In some embodiments, the alignment value corresponding to the operating parameter of the first chemical equipment is determined based on the values ​​of the operating parameter of the first chemical equipment at a first moment and a second moment, respectively. The first moment is a sampling moment before the target sampling moment, and the second moment is a sampling moment after the target sampling moment. The difference between the first moment and the target sampling moment is the same as the difference between the second moment and the target sampling moment.

[0067] For example, the alignment value Q corresponding to the operating parameter of the first chemical equipment can be expressed as: Q=Q1×(1-Δt / τ)+Q2×(Δt / τ); Where Q1 represents the value of the operating parameter of the first chemical equipment at the first moment, Q2 represents the value of the operating parameter of the first chemical equipment at the second moment, and Δt represents the difference between the first moment and the target sampling moment. τ is the dynamic interpolation weight, which represents the length of the smoothing window of the interpolation algorithm when the operating parameters of the first chemical equipment change slowly. It directly affects the smoothness of the data alignment and the ability to retain sudden changes. When the operating parameters of the first chemical equipment fluctuate drastically, the interpolation window needs to be shortened to retain sudden changes. Therefore, the dynamic interpolation weight method is adopted. The dynamic interpolation weight calculation formula is as follows: τ=τ_base / (1+|Δx / Δt| / x_range); Where τ_base is the baseline value for the dynamic interpolation weight (for example, 30 seconds); Δx = Q2 - Q1; and x_range represents the range of the monitoring device (described above). The range of a monitoring device is a unique attribute of the device. For example, if a household thermometer has a range of 35-42°C, then x_range = 7. The formula shows that a larger Δx / Δt indicates a smaller τ.

[0068] In some embodiments, an environmental risk value for the environment in which the first chemical equipment is located is determined based on environmental data corresponding to the first chemical equipment. A risk transmission value for the second chemical equipment is determined based on correlation data between the first and second chemical equipment and the health score of the second chemical equipment. An environmental score corresponding to the first chemical equipment is determined based on the environmental risk value for 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 equipment score weight, environmental score weight, and management score weight.

[0069] For example, the environmental score H_env corresponding to the first chemical equipment can be expressed as: 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; Here, σ(x) is a sigmoid function that maps 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 resides. This value can be calculated through linear normalization based on the corrosive gas concentration, ambient temperature, and humidity. b represents an offset, derived from a combination of historical incidents and feedback learning. Typically, b = -0.5 (to balance the sensitivity of risk transmission) is used. This offset is dynamically adjusted based on actual and predicted risks. E_neighbor represents the risk transmission value of the second chemical equipment. ρ_ij represents the strength of the association between the first and second chemical equipment. This is determined by multiplying the process correlation between the first and second chemical equipment by the physical distance between them. D_j represents the risk value of the second chemical equipment, and H_j represents the health score of the second chemical equipment.

[0070] In some embodiments, a personnel capability score corresponding to the first chemical equipment is determined based on the qualification level of the target operator, the training completion rate, and the operation success rate within the target time period. A maintenance change score corresponding to the first chemical equipment is determined based on the maintenance type and maintenance on-time rate for the first chemical equipment within the target time period, as well as the spare parts inventory adequacy rate and equipment change records for the first chemical equipment. A hidden danger rectification score corresponding to the first chemical equipment is determined based on the number of hidden dangers, hidden danger levels, and hidden danger rectification on-time rate for the first chemical equipment within the target time period. An inspection score corresponding to the first chemical equipment is determined based on the inspection attendance rate and exception handling rate for the first chemical equipment within the target time period. A management score corresponding to the first chemical equipment is determined based on the personnel capability score, maintenance 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 change management weight corresponding to the maintenance 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.

[0071] The spare parts inventory adequacy ratio for the first chemical equipment is determined based on the number of spare parts in inventory corresponding to the first chemical equipment. The inspection attendance rate is determined based on the actual and expected number of inspections for the first chemical equipment within the target time period. The exception handling rate is determined based on the number of handled exceptions and the total number of discovered exceptions for the first chemical equipment within the target time period.

[0072] For example, the management score H_mgmt corresponding to the first chemical equipment can be expressed as: H_mgmt=∏(1-μ_i·f_i); Here, μ_i represents the weight of the corresponding management dimension (e.g., personnel capability management weight, maintenance change management weight, hidden danger rectification management weight, and inspection management weight). This can be determined using the Analytic Network Hierarchy Process (AHP). For example, the personnel capability management weight can be set to 0.2, the maintenance change management weight to 0.3, the hidden danger rectification management weight to 0.3, and the inspection management weight to 0.1. f_i represents the risk affiliation of the corresponding management dimension, where f_i = 1 minus the risk score of the corresponding management dimension (e.g., personnel capability score, maintenance change score, hidden danger rectification score, and inspection score).

[0073] S102: Determine a health score of the first chemical equipment based on the equipment score, environment score, management score, and equipment score weight, environment score weight, and management score weight corresponding to the first chemical equipment.

[0074] Among them, the equipment score weight, environmental score weight and management score weight are all determined based on the equipment score, environmental score and management score corresponding to the first chemical equipment.

[0075] For example, the health score H of the first chemical equipment can be expressed as: H=α·H_phy+β·H_env+γ·H_mgmt.

[0076] Among them, α represents the equipment score weight, β represents the environment score weight, and γ represents the management score weight.

[0077] In some embodiments, the device scoring weight is determined based on the first preset relationship.

[0078] The first preset relationship includes: α=(1-H_phy) / D; Where D = max ((3-(H_phy+H_env+H_mgmt)), 0.1). H_phy represents the equipment score, H_env represents the environment score, and H_mgmt represents the management score.

[0079] In some embodiments, the environment score weight is determined based on the second preset relationship.

[0080] The second preset relationship includes: β=(1-H_env) / D.

[0081] In some embodiments, the management score weight is determined based on a third preset relationship.

[0082] The third preset relationship includes: γ=(1-H_mgmt) / D.

[0083] S103: Determine the risk level of the first chemical equipment based on the health score of the first chemical equipment.

[0084] Among them, the higher the health score of the first chemical equipment, the smaller the risk corresponding to the risk level of the first chemical equipment.

[0085] For example, the risk level of the first chemical equipment may include level 1 (low), level 2 (intermediate), level 3 (higher), and level 4 (higher). 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 the health score of the first chemical equipment falls. The corresponding relationship between the health score of the first chemical equipment and the risk level of the first chemical equipment can be shown in Table 1 below.

[0086]

[0087] S104: Based on the risk level of the first chemical equipment, early warning information for characterizing the risk level of the first chemical equipment is prompted.

[0088] In some embodiments, based on the risk level of the first chemical equipment, a decision corresponding to the risk level of the first chemical equipment is executed.

[0089] For example, when it is determined that the risk level of the first chemical equipment is level one, a decision may be made for the first chemical equipment: observe operation and maintain a regular inspection cycle.

[0090] If the risk level of the first chemical equipment is determined to be level two, a decision can be made for the first chemical equipment: strengthen inspections. Based on the weights of the various contributing factors in the health score, inspection recommendations are given for the equipment itself or surrounding related equipment. For example, if the pressure of tank C101 associated with this equipment is too high, resulting in excessive bearing pressure, please reduce the pressure of tank C101 in a timely manner and increase the equipment inspection cycle from the current once / day to three times / day.

[0091] If the risk level of the first chemical equipment is determined to be level three, the decision can be made for the first chemical equipment: maintenance within 48 hours + regional isolation. Based on the weight of each contributing factor in the health score, specific maintenance suggestions for the equipment itself or peripheral equipment are given, such as: the equipment shell is severely corroded, please take measures to replace the shell as soon as possible.

[0092] When it is determined that the risk level of the first chemical equipment is level four, a decision can be made on the first chemical equipment: emergency shutdown, immediate isolation of the equipment and activation of the emergency plan.

[0093] In some embodiments, the present invention can establish a closed-loop data feedback loop by comparing method decisions with actual manual operations in real time. When a deviation is detected between the manual response and the original decision (e.g., a worker shortening the seal inspection cycle from the recommended 7 days to 3 days), the system automatically records the operational parameters and result data. An optimization algorithm calculates the discrepancy rate and dynamically adjusts the health score weighting (e.g., increasing the weight of management actions by 1.57 times). This mechanism employs a two-way learning logic: if manual operation yields superior results, the model is optimized based on this experience; if deviations result in losses (e.g., failure to replace a bearing in a timely manner leads to an escalation of a fault), the warning rules are modified in reverse. This achieves a self-evolving capability that becomes increasingly accurate with use.

[0094] This paper leverages 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 the health scores of equipment, breaking through 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, full-link link from "equipment status monitoring" to "assisted decision-making and disposal."

[0095] Furthermore, this invention builds a two-way learning engine combining "operation feedback and model optimization" to overcome the rigid decision-making issues of traditional systems. By comparing system recommendations with manual actions (such as adjusting inspection cycles and spare parts replacement strategies) in real time, it dynamically calculates the discrepancy rate and feeds back to the model. When manual actions are superior, the management action weight is automatically increased; when execution deviations lead to losses, the warning threshold is adjusted accordingly. This creates a unique advantage: "It becomes smarter with use."

[0096] The present invention also provides a risk warning system for chemical equipment, see Figure 2 The present invention provides a risk warning system for chemical equipment, which includes: a sub-score determination module, a total score determination module, a risk level determination module and a warning module.

[0097] The sub-score 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 the equipment score, environmental score, and management score, as well as the equipment score weight, environmental score weight, and management score weight. The risk level determination module is used to determine the risk level of the first chemical equipment based on the health score of the first chemical equipment. The early warning module is used to generate early warning information indicating the risk level of the first chemical equipment based on the risk level of the first chemical equipment.

[0098] In some schemes, multiple embodiments of the present application can be combined and the combined scheme can be implemented. Optionally, some operations in the process of each method embodiment are optionally combined, and / or the order of some operations is optionally changed. In addition, the execution order between the steps of each process is only exemplary and does not constitute a limitation on the execution order between the steps. There can also be other execution orders between the steps. It is not intended to indicate that the execution order is the only order in which these operations can be performed. Ordinary technicians in this field will think of many ways to reorder the operations described herein. In addition, it should be noted that the process details involved in a certain embodiment of this article are also applicable to other embodiments in a similar manner, or different embodiments can be used in combination.

[0099] Furthermore, some steps in the method embodiments may be equivalently replaced with other possible steps. Alternatively, some steps in the method embodiments may be optional and may be deleted in certain usage scenarios. Alternatively, other possible steps may be added to the method embodiments. Furthermore, the various method embodiments may be implemented separately or in combination.

[0100] Through the description of the above implementation methods, technical personnel in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned 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.

[0101] 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 schematic. For example, the division of the modules or units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or units, which can be electrical, mechanical or other forms.

[0102] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0103] If the integrated unit is implemented in the form of 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 embodiment of the present application, or the part that makes the contribution, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a device (which can be a single-chip microcomputer, chip, etc.) or a processor to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program code.

[0104] The above content is only a specific embodiment of this application, but the scope of protection of this application is not limited to this. Any changes or replacements within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection 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; and 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 first chemical equipment, 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 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 operator is the operator of the first chemical equipment; Determining a health score of the first chemical equipment based on the equipment score, environment score, and management score corresponding to the first chemical equipment, as well as the equipment score weight, environment score weight, and management score weight; the equipment score weight, the environment score weight, and the management score weight are all determined based on the equipment score, environment score, and management score corresponding to the first chemical equipment; determining a risk level of the first chemical equipment based on the health score of the first chemical equipment; Based on the risk level of the first chemical equipment, early warning information representing the risk level of the first chemical equipment is prompted.

2. The method according to claim 1, characterized in that The equipment attribute data includes the 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 limit 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 risk 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 operating personnel, the training completion rate and the operation success rate within the target time period; the historical maintenance data includes the maintenance type and maintenance punctuality rate for the first chemical equipment within the target time period; the spare parts inventory data includes the number of spare parts of the first chemical equipment in inventory, and the equipment change record includes the change data of the first chemical equipment within the target time period; the change data of the first chemical equipment includes the location movement data, equipment parameter change data, and accessories replacement data of the first chemical equipment; the historical hidden danger rectification data includes the number of hidden dangers of the first chemical equipment within the target time period, the hidden danger level and the hidden danger rectification punctuality rate; the historical inspection data includes the actual number of inspections, the expected number of inspections, the number of handled anomalies and the total number of discovered anomalies for the first chemical equipment within the target time period.

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

6. The method according to claim 5, characterized in that The safety limit of the monitoring equipment includes an upper limit and a lower limit; and determining the dynamic abnormality coefficient of the first chemical equipment based on the operating status data corresponding to the first chemical equipment includes: When the alignment value corresponding to the operating parameter of the first chemical equipment is greater than or equal to the lower limit value and less than or equal to the upper limit value, 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 of the first chemical equipment during operation; 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; When the alignment value corresponding to the operating parameter of the first chemical equipment is greater than the upper limit value, determining a value of a dynamic abnormality coefficient corresponding to the operating parameter of the first chemical equipment based on the alignment value corresponding to the operating parameter of the first chemical equipment, the upper limit value, and a preset upper threshold value; 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 abnormality 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 lower limit value and the preset threshold lower limit.

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

8. The method according to claim 7, characterized in that Determining the management score corresponding to the first chemical equipment includes: Determining a personnel capability score corresponding to the first chemical equipment based on the qualification level of the target operator, the training completion rate and the operation success rate within the target time period; determining a maintenance change score corresponding to the first chemical equipment based on the maintenance type and maintenance on-time rate of 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 spare parts inventory adequacy rate of the first chemical equipment is determined based on the number of spare parts in inventory corresponding to the first chemical equipment; Determining a hidden danger rectification score corresponding to the first chemical equipment based on the number of hidden dangers, the hidden danger level, and the hidden danger rectification on-time rate of the first chemical equipment within the target time period; determining an inspection score corresponding to the first chemical equipment based on an inspection completion rate and an exception handling rate of the first chemical equipment within the target time period; the inspection completion rate is determined based on an actual number of inspections and an expected number of inspections for the first chemical equipment within the target time period; and the exception handling rate is determined based on a number of handled exceptions and a total number of discovered exceptions for the first chemical equipment within the target time period; Based on the personnel capability score, maintenance 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 change management weight corresponding to the maintenance 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: Determining the device scoring weight based on a first preset relationship; the first preset relationship includes α=(1-H_phy) / D; Determining the environmental scoring weight based on a second preset relationship; the second preset relationship includes β=(1-H_env) / D; Determining the management score weight based on a third preset relationship; the third preset relationship includes γ=(1-H_mgmt) / D; Wherein, D=max((3-(H_phy+H_env+H_mgmt)),0.1); α represents the device score weight, β represents the environment score weight, and γ represents the management score weight; H_phy represents the device score, H_env represents the environment 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 the health score of the first chemical equipment, 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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