Earthquake emergency handling system for automatic production line

Abstract

The invention provides an automatic production line earthquake emergency disposal system, and relates to the technical field of data processing, and the system comprises an earthquake monitoring module which is used for obtaining earthquake waveform data, earthquake magnitude information and epicenter position data; the production process state acquisition module is used for acquiring the process type, the equipment operation state and the vibration tolerance parameter of each production process; the earthquake influence analysis module is used for calculating expected vibration amplitudes, equipment damage risk degrees and accumulated vibration influences of different production processes; the grading disposal strategy generation module is used for determining risk grades of different production processes and generating emergency disposal instructions including an immediate shutdown instruction of a low-vibration-tolerance process, a continuous monitoring instruction of a high-vibration-tolerance process and a safety recovery scheme for the different production processes; and the control execution module is used for receiving the grading emergency disposal strategy and executing corresponding emergency disposal operation. According to the invention, the autonomy and accuracy of the emergency disposal system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, in particular to an earthquake emergency disposal system for an automated production line. Background Art

[0002] During the operation of an automated production line, sudden disasters such as earthquakes may have a serious impact on equipment, products, and personnel safety. In the prior art, earthquake emergency disposal is usually carried out by combining an earthquake monitoring system with an automated control system. A common method is to use earthquake sensors to collect seismic wave data in real time, and judge the earthquake magnitude through a threshold. If the earthquake magnitude reaches a preset standard, the emergency shutdown mechanism of the automated production line is triggered. In addition, the earthquake early warning information can be transmitted to the production management system through a wireless communication network, and then the power-off of the production line, the recovery of the robotic arm, the activation of the safety protection device, etc. can be controlled to ensure the safety of production equipment and personnel.

[0003] However, in practical applications, the prior art may have problems with inaccurate responses when facing earthquake emergency disposal. Especially in industrial parks with a large earthquake impact range, it may lead to mismatched disposal decisions for different production processes, affecting overall safety. For example, in an automated factory with multiple production lines running in parallel, different production processes may share the same set of earthquake detection systems. If the system only makes a unified response based on a single earthquake intensity threshold without considering the equipment types, operating states, and vibration tolerances of each production process, it may cause some production processes to stop prematurely during minor vibrations, affecting production continuity, while other key production processes fail to stop in time, increasing equipment damage and safety hazards. Summary of the Invention

[0004] The purpose of the present invention is to provide an earthquake emergency disposal system for an automated production line, aiming to solve the problems mentioned in the background art.

[0005] To solve the above technical problems, the technical solution of the present invention is as follows:

[0006] An earthquake emergency disposal system for an automated production line, the system includes:

[0007] A production process status acquisition module, used to collect the process type, equipment operating status, and its vibration tolerance parameters of each production process, and generate operation status data;

[0008] An earthquake impact analysis module, used to calculate the expected vibration amplitude, equipment damage risk degree, and cumulative vibration impact of different production processes according to earthquake data and operation status data, and obtain process impact analysis data;

[0009] The hierarchical disposal strategy generation module is used to determine the risk levels of different production processes based on the process impact analysis data, and generate emergency disposal instructions for production processes with different risk levels, including an immediate shutdown instruction for low vibration tolerance processes, a continuous monitoring instruction for high vibration tolerance processes, and a safety recovery plan for different production processes;

[0010] The control execution module is used to receive the hierarchical emergency disposal strategy and execute the corresponding emergency disposal operations.

[0011] Preferably, the production process status acquisition module includes:

[0012] The process type identification sub-module is used to obtain the process stages, processing methods, and key equipment categories of each production process to form process type data;

[0013] The equipment status monitoring sub-module is used to monitor the operating mode, load level, and real-time power consumption of the equipment in each production process according to the process type information, and generate equipment operation status data;

[0014] The vibration tolerance calculation sub-module is used to calculate the vibration trigger threshold and vibration cumulative tolerance of the equipment according to the equipment operation status data, combined with the equipment structure parameters and historical vibration response data, and generate vibration tolerance parameters.

[0015] Preferably, the earthquake impact analysis module includes:

[0016] The vibration amplitude calculation sub-module is used to calculate the expected vibration amplitude of each production process according to the earthquake data, combined with the geographical location coordinates, equipment installation height, and ground vibration amplification effect parameters of each production process;

[0017] The equipment damage risk assessment sub-module is used to calculate the vibration stress distribution of each equipment according to the vibration data, combined with the equipment structure characteristics, vibration tolerance parameters, and historical damage data of each production process, and predict the degree of equipment damage risk;

[0018] The cumulative vibration effect calculation sub-module is used to analyze the cumulative vibration impact of the earthquake on the production process according to the vibration data, expected vibration amplitude, and equipment damage risk degree.

[0019] Preferably, the hierarchical disposal strategy generation module includes:

[0020] The risk level determination sub-module is used to evaluate the risk levels of each production process according to the process impact analysis data;

[0021] The shutdown decision sub-module is used to generate an immediate shutdown instruction for low vibration tolerance processes according to the risk level, and set a shutdown buffer time in combination with the production task priority;

[0022] The monitoring and regulation sub-module is used to generate continuous monitoring instructions for high-vibration tolerance processes according to the risk level, and conduct real-time trend analysis on vibration data. If a secondary vibration amplification effect is detected, the monitoring frequency is dynamically adjusted.

[0023] The recovery plan formulation sub-module is used to generate a safe production recovery plan according to the risk level and process impact analysis data.

[0024] Preferably, the vibration tolerance calculation sub-module includes:

[0025] The structural response modeling unit is used to extract the structural characteristic parameters of the equipment according to the equipment operation status data, and establish an equipment structural response model based on the equipment installation method, support structure type, and mass distribution.

[0026] The dynamic threshold generation unit is used to fit the structural response model with the historical vibration response data, calculate the preliminary trigger threshold corresponding to each equipment according to the fitting result, and dynamically adjust the preliminary trigger threshold according to the current state of the equipment to obtain the vibration trigger threshold.

[0027] The vibration adaptability evaluation unit is used to calculate the cumulative vibration tolerance of the equipment according to the vibration trigger threshold and the vibration stability index of the equipment, and generate vibration tolerance parameters.

[0028] Preferably, the cumulative vibration effect calculation sub-module includes:

[0029] The time-weighted integration unit is used to perform time-series segmentation processing on the vibration data, introduce a time decay factor, and perform weighted integration on the vibration intensities at different times to generate a vibration cumulative impact value.

[0030] The fatigue trend analysis unit is used to compare the vibration cumulative impact value with the vibration tolerance parameters of each equipment, and predict the structural fatigue trend of the equipment due to continuous vibration based on the equipment service life model.

[0031] The damage potential discrimination unit is used to determine whether the current equipment is in the safe operation area, warning area, or risk area according to the structural fatigue trend, combined with the preset fatigue threshold range, and generate the cumulative vibration impact result.

[0032] Preferably, the risk level determination sub-module includes:

[0033] The multi-parameter fusion unit is used to extract the expected vibration amplitude, equipment damage risk degree, and cumulative vibration impact according to the process impact analysis data, and calculate the comprehensive risk score according to the preset weight factor.

[0034] A fuzzy rule matching unit, which is used to input the comprehensive risk score into a fuzzy rule system, and infer the fuzzy risk levels of each production process according to preset fuzzy membership functions and risk judgment rules;

[0035] A risk level mapping unit, which is used to output clear risk level labels according to the defuzzification criteria corresponding to the fuzzy risk levels.

[0036] Preferably, the structural response modeling unit includes:

[0037] A structural parameter extraction sub-unit, which is used to extract the installation method of the equipment, the configuration of the connecting brackets, the type of component materials, and the mass distribution information according to the equipment operation status data, and form the basic structural parameters;

[0038] A modeling template selection sub-unit, which is used to select a matching template from a preset multi-type equipment structure modeling templates according to the basic structural parameters, and the matching templates include a rigid structure model, a hierarchical structure model, and a flexible connection model;

[0039] A response model construction sub-unit, which is used to map the basic structural parameters into the matching template to construct an equipment structure response model including multi-degree-of-freedom vibration characteristics.

[0040] Preferably, the dynamic threshold generation unit includes:

[0041] A state factor matching sub-unit, which is used to construct a corresponding state factor vector based on the current operation mode, load level, and historical anomaly records of the equipment;

[0042] An empirical model fitting sub-unit, which is used to perform regression fitting on the state factor vector and historical vibration response data to establish a dynamic fitting function for the preliminary vibration trigger threshold;

[0043] A threshold adaptive adjustment sub-unit, which is used to real-time correct the preliminary vibration trigger threshold according to the output result of the dynamic fitting function, the current state of the equipment, and the feedback result of the equipment structure response model, and generate the vibration trigger threshold corresponding to the equipment.

[0044] The above solution of the present invention has at least the following beneficial effects:

[0045] The earthquake emergency disposal system for the automated production line of the present invention can achieve refined vibration response for different production processes and equipment by closely integrating earthquake monitoring, production process status collection, earthquake impact analysis, and hierarchical disposal strategy generation modules. Compared with the prior art, this system generates personalized disposal plans by dynamically evaluating the vibration tolerance and risk levels of each production process, greatly improving the accuracy and reliability of earthquake emergency disposal.

[0046] The prior art usually relies on a single seismic intensity threshold for unified response, resulting in inaccurate responses due to the failure to consider the differences in production processes. Especially in large-scale industrial parks or environments where multiple production lines operate in coordination, it may occur that slight vibrations cause some processes to shut down prematurely, or that the system fails to shut down in time when the vibrations intensify during critical processes. This approach not only affects production efficiency but also increases the risk of equipment damage. In contrast, the present invention collects in detail information such as the process parameters, equipment operation status, and vibration tolerance of each process, ensuring that the most appropriate emergency response can be made according to the actual situation of each process during an earthquake, avoiding unnecessary production interruptions, and providing timely protection in case of possible equipment damage.

[0047] Specifically, the present invention obtains real-time seismic waveform data, magnitude information, and epicenter location data through a seismic monitoring module. On this basis, by combining various process operation data provided by the production process status acquisition module, the vibration amplitude, equipment damage risk level, and cumulative vibration impact of each process are calculated, and further process impact analysis data is generated. The hierarchical disposal strategy generation module generates risk levels based on this data and generates targeted emergency disposal instructions in combination with the vibration tolerance parameters of processes with different risk levels. For processes with low vibration tolerance, the system can generate shutdown instructions in time to avoid damage to the equipment caused by excessive vibration; for processes with high vibration tolerance, the system generates continuous monitoring instructions to ensure that the vibration impact is tracked in real time and the monitoring frequency can be adjusted at any time or emergency measures can be taken when the vibration intensifies.

[0048] Through this personalized disposal strategy based on the characteristics of production processes and vibration tolerance, the present invention can improve the safety and stability of automated production lines. Especially in the precision manufacturing industry, such as high-value and high-precision manufacturing environments like semiconductor production lines, the present invention can ensure that critical processes are protected in time during an earthquake, avoiding equipment damage and production stagnation problems caused by excessive or too little vibration, reducing the risks of equipment damage, production line shutdown, and personnel casualties, and ensuring the continuity and safety of production.

[0049] In addition, the present invention combines dynamic threshold adjustment and fuzzy logic reasoning, and can adjust the vibration trigger threshold in real time according to the current state of the equipment, historical vibration responses, and changes in the seismic environment, providing a more flexible and accurate emergency response for production processes. This dynamic adjustment mechanism effectively solves the problems of slow response and poor adaptability of traditional static threshold systems under sudden vibration conditions, and further improves the intelligent level and practical application value of the system.

[0050] In summary, through refined earthquake response strategies and a flexible risk level determination mechanism, the present invention effectively improves the earthquake resistance of the automated production line, enabling the system to respond quickly and accurately during earthquake disasters, ensuring the safety of production equipment and personnel, and maximizing the continuous and stable operation of the production line. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 is an architecture diagram of the earthquake emergency disposal system for an automated production line provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0052] Hereinafter, exemplary embodiments of the present disclosure will be described in more detail with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be fully conveyed to those skilled in the art.

[0053] As Figure 1 shown, an embodiment of the present invention proposes an earthquake emergency disposal system for an automated production line, and the system includes:

[0054] An earthquake monitoring module, configured to obtain earthquake waveform data, magnitude information, and epicenter position data, and form earthquake data;

[0055] A production process status acquisition module, configured to collect the process type, equipment operation status, and vibration tolerance parameters of each production process, and generate operation status data;

[0056] An earthquake impact analysis module, configured to calculate the expected vibration amplitude, equipment damage risk degree, and cumulative vibration impact of different production processes according to the earthquake data and the operation status data, and obtain process impact analysis data;

[0057] A hierarchical disposal strategy generation module, configured to determine the risk levels of different production processes according to the process impact analysis data, and generate emergency disposal instructions for production processes with different risk levels, including an immediate shutdown instruction for processes with low vibration tolerance, a continuous monitoring instruction for processes with high vibration tolerance, and a safety recovery plan for different production processes;

[0058] A control execution module, configured to receive the hierarchical emergency disposal strategy and execute corresponding emergency disposal operations.

[0059] In the embodiments of the present invention, through the collaborative action of each module, the system can work efficiently from the acquisition of seismic data, the monitoring of the status of production processes, the analysis of the impact of vibrations on equipment, to the assessment of risk levels and the generation of emergency response strategies, ensuring that the system can respond quickly during an earthquake and reduce the risks of the production line.

[0060] First, the system obtains seismic waveform data, magnitude information, and epicenter location data through the seismic monitoring module, and then forms seismic data. Through this module, the system can understand the occurrence and intensity of earthquakes in real time, obtain the specific location and fluctuation conditions of the seismic source, and accurately judge the impact range of vibrations. These data provide basic information for subsequent analysis, ensuring that other modules can make scientific and reasonable decisions in real earthquake scenarios.

[0061] Immediately afterwards, the production process status acquisition module generates operation status data by monitoring information such as the process stage, processing method, and key equipment category of each production process, and combining factors such as the equipment operation status, load level, and real-time power consumption. This module not only provides equipment operation information during the production process, but also provides a basis for evaluating the impact of vibrations on equipment through these data. Especially during an earthquake, the system can accurately obtain the working status and vibration tolerance parameters of the equipment, thereby judging the potential risks of the equipment during the earthquake.

[0062] The earthquake impact analysis module combines the seismic data with the operation status data of the production process to calculate the expected vibration amplitude, equipment damage risk level, and cumulative vibration impact of different production processes. This module can not only predict the vibration amplitude caused by an earthquake, but also comprehensively consider the historical vibration response data, vibration tolerance of the equipment, and the current operation status of the equipment to calculate the potential risk level of the equipment. Through this accurate risk prediction, equipment damage and production interruption caused by vibrations can be effectively avoided.

[0063] Finally, the hierarchical disposal strategy generation module generates emergency disposal instructions for production processes with different risk levels based on the process impact analysis data. For processes with low vibration tolerance, the system will automatically generate an immediate shutdown instruction to prevent the equipment from suffering irreparable damage due to excessive vibrations; for processes with high vibration tolerance, the system generates a continuous monitoring instruction to track the vibration impact in real time and respond to the situation of increasing vibrations. In addition, the system can also generate corresponding safety restoration plans based on the risk level of the process and the impact analysis data to ensure the smooth progress of production restoration.

[0064] Through the highly collaborative work of each module, this system can achieve automated and intelligent earthquake emergency response, ensuring the safety and efficiency of production. Compared with traditional manual intervention methods, this system has obvious advantages: First, when an earthquake occurs, the system can process data in real time and make decisions immediately, greatly reducing the production downtime; Second, the system has strong prediction ability and can formulate corresponding strategies according to the earthquake intensity and the seismic resistance of equipment, improving the service life of equipment and reducing maintenance costs; Finally, the hierarchical disposal strategy generation module can generate personalized disposal plans for different production processes and equipment, thus significantly improving the risk resistance ability of the entire production line during earthquake disasters.

[0065] Therefore, this system not only improves production safety and stability, but also optimizes the emergency management of the production process, saving a large amount of costs and time for enterprises and having broad application prospects.

[0066] Among them, the earthquake monitoring module is one of the basic components of the system. Its main function is to monitor and collect earthquake-related data in real time, providing data support for subsequent earthquake impact analysis, equipment risk assessment and emergency disposal strategy generation. By deploying earthquake sensors and other monitoring devices, this module can accurately capture earthquake waveform data, magnitude information and epicenter location data, and converge this information into the central processing system for further analysis.

[0067] Specifically, the earthquake monitoring module usually consists of the following key parts:

[0068] Earthquake waveform data acquisition unit: This unit real-time collects the time series data of earthquake waves through earthquake sensors installed at different geographical locations. These data reflect the vibration amplitude of earthquake waves in different frequency bands, providing the original waveform data for subsequent vibration impact analysis.

[0069] Epicenter location and magnitude calculation unit: This part is responsible for determining the exact location of the epicenter through triangulation or other positioning algorithms based on the signal data received by the earthquake sensors. At the same time, it calculates the magnitude using the intensity and frequency data of earthquake waves to evaluate the severity of the earthquake. Magnitude calculation usually uses common calculation methods such as the standard Richter epicenter magnitude or surface wave magnitude.

[0070] Data transmission and synchronization unit: The earthquake monitoring module is also equipped with a real-time data transmission unit, which transmits the collected earthquake data to the central processing unit of the system through a wireless communication network (such as Wi-Fi, 4G, 5G or a dedicated communication link). This process ensures the real-time nature of earthquake data and can be synchronized to various monitoring systems and emergency response mechanisms.

[0071] Through this module, the system can quickly obtain and transmit relevant data during an earthquake, providing key earthquake early warning information, greatly enhancing the system's ability to respond to sudden earthquake events, and reducing equipment damage and production interruptions caused by response delays.

[0072] In a preferred embodiment of the present invention, the production process status acquisition module includes:

[0073] A process type identification sub-module for obtaining the process stage, processing method, and key equipment category of each production process to form process type data;

[0074] An equipment status monitoring sub-module for monitoring the operating mode, load level, and real-time power consumption of equipment in each production process according to the process type information, and generating equipment operation status data;

[0075] A vibration tolerance calculation sub-module for calculating the vibration trigger threshold and vibration cumulative tolerance of the equipment based on the equipment operation status data, combined with the equipment structure parameters and historical vibration response data, and generating vibration tolerance parameters.

[0076] In the embodiment of the present invention, this module provides key input data for subsequent earthquake impact analysis, equipment damage risk assessment, and hierarchical disposal strategy generation by real-time monitoring and collecting various data of the production process.

[0077] In the process type identification sub-module, by collecting the process stage, processing method, and key equipment category of each production process, the system can comprehensively understand the characteristics of different processes and their vibration tolerance requirements. Through the work of this module, the system can clearly judge the specific requirements of each process and provide background information for equipment monitoring and vibration analysis. According to the different process stages, the system can further subdivide various production processes and clarify the types of risks that each process may face during an earthquake.

[0078] The equipment status monitoring sub-module monitors data such as the operating mode, load level, and real-time power consumption of equipment in each production process through further analysis of the process type information. This module can grasp the status of the equipment during operation in real time, understand the load situation, operating power, and health status of the equipment, and thus provide data support for subsequent vibration tolerance analysis. During an earthquake, the equipment status monitoring module can timely transmit the real-time operating status of the equipment and provide accurate data support for the risk assessment module to ensure the efficiency and accuracy of the risk assessment process.

[0079] The vibration tolerance calculation sub-module combines the device operation status data, device structure parameters, and historical vibration response data to calculate the vibration trigger threshold and vibration cumulative tolerance of the device, and generate vibration tolerance parameters. Through this module, the system can evaluate the specific tolerance of the device during vibration, predict the possible damage risk of the device, and provide specific data for the earthquake impact analysis module. By accurately calculating the vibration trigger threshold, the vibration tolerance calculation module can help the system determine which devices may be affected during an earthquake and formulate corresponding preventive measures in advance.

[0080] The collaborative work of this module lays the foundation for the efficient operation of the entire earthquake emergency response system. By accurately collecting and monitoring various data of the production process, the production process status collection module can provide necessary real-time data support for the system, ensuring that the system can obtain key information and respond immediately when an earthquake occurs, thus avoiding the risks of equipment damage and production line stagnation.

[0081] Among them, the process type identification sub-module is a part of the production process status collection module, responsible for accurately identifying and classifying different production process types, and providing relevant process data to the subsequent risk assessment and vibration tolerance analysis modules. The core function of this module is to ensure that the system can understand the specific characteristics and requirements of each production process, so as to provide valuable background data for earthquake impact analysis.

[0082] This sub-module mainly works in the following ways:

[0083] Process stage identification: The process type identification sub-module first identifies different process stages in the production process, such as the initial processing stage, assembly stage, testing stage, etc. Each process stage may involve different equipment and operation modes, so accurately distinguishing these stages can help the system better understand the current state of the production line and make a reasonable assessment of the vibration impact.

[0084] Processing method analysis: This sub-module can also analyze the specific processing methods used in each process, such as machining, welding, injection molding, assembly, etc. Different processing methods have different requirements for the vibration tolerance of the equipment, so identifying this information helps to evaluate the sensitivity of each process to vibration in the subsequent stage, especially for processes with high precision requirements, such as semiconductor production or precision assembly.

[0085] Key equipment category identification: In addition to process stages and processing methods, the process type identification sub-module is also responsible for identifying the key equipment categories involved in each process. These devices may include automated robots, conveyor belts, precision instruments, machine tools, etc. The vibration tolerance and response characteristics of each device are different. Understanding the device categories helps the system evaluate the potential impact of vibration on the device and provides a basis for setting the vibration trigger threshold.

[0086] Data Output and Interface: The recognized process type information is organized into data and output to the system's database or real-time monitoring system. These data will provide important references for subsequent equipment status monitoring and vibration tolerance calculation.

[0087] Through this sub-module, the system can comprehensively understand the working status, equipment requirements, and processing methods of each production process, providing comprehensive data support for subsequent risk assessment, vibration analysis, and emergency response strategies.

[0088] Among them, the equipment status monitoring sub-module is responsible for real-time collection of equipment operation status data in each production process, including information such as the equipment's operation mode, load level, power consumption, etc. The core design of this sub-module is to help the system real-time evaluate the health status of the equipment through precise equipment monitoring, and provide key input data for subsequent vibration tolerance calculation and risk assessment.

[0089] The equipment status monitoring sub-module mainly consists of the following parts:

[0090] Equipment Operation Mode Monitoring: This unit monitors the working status of the equipment through sensors and monitoring systems, including whether it is in operation, standby, or shutdown state. The vibration tolerance of the equipment is different in different working modes. Therefore, real-time obtaining the equipment's working mode information is crucial for subsequent vibration impact analysis.

[0091] Load Level Monitoring: The load level of the equipment directly affects its vibration tolerance. Under high load conditions, the equipment may be more vulnerable to vibration and cause excessive damage. Through current, voltage, and load sensors, the equipment status monitoring sub-module can real-time monitor the load level of the equipment and provide data support for subsequent vibration tolerance calculation.

[0092] Real-time Power Consumption Monitoring: Power consumption is an important indicator for evaluating the equipment's operation status. Especially in the case of vibration, abnormal fluctuations in the equipment's power may indicate abnormal working status or damage of the equipment. This unit judges whether the equipment is operating within the normal range by real-time monitoring the power consumption of the equipment, providing a basis for risk assessment and fault warning.

[0093] Data Integration and Transmission: The equipment status monitoring sub-module integrates and transmits the collected equipment status data to the system's central processing unit. These data are transmitted in real-time through wireless or wired networks to ensure that the system can timely obtain the latest operation information of the equipment and quickly respond during an earthquake.

[0094] Through the device status monitoring sub-module, the system can understand the working status, load level, and power consumption of the device in real time, accurately identify potential problems of the device, and provide accurate input data for vibration tolerance assessment and risk analysis. This function effectively avoids the deficiency of traditional monitoring systems that only rely on a single device status, provides more comprehensive device operation information, and thus improves the evaluation accuracy of the system for the vibration tolerance of the device and the efficiency of emergency response.

[0095] In a preferred embodiment of the present invention, the earthquake impact analysis module includes:

[0096] A vibration amplitude calculation sub-module, which is used to calculate the expected vibration amplitude of each production process according to earthquake data, combined with the geographical location coordinates, equipment installation height, and ground vibration amplification effect parameters of each production process;

[0097] An equipment damage risk assessment sub-module, which is used to calculate the vibration stress distribution of each equipment and predict the degree of equipment damage risk according to vibration data, combined with the equipment structure characteristics, vibration tolerance parameters, and historical damage data of each production process;

[0098] An accumulated vibration effect calculation sub-module, which is used to analyze the accumulated vibration impact of the earthquake on the production process according to vibration data, expected vibration amplitude, and equipment damage risk degree.

[0099] In the embodiment of the present invention, the earthquake impact analysis module is one of the core modules of the system, responsible for comprehensively analyzing information such as earthquake data, production process status data, and equipment vibration tolerance to accurately evaluate the impact of the earthquake on production processes and equipment.

[0100] The vibration amplitude calculation sub-module calculates the expected vibration amplitude of different production processes according to earthquake waveform data, epicenter position data, and parameters such as the geographical location coordinates and installation height of the equipment. Through this module, the system can accurately predict the impact intensity of the earthquake on each process and equipment, and evaluate the potential threat of vibration to the production process. The accuracy of vibration amplitude calculation directly affects the accuracy of subsequent risk assessment. Therefore, the design of this module needs to consider the specific conditions of different production processes and equipment, and perform dynamic calculations in combination with real-time earthquake data.

[0101] The equipment damage risk assessment sub-module then evaluates the risk degree of the equipment during the earthquake according to vibration impact data, equipment structure characteristics, and vibration tolerance parameters. This module calculates the possible damage risk of the equipment by analyzing the vibration stress distribution, and determines whether the equipment needs to be shut down immediately or perform other emergency treatments. Through this module, the system can perform personalized risk assessment on each equipment to ensure that the equipment can be protected in time when the vibration is large, and avoid equipment damage caused by long-term operation.

[0102] The cumulative vibration effect calculation sub-module calculates the cumulative vibration impact of the device based on the vibration data, expected vibration amplitude, and the degree of equipment damage risk. Through this module, the system can predict the long-term impact that the device may suffer during continuous vibration, identify potential fatigue problems and structural damages of the device in advance, and provide data basis for subsequent maintenance and restoration. The calculation of the cumulative vibration effect can provide decision support for the restoration of the production process, ensuring that the production will not malfunction due to equipment damage during the post-earthquake restoration process.

[0103] Overall, the earthquake impact analysis module provides an accurate earthquake impact assessment for the entire system by comprehensively analyzing multiple data sources, ensuring the scientificity and timeliness of various disposal measures.

[0104] Among them, the vibration amplitude calculation sub-module completes the calculation of the vibration amplitude through the following steps:

[0105] Earthquake data acquisition: The sub-module first obtains the seismic waveform data and epicenter location data provided by the earthquake monitoring module. The seismic waveform data provides the intensity information of different frequency components during the earthquake, while the epicenter location data helps the system determine the source distance and propagation path.

[0106] Association of geographical location and equipment installation location: Based on the geographical coordinates of each production process and the installation height of the equipment, the system can calculate the intensity of the impact of seismic wave propagation on different processes. Since the seismic wave propagation is affected by geographical factors, the vibration amplitude will gradually weaken as the distance from the epicenter increases. At the same time, the installation height of the equipment and the ground vibration amplification effect will also affect the actual intensity of the vibration.

[0107] Assessment of vibration amplification effect: The characteristics of seismic wave propagation are different under different geological conditions. Especially in some areas, the seismic wave may experience amplification effect. The vibration amplitude calculation sub-module will consider the influence of geological conditions on the vibration intensity, so as to calculate the vibration amplitude that each production process may encounter more accurately.

[0108] Time dynamic adjustment of vibration impact: As time goes by, the propagation intensity of the seismic wave will gradually weaken. Therefore, the sub-module will also dynamically adjust the vibration amplitude according to the duration of the vibration. This dynamic adjustment mechanism can ensure that the system updates the calculation results of the vibration amplitude in a timely manner during the earthquake.

[0109] Through the above process, the vibration amplitude calculation sub-module can accurately evaluate the vibration amplitude of different production processes, and provide data support for subsequent equipment damage risk assessment and emergency disposal instruction generation.

[0110] Among them, the equipment damage risk assessment sub-module has the following specific work process:

[0111] Combination of vibration amplitude and equipment structure characteristics: The sub-module first combines the vibration data provided by the vibration amplitude calculation sub-module with the structure characteristics of the equipment to analyze the vibration response of the equipment in different processes. The structure characteristics of the equipment include the rigidity, weight, support structure type, etc. of the equipment, and these factors will directly affect the vibration tolerance of the equipment. Through this analysis, the system can evaluate the stress distribution of each equipment under different vibration conditions, and then obtain the damage risk of the equipment.

[0112] Consideration of vibration tolerance parameters: The vibration tolerance parameters of the equipment are the key factors for evaluating whether the equipment can withstand vibrations, including the vibration trigger threshold and vibration cumulative tolerance of the equipment, etc. These parameters are usually calculated and estimated based on data such as the design specifications, material strength, and usage history of the equipment. The equipment damage risk assessment sub-module combines these parameters with the vibration amplitude to determine whether the equipment will be damaged.

[0113] Reference to historical vibration response data: The historical vibration response data provides an important basis for evaluating the performance of the equipment in emergencies such as earthquakes. By analyzing the past vibration response data of the equipment, the sub-module can judge the performance of the equipment under similar vibration conditions and predict the risk level of the equipment under the current earthquake conditions. This process can help the system identify the long-term damage risks that may be caused by vibration cumulative damage.

[0114] Risk level assessment: Finally, the sub-module assigns a risk level to the equipment in each production process according to the equipment damage risk assessment results. This level represents the potential damage risk of the equipment under the current earthquake conditions and provides data basis for the generation of subsequent classification and disposal strategies.

[0115] Through this process, the equipment damage risk assessment sub-module provides accurate assessment data on the equipment status and earthquake impact for the entire system, ensuring that the system can make correct emergency response decisions in a timely manner.

[0116] In a preferred embodiment of the present invention, the classification and disposal strategy generation module includes:

[0117] Risk level determination sub-module, used to evaluate the risk levels of each production process according to the process impact analysis data;

[0118] Shutdown decision sub-module, used to generate an immediate shutdown instruction for low vibration tolerance processes according to the risk level, and set a shutdown buffer time in combination with the production task priority;

[0119] Monitoring and regulation sub-module, used to generate continuous monitoring instructions for high vibration tolerance processes according to the risk level, and conduct real-time trend analysis on the vibration data. If a secondary vibration amplification effect is detected, the monitoring frequency is dynamically adjusted;

[0120] The recovery plan formulation sub-module is used to generate a safe production recovery plan based on the risk level and process impact analysis data.

[0121] In the embodiment of the present invention, the hierarchical disposal strategy generation module plays a crucial role in the whole system. Its core function is to generate emergency disposal instructions for different production processes according to the earthquake impact analysis data, ensuring that the system can respond quickly and accurately when an earthquake occurs.

[0122] The risk level determination sub-module evaluates the risk level of each production process by receiving the data provided by the earthquake impact analysis module. First, this sub-module evaluates each process according to factors such as the vibration amplitude of the production process, the risk degree of equipment damage, and the cumulative vibration impact, in accordance with the preset risk classification criteria. By judging different risk levels, the system can quickly determine which processes need to take immediate shutdown or other emergency response measures, and which processes can continue to operate. The accurate assessment of the risk level is crucial for generating subsequent disposal instructions, directly affecting whether the system can effectively prevent equipment damage and avoid production stagnation in a short time.

[0123] The shutdown decision sub-module generates a shutdown instruction according to the risk level. For processes with low vibration tolerance, this module will immediately generate a shutdown instruction and set a shutdown buffer time according to the production task priority. The design of this mechanism can ensure that even when vibrations occur, the equipment can be protected in a timely manner, avoiding serious damage caused by the equipment's inability to adapt to vibrations. At the same time, setting the shutdown buffer time can minimize the time of production process interruption on the premise of ensuring safety, optimize production scheduling, and reduce the economic losses caused by shutdowns.

[0124] The monitoring and regulation sub-module generates continuous monitoring instructions according to the risk level. For processes with high vibration tolerance, the system will choose to continuously monitor the vibration situation and dynamically adjust the monitoring frequency. Through real-time trend analysis of the vibration data, the system can quickly detect changes in the vibration amplitude and increase the monitoring frequency when the vibration intensifies, ensuring the safe operation of the production process. By flexibly adjusting the monitoring frequency, this sub-module can respond to changes in process vibrations in real time under different vibration conditions and ensure the normal operation of the production line.

[0125] The recovery plan formulation sub-module generates a safe production recovery plan based on the risk level and process impact analysis data. The recovery plans for production processes with different risk levels will vary after an earthquake. For high-risk processes, the system will adopt more stringent recovery strategies to ensure that the equipment can be restarted in a safe environment; for low-risk processes, the recovery process is relatively simple. This sub-module generates targeted recovery plans by precisely analyzing the vibration tolerance, equipment damage situation, and repair requirements of each production process. The formulation of the recovery plan not only ensures the rapid resumption of production but also avoids secondary equipment damage or production accidents caused by improper recovery.

[0126] Through the implementation of this module, the hierarchical disposal strategy generation module ensures that the system can generate personalized disposal strategies according to the vibration tolerance and risk level of different production processes, effectively improving the safety and efficiency of production. Compared with traditional emergency management systems, this module has obvious innovation. It can dynamically adjust emergency disposal measures, improving the adaptability and intelligent level of the system.

[0127] Among them, the working process of the shutdown decision sub-module is as follows:

[0128] Risk level assessment: According to the risk level provided by the equipment damage risk assessment sub-module, the shutdown decision sub-module first assesses the risks of each production process. If the equipment damage risk level of a certain process is too high, or the vibration intensity exceeds the vibration tolerance threshold of the equipment, a shutdown instruction needs to be triggered.

[0129] Shutdown judgment criteria: Based on the amplitude, duration of the vibration, and the vibration tolerance parameters of the equipment, the sub-module judges whether immediate shutdown is required. For processes with low vibration tolerance, the system will generate an immediate shutdown instruction after an earthquake to avoid equipment damage during vibration. For processes with stronger vibration tolerance, the system will decide whether to shutdown immediately according to the vibration intensity.

[0130] Task priority and shutdown buffer time: The shutdown decision sub-module also considers the priority of production tasks and reasonably sets the shutdown buffer time. For some non-critical production processes, the system may set a longer shutdown buffer time to reduce production interruption time and improve production efficiency. For critical processes, the shutdown instruction will be triggered first to ensure the safety of equipment and production lines.

[0131] Shutdown instruction generation: After determining that shutdown is required, the system will generate different types of shutdown instructions according to the specific situation, including immediate equipment shutdown instructions and step-by-step shutdown instructions, and transmit them to the control execution module to ensure that the equipment can stop running quickly.

[0132] Through this process, the shutdown decision sub-module ensures that during an earthquake, the system can make accurate shutdown decisions based on the risk levels and vibration tolerances of different production processes, avoiding equipment damage and production stagnation caused by vibrations.

[0133] Among them, the monitoring and regulation sub-module has the following specific workflow:

[0134] Real-time monitoring of vibration data: The sub-module first receives real-time vibration data from the earthquake monitoring module and the equipment status monitoring sub-module. Through this data, the system can accurately monitor the vibration amplitude and frequency of each production process and understand the impact of vibrations on the equipment in real time.

[0135] Analysis of vibration trends: The sub-module judges whether the vibration amplitude exceeds the preset safety threshold through real-time trend analysis of the vibration data. If the vibration amplitude increases, it may lead to equipment failure or damage, and the system will dynamically adjust the monitoring frequency based on this information to improve the tracking ability of the vibration situation.

[0136] Dynamically adjusting the monitoring frequency: When it is detected that the vibration amplitude increases and the equipment may be approaching the vibration threshold, the system will increase the monitoring frequency to obtain real-time changes in the vibration. If the vibration amplitude decreases, the monitoring frequency can be correspondingly reduced, thereby reducing unnecessary data processing and resource consumption.

[0137] Activation of the emergency response mechanism: If the monitoring data indicates that the vibration has a tendency to intensify, the sub-module will immediately transmit the information to the control execution module to activate further emergency response measures, such as shutdown instructions or equipment protection mechanisms.

[0138] Through real-time vibration monitoring and dynamic adjustment of the frequency, the monitoring and regulation sub-module can ensure that the equipment remains in a safe state during vibrations and provide the necessary data support for subsequent disposal strategies.

[0139] Among them, the sub-module for formulating recovery plans has the following specific process:

[0140] Evaluating the risk level and equipment status: The sub-module evaluates the safety status of each production process and equipment based on the risk level and equipment status data provided by the hierarchical disposal strategy generation module. After determining the vibration tolerance and damage degree of the equipment, the sub-module will design different recovery plans.

[0141] Formulating multi-level recovery plans: For equipment slightly affected by vibrations, the system will generate quick recovery instructions to ensure that the equipment can resume production in the shortest possible time. For equipment severely affected by vibrations, it will be recovered in stages according to the repair situation of the equipment, avoiding possible re-damage caused by premature startup of the equipment.

[0142] Coordinate the restoration sequence of production processes: The restoration plan formulation sub-module also arranges the restoration sequence reasonably according to the importance and priority of production processes. Key production processes will be started first to ensure that the core part of the production line is restored as soon as possible; non-key processes can be restored appropriately later to avoid new risks caused by improper operations.

[0143] Generate restoration instructions and transmit them to the control execution module: By refining the restoration plan, the sub-module generates corresponding restoration control instructions for each device and transmits them to the control execution module to start the restoration work in a timely manner.

[0144] Through the implementation of this module, the system can quickly generate personalized restoration plans after an earthquake to ensure the safe and orderly restoration of equipment production.

[0145] In a preferred embodiment of the present invention, the vibration tolerance calculation sub-module includes:

[0146] A structure response modeling unit, which is used to extract the structural characteristic parameters of the device according to the device operation state data, and establish a device structure response model according to the installation method of the device, the type of support structure and the mass distribution;

[0147] A dynamic threshold generation unit, which is used to fit the structure response model with the historical vibration response data, calculate the preliminary trigger threshold corresponding to each device according to the fitting result, and dynamically adjust the preliminary trigger threshold according to the current state of the device to obtain the vibration trigger threshold;

[0148] A vibration adaptability evaluation unit, which is used to calculate the vibration cumulative bearing capacity of the device according to the vibration trigger threshold and the vibration stability index of the device, and generate vibration tolerance parameters; where, ,

[0149] is the vibration cumulative bearing capacity, is the reference bearing capacity coefficient, is the structural stiffness, is the mass of the device, is the installation height, is a unit conversion coefficient for converting into a dimensionless number, is the average vibration trigger threshold, is the historical maximum vibration response value, is a constant, a very small positive number, used to prevent division by zero, is the current load, is the maximum rated load, is the adjustment coefficient.

[0150] In the embodiments of the present invention, the vibration tolerance calculation sub-module plays a crucial role in the system. It is responsible for calculating the vibration trigger threshold and the vibration cumulative tolerance capacity of the device based on the operating state, structural parameters, and historical vibration response data of the device.

[0151] The structural response modeling unit is a core component of the vibration tolerance calculation sub-module. Its function is to extract the structural characteristic parameters of the device according to the operating state data of the device, and establish a structural response model of the device in combination with the installation method, support structure type, and mass distribution of the device. This response model is established based on the dynamic performance of the device under different loads and vibration environments, so it has high accuracy. Through precise structural response modeling, the system can simulate the vibration response of the device during an earthquake, thereby obtaining the vibration trigger threshold of the device.

[0152] The dynamic threshold generation unit then fits the structural response model with the historical vibration response data according to the current state of the device, and calculates the vibration trigger threshold of the device in real time. In a vibration environment, different devices will exhibit different vibration tolerances. Especially in the case of load changes, temperature fluctuations, or device aging, the vibration trigger threshold of the device may change. Therefore, the design of dynamically adjusting the vibration trigger threshold is highly innovative. It can adjust the vibration trigger threshold of the device according to the real-time state and historical data of the device, ensuring the safety and reliability of the device in practical applications.

[0153] The vibration adaptability evaluation unit combines the vibration trigger threshold and the vibration stability index of the device to calculate the vibration cumulative tolerance capacity of the device. The vibration cumulative tolerance capacity measures the comprehensive tolerance capacity of the device after experiencing long-term vibrations. This evaluation process can accurately predict the damage risk of the device under different vibration intensities, providing more detailed data support for subsequent earthquake impact analysis.

[0154] Through this module, the system can accurately evaluate the vibration tolerance of the device during an earthquake, ensure that the device can respond in a timely manner during the vibration process, and take appropriate protection measures. Compared with the traditional static threshold design, the vibration tolerance calculation sub-module significantly improves the protection ability of the device and the response speed of the system through dynamic adjustment and real-time evaluation.

[0155] In a preferred embodiment of the present invention, the cumulative vibration effect calculation sub-module includes:

[0156] The time-weighted integration unit is used to perform time-series segmentation processing on the vibration data, and introduce a time decay factor to perform weighted integration on the vibration intensities at different times to generate a vibration cumulative impact value; where ,

[0157] is the vibration cumulative impact value, representing the total impact of vibrations experienced by the device before time ; is the initial amplitude of the seismic source, representing the initial vibration intensity emitted by the seismic source, is the horizontal distance between the device and the epicenter, is the depth of the epicenter, is the adjustment coefficient, representing the attenuation degree of the intensity during the vibration propagation process, is the earthquake magnitude, describing the intensity of the earthquake, is the time decay factor, where is the adjustment coefficient, is the current time, is the historical time, is the time of the vibration frequency, representing the vibration frequency, is the vibration frequency threshold of the device, representing the upper limit of the vibration frequency that the device can tolerate, is the adjustment coefficient, representing the impact degree of the vibration frequency on the device;

[0158] The fatigue trend analysis unit is used to compare the vibration cumulative impact value with the vibration tolerance parameters of each device, and based on the device service life model, predict the structural fatigue trend of the device due to continuous vibrations;

[0159] The damage potential discrimination unit is used to determine whether the current device is in the safe operation area, warning area or risk area according to the structural fatigue trend, combined with the preset fatigue threshold range, and generate the cumulative vibration impact result.

[0160] In the embodiment of the present invention, the function of the cumulative vibration effect calculation sub-module is to calculate the vibration cumulative impact of the device by analyzing the vibration data and the degree of risk of device damage when an earthquake occurs.

[0161] The time-weighted integration unit is responsible for performing time series segmentation processing on the vibration data, and introducing the time decay factor to perform weighted integration on the vibration intensities at different times. By analyzing the time evolution of the vibration data, this unit can accurately evaluate the continuous impact of vibrations on the device, and consider the different impact degrees of vibrations at different times through weighted integration. The introduction of the time decay factor ensures the gradual weakening of the vibration intensity, making the calculation of the vibration impact on the device more in line with the actual situation.

[0162] The fatigue trend analysis unit compares the cumulative vibration impact value with the equipment's vibration tolerance parameters and, based on the equipment's service life model, predicts the structural fatigue trend of the equipment due to continuous vibration. Fatigue trend analysis effectively assesses the accumulation of fatigue in equipment under long-term vibration, helping the system predict equipment damage and failure in advance. This module is particularly suitable for high-precision equipment and critical production processes, enabling early identification of potential equipment failures and preventing sudden damage at critical moments.

[0163] The damage potential identification unit, based on fatigue trend analysis results and preset fatigue thresholds, determines whether the equipment is currently in the safe operating zone, warning zone, or risk zone, and generates cumulative vibration impact results. By monitoring equipment fatigue damage in real time, this unit helps the system determine the equipment's operating status in real time and outputs corresponding warning information based on different damage potentials, providing data support for subsequent emergency response.

[0164] Through the implementation of this module, the system can not only assess the immediate impact of earthquakes on equipment, but also predict potential fatigue damage to equipment from long-term vibrations, providing a scientific basis for equipment maintenance and upkeep. This continuous monitoring and long-term early warning design significantly improves equipment safety and reliability, ensuring the long-term stable operation of the production line.

[0165] Among them, the specific working process of the damage potential judgment unit is as follows:

[0166] Cumulative vibration impact data input: The damage potential assessment unit first receives cumulative vibration impact data from the time-weighted integration unit. This data reflects the long-term impact of vibration on the equipment. This data allows the system to understand the vibration intensity and impact experienced by the equipment during the earthquake, providing a basis for subsequent damage assessment.

[0167] Equipment Fatigue Trend Analysis: This unit also uses the results of equipment fatigue trend analysis as input. Based on historical vibration data and parameters such as the equipment's material strength and service life, it analyzes the equipment's fatigue evolution. This analysis allows the system to determine the potential fatigue damage that may occur during prolonged vibration and, in turn, to estimate the equipment's remaining life and damage potential.

[0168] Damage Risk Zone Determination: Based on cumulative vibration impact data and fatigue trend analysis, the damage potential identification unit divides the equipment's status into different risk zones, including safe operation, warning, and risk zones. When fatigue damage accumulates to a certain level, or the impact of vibration on the equipment exceeds its tolerance, the system determines that the equipment has entered the warning or risk zone. Real-time monitoring is then used to adjust the equipment's status or implement appropriate protective measures.

[0169] Output damage determination result: The damage potential discrimination unit provides the output damage risk level information to the hierarchical disposal strategy generation module. This information will be used as basic data to generate corresponding emergency disposal measures to ensure that the equipment can be protected in a timely manner during the vibration process and avoid equipment downtime or failure caused by potential damage.

[0170] Through the implementation of this sub-module, the system can monitor the damage potential of the equipment in real time, give early warnings and make emergency responses, ensure that the equipment can be effectively protected during the vibration process, avoid irreparable damage caused by long-term vibration, and improve the safety and stability of the production line.

[0171] In a preferred embodiment of the present invention, the risk level determination sub-module includes:

[0172] A multi-parameter fusion unit for extracting the expected vibration amplitude, the degree of equipment damage risk, and the cumulative vibration impact according to the process impact analysis data, and calculating a comprehensive risk score according to a preset weight factor;

[0173] A fuzzy rule matching unit for inputting the comprehensive risk score into a fuzzy rule system and inferring the fuzzy risk level of each production process according to a preset fuzzy membership function and risk judgment rules;

[0174] A risk level mapping unit for outputting a clear risk level label according to the clarification standard corresponding to the fuzzy risk level.

[0175] In the embodiment of the present invention, the risk level determination sub-module plays a crucial role in the earthquake emergency disposal system of the automated production line. Its core function is to evaluate the risk levels of different production processes according to the data from the earthquake impact analysis module and provide data support for the subsequent generation of emergency disposal strategies.

[0176] The work of this sub-module starts from the process impact analysis data, comprehensively analyzes key factors such as the expected vibration amplitude of the production process, the degree of equipment damage risk, and the cumulative vibration impact. These factors reflect the impact degree of the earthquake on the production process. Therefore, they provide a necessary basis for the assessment of the risk level. Through the fusion of these data, the system can obtain the comprehensive risk score of each production process and determine its risk level based on the preset risk classification standard. Through this multi-dimensional data analysis, the system can distinguish high-risk, medium-risk, and low-risk processes and generate emergency response strategies of different levels.

[0177] To further enhance risk assessment accuracy, the risk level determination submodule incorporates a multi-parameter fusion unit. This unit performs a weighted risk calculation based on preset weighting factors and combines various data points (such as vibration amplitude, equipment damage risk, and cumulative vibration impact). This weighted calculation ensures that the impact of each factor on the final risk assessment is appropriately reflected. This approach enables the system to more accurately assess the risk level of each production process, avoiding erroneous decisions caused by a single factor.

[0178] The fuzzy rule matching unit plays a key role in this process. Based on the comprehensive risk score calculated by the multi-parameter fusion unit, the fuzzy rule matching unit inputs the score into the fuzzy rule system. Based on the preset fuzzy membership functions and risk judgment rules, it infers the fuzzy risk level for each production process. This fuzzy reasoning mechanism enables the system to handle uncertainty in risk assessment and avoid overly strict or broad risk classification. Through the application of fuzzy logic, the system can still make reasonable risk judgments in complex or ambiguous situations.

[0179] The risk level mapping unit is responsible for converting ambiguous risk levels into clear risk level labels for subsequent response instructions. Through this mapping process, the system transforms risk levels from ambiguous to clear, specific instructions, providing precise decision support for subsequent emergency response. Whether it's shutdown, monitoring, or other safety recovery measures, this module can quickly generate and ensure accurate and efficient execution.

[0180] Through this module's operation, the risk level assessment submodule can accurately and in real time assess the risks of each production process and generate personalized emergency response instructions based on the risk level. Compared with traditional emergency management systems, this module has a more refined risk classification and processing mechanism, capable of multi-level classification of production processes based on different vibration impacts, providing precise support for subsequent emergency response. This precise risk assessment enables the production line to respond quickly in the event of an earthquake, reducing the risk of equipment damage and maximizing the normal operation of the production line.

[0181] This module not only improves the system's ability to handle earthquake events, but also enhances its flexibility and intelligence. By introducing fuzzy logic and multi-parameter fusion analysis, the system can make reasonable emergency response decisions in complex earthquake environments, ensuring the continued stable operation of production processes during earthquake disasters.

[0182] Among them, the working process of the fuzzy rule matching unit can be divided into the following steps:

[0183] Preparation of input data: The fuzzy rule matching unit receives the comprehensive risk score from the multi-parameter fusion unit as the input data. The comprehensive risk score usually includes information such as vibration amplitude, equipment damage risk level, cumulative vibration impact, etc. These data reflect the overall degree of earthquake impact on different production processes.

[0184] Fuzzy logic inference mechanism: This unit processes the input data using a preset fuzzy rule system. The fuzzy rule system is based on empirical data or expert knowledge and transforms the input data into fuzzy risk levels through fuzzy membership functions (an important concept in fuzzy set theory). Common fuzzy membership functions include low risk, medium risk, and high risk, etc. These functions map the input data to fuzzy levels. For example, the membership degree corresponding to "low risk" is relatively high, while that of "high risk" is relatively high.

[0185] Inference process: The fuzzy rule matching unit matches the input comprehensive risk score with the preset rule base through fuzzy logic rules and conducts inference calculations. Specifically, each fuzzy rule derives a fuzzy risk result based on different levels of input data, such as an intermediate state between "low risk" and "high risk". During the rule matching process, the system automatically processes the fuzzy data to judge the risk level to cope with incomplete information or uncertainty.

[0186] Output of fuzzy risk levels: The result after inference is the fuzzy risk levels, which will be transformed into clear risk level labels in the risk level mapping unit for subsequent generation of emergency response strategies. The use of fuzzy logic improves the flexibility and fault tolerance of the system in complex and dynamic environments, enabling the system to still make reasonable judgments even when the input data is incomplete or has errors.

[0187] Through this process, the fuzzy rule matching unit enhances the system's adaptability in the face of uncertain and dynamic earthquake data, avoids the limitations of traditional hard threshold judgment methods, and thus provides a more intelligent risk assessment.

[0188] Among them, the working process of the risk level mapping unit is as follows:

[0189] Input of fuzzy risk levels: This unit first receives the fuzzy risk levels output by the fuzzy rule matching unit. These levels may be "low risk", "medium risk", or "high risk", but due to the use of fuzzy logic inference, the results may be at a certain position between these levels.

[0190] Risk level conversion rule: The risk level mapping unit maps the fuzzy risk level to a clear risk level label according to the preset conversion rule. Usually, the system sets a set of clear criteria to convert the fuzzy result into a standardized risk level. For example, if the fuzzy result is between "low risk" and "medium risk", it may be marked as "medium risk", and between "medium risk" and "high risk" it is "high risk". This mapping process ensures the conversion from fuzzy to clear, enabling subsequent processing steps to obtain clear instructions.

[0191] Output clear risk level labels: Through the mapping process, the system will finally generate clear risk level labels for each production process. These labels can clearly represent the specific risk status of each process during an earthquake, providing basic data for generating emergency response strategies. The mapped risk level labels usually include "low risk", "medium risk" and "high risk", and play a key role in the subsequent generation of emergency response strategies.

[0192] Through this mapping process, the risk level mapping unit ensures that the system can generate practical and operable emergency response strategies from the results obtained by fuzzy logic reasoning, providing accurate support for subsequent equipment protection, shutdown decision-making, etc.

[0193] In a preferred embodiment of the present invention, the structural response modeling unit includes:

[0194] The structural parameter extraction subunit is used to extract the installation method, connection bracket configuration, component material type and mass distribution information of the equipment according to the equipment operation status data to form the structural basic parameters;

[0195] The modeling template selection subunit is used to select a matching template from a preset multi-type equipment structure modeling template according to the structural basic parameters. The matching templates include a rigid structure model, a hierarchical structure model and a flexible connection model;

[0196] The response model construction subunit is used to map the structural basic parameters into the matching template to construct an equipment structural response model including multi-degree-of-freedom vibration characteristics.

[0197] In the embodiment of the present invention, the structural response modeling unit is a key component of the vibration tolerance calculation sub-module, responsible for establishing a structural response model for the equipment and accurately evaluating the vibration response of the equipment during an earthquake.

[0198] The structural parameter extraction subunit extracts key information from the operation status data of the device, including the installation method of the device, the type of support structure, the type of component material, and the mass distribution, etc. This process can record the geometric parameters and material properties of the device in detail, providing accurate structural data for subsequent modeling. Through the detailed extraction of structural parameters, the system can effectively identify the potential weaknesses and vibration response characteristics of the device during an earthquake, laying a foundation for the establishment of the subsequent structural response model.

[0199] The modeling template selection subunit selects the most suitable template from a preset multi-type device structure modeling template according to the extracted basic structural parameters. The templates include rigid structure models, hierarchical structure models, and flexible connection models, etc. Each template represents a different type of device design and can provide appropriate vibration response simulations for the performance of the device under different working conditions. Through flexible template selection, the system can dynamically adjust the model according to the device type, ensuring that the model used can adapt to the vibration characteristics of different devices.

[0200] The response model construction subunit maps the basic structural parameters into the selected template to construct a device structural response model with multi-degree-of-freedom vibration characteristics. Through this method, the vibration response of the device can be simulated more accurately, taking into account the independent responses of different parts of the device during vibration. The innovation of this method lies in that it not only considers the overall vibration response of the device but also can simulate the resonance effects that may occur in different parts of the device during vibration, further improving the accuracy of the model.

[0201] Through the implementation of this module, the structural response modeling unit can provide comprehensive modeling support for the vibration response of the device during an earthquake, ensuring that the subsequent vibration tolerance calculation is more accurate. During an earthquake, the system can make a timely assessment of the vibration tolerance of the device through accurate structural response analysis and dynamically adjust the vibration trigger threshold of the device. The work of this module greatly improves the anti-risk ability of the device in earthquake disasters, enabling the device to respond effectively in different vibration environments.

[0202] Among them, the work process of the structural parameter extraction subunit is as follows:

[0203] Obtain the operation status data of the device: This subunit first obtains the real-time operation status data of the device from the device status monitoring module. These data include information such as the working mode and load level of the device, which helps to understand the operation status of the device in the current environment.

[0204] Extraction of equipment structural features: Based on the operating status data of the equipment, the structural parameter extraction subunit further extracts the specific structural parameters of the equipment. These parameters include the installation method of the equipment (such as whether it is a fixed installation or a mobile device), the type of connection bracket, the support structure (such as whether it is a rigid support or a flexible support), the material type of the components (such as metal, plastic, alloy, etc.), and the mass distribution of the equipment (such as which part of the equipment the mass is concentrated in).

[0205] Data integration and processing: The extracted equipment structural parameters will be sorted out and transmitted to the structural response modeling subunit for subsequent analysis. The accurate extraction of structural parameters is crucial for the vibration response that the equipment may generate during an earthquake, and it can help the system generate an accurate equipment structural response model.

[0206] Through this process, the structural parameter extraction subunit can provide accurate data support for the vibration response of the equipment, ensuring that subsequent structural modeling and vibration assessment are more accurate, and improving the system's assessment ability of the equipment's vibration adaptability.

[0207] Among them, the modeling template selection subunit has the following specific work process:

[0208] Receiving the basic equipment structural parameters: This subunit receives the basic equipment structural parameters provided by the structural parameter extraction subunit, such as the installation method, support type, material type, etc. These parameters describe the geometric shape and structural composition of the equipment and are the basis for vibration response modeling.

[0209] Template selection: According to the basic equipment structural parameters, the modeling template selection subunit selects the most suitable model from a set of predefined equipment structural templates. The templates may include rigid structure models, hierarchical structure models, and flexible connection models, etc. Different models are suitable for different types of equipment. For example, a rigid structure model is suitable for equipment with rigid supports, while a flexible connection model is suitable for equipment with a more flexible structure.

[0210] Dynamic adjustment and model matching: This subunit will adjust the template selection strategy according to the specific parameters of the equipment to ensure that each equipment can obtain the most accurate structural response model. By precisely matching the equipment characteristics with the modeling template, the system can better simulate the propagation process of vibration in the equipment.

[0211] Outputting the matched modeling template: Finally, the modeling template selection subunit will output the selected modeling template and hand it over to the subsequent response model construction subunit for further structural response analysis.

[0212] Through this process, the modeling template selection subunit ensures that the vibration response model of the equipment highly matches the structural characteristics of the equipment, providing accurate basic data for the vibration analysis of the system.

[0213] Among them, the response model construction subunit has the following workflow:

[0214] Receive the modeling template and structural parameters: The response model construction subunit obtains the matching modeling template from the modeling template selection subunit and combines the structural parameters of the device (such as mass distribution, installation method, support type, etc.) to generate the structural response model of the device.

[0215] Multi-degree-of-freedom modeling: This subunit regards each part of the device (such as structural components, connecting parts, etc.) as independent vibration units by introducing a multi-degree-of-freedom vibration model and simulates the independent responses of each part during vibration. Through the multi-degree-of-freedom model, the system can more accurately simulate the vibration behavior of the device, especially in a complex vibration environment.

[0216] Vibration response analysis: After establishing the multi-degree-of-freedom structural response model of the device, the response model construction subunit simulates the vibration response of the device under the action of seismic waves. This process helps the system evaluate the possible resonance effects, vibration transmission paths, and vibration responses of each part of the device during vibration.

[0217] Model output: Finally, the structural response model of the device output by the response model construction subunit provides basic data for subsequent vibration adaptability assessment, fatigue analysis, and risk assessment, ensuring that the system can accurately analyze the performance of the device in different vibration environments.

[0218] Through this process, the response model construction subunit ensures that the vibration response of the device can be accurately modeled, thereby improving the system's ability to evaluate the vibration tolerance of the device.

[0219] In a preferred embodiment of the present invention, the dynamic threshold generation unit includes:

[0220] A state factor matching subunit for constructing a corresponding state factor vector based on the current operating mode, load level, and historical anomaly records of the device;

[0221] An empirical model fitting subunit for performing regression fitting on the state factor vector and historical vibration response data to establish a dynamic fitting function for the preliminary vibration trigger threshold;

[0222] A threshold adaptive adjustment subunit for real-time correcting the preliminary vibration trigger threshold according to the output result of the dynamic fitting function, the current state of the device, and the feedback result of the device structural response model to generate the vibration trigger threshold corresponding to the device; where ,

[0223] is the vibration trigger threshold, representing the maximum vibration acceleration that the device can tolerate. When the acceleration exceeds this value, the device will trigger a vibration response. is the preliminary vibration trigger threshold of the device, which is the vibration tolerance of the device under standard conditions. Among them, is the basic vibration trigger threshold, that is, the basic vibration trigger threshold when all state factors are zero. is the weight coefficient of the th state factor, indicating the influence weight of this factor on the threshold. is the value of the th state factor at time , including the dimensionless or normalized values of the operating mode, load level, and number of historical anomalies. is the total number of state factors. is the device workload at time , representing the current load of the device. is the maximum load of the device, indicating the maximum load that the device can withstand during design. is the load state factor, indicating the influence of the current load of the device on the vibration trigger threshold. is the cumulative usage time of the device, representing the time that the device has been used. is the maximum design life of the device, indicating the service life of the device under ideal conditions. is the device aging factor, indicating the influence of the usage years of the device on the vibration tolerance. is the adjustment coefficient, indicating the influence speed of aging on the vibration trigger threshold. and are the weight coefficients of temperature and humidity, indicating the influence of environmental factors on the vibration tolerance of the device. is the environmental temperature, representing the temperature of the environment where the device is located. , , are the weight coefficients.

[0224] In the embodiment of the present invention, the dynamic threshold generation unit is an important part of the vibration tolerance calculation sub-module. Its main function is to dynamically adjust the vibration trigger threshold of the device according to the real-time state of the device, historical vibration response data, and feedback from the structural response model.

[0225] The state factor matching subunit constructs a corresponding state factor vector based on the current operating mode, load level, and historical anomaly records of the device. These factors reflect the real-time operating state of the device, including changes in load, the working mode of the device, and whether abnormal conditions have occurred, etc. By collecting these factors in real time, the system can timely identify the state changes of the device before or during an earthquake and provide a data basis for adjusting the vibration trigger threshold.

[0226] The empirical model fitting subunit performs regression fitting on the state factor vector and historical vibration response data to establish a dynamic fitting function for the vibration trigger threshold. Through this method, the system can calculate the current vibration trigger threshold of the device according to the real-time state of the device and the historical vibration response. This method not only considers the operating state of the device but also combines the vibration responses in historical data, enabling the system to flexibly respond to different types of vibration environments.

[0227] The threshold adaptive adjustment subunit then adjusts the preliminary vibration trigger threshold in real time according to the output result of the dynamic fitting function, the current state of the device, and the feedback of the device structure response model. This subunit can adjust the vibration threshold according to the real-time operating state of the device and the changes in the vibration environment, enabling the device to make the most appropriate response under different vibration intensities. This dynamic adjustment mechanism ensures the adaptability of the device during vibration and avoids the problem of slow response of traditional fixed-threshold systems in the case of sudden vibrations.

[0228] Through the operation of this module, the dynamic threshold generation unit can ensure that the device responds in real time during an earthquake, adjusting the vibration trigger threshold according to the state changes of the device, historical vibration data, and the structure model. This flexibility and self-adaptability enable the system to make efficient responses in various vibration environments, reducing the risk of device damage and production downtime and improving the vibration tolerance of the device.

[0229] In a preferred embodiment of the present invention, the fatigue trend analysis unit includes:

[0230] The life modeling subunit is used to construct a service life model for the corresponding device according to the vibration tolerance parameters of the device, combined with its material yield limit, structural deformation ability, and operating historical data;

[0231] The stress conversion subunit is used to convert the vibration cumulative influence value into an equivalent periodic stress sequence and map and compare it with the service life model to generate a structural fatigue change trend;

[0232] The trend evaluation subunit is used to calculate the fatigue life consumption ratio according to the structural fatigue change trend, and combined with the vibration historical fluctuation range, predict the fatigue evolution path of the device during future operation and generate structural fatigue trend data.

[0233] In the embodiment of the present invention, the fatigue trend analysis unit is a key component of the cumulative vibration effect calculation sub-module. Its main function is to evaluate the fatigue accumulation of the device during long-term vibration and predict the fatigue evolution trend of the device.

[0234] The service life modeling sub-unit constructs a service life model of the device based on the vibration tolerance parameters of the device, combined with the material yield limit, structural deformation ability and operation history data of the device. This model can accurately simulate the fatigue evolution process of the device in a vibration environment and predict the durability of the device under long-term vibration load. Through the work of this sub-unit, the system can provide an accurate fatigue life assessment for the device to ensure the long-term stable operation of the device.

[0235] The stress conversion sub-unit converts the vibration cumulative effect value into an equivalent periodic stress sequence and maps and compares it with the service life model to generate the structural fatigue change trend. The design of this sub-unit is based on traditional fatigue analysis methods, converting the vibration cumulative effect into stress changes, so that the fatigue damage of the device can be better combined with its service life model. Through this method, the system can accurately evaluate the cumulative stress borne by the device during vibration and provide data support for subsequent fatigue analysis.

[0236] The trend evaluation sub-unit calculates the fatigue life consumption ratio according to the structural fatigue change trend and predicts the fatigue evolution path of the device during future operation in combination with the vibration history fluctuation range. Through this evaluation, the system can identify in advance the fatigue problems that the device may encounter during future operation and provide a scientific basis for the maintenance and replacement of the device. This sub-unit can provide a more accurate fatigue warning for the device through the comprehensive analysis of the vibration history and the current fatigue state to ensure that the device is maintained in time before reaching the fatigue limit.

[0237] Through the implementation of the fatigue trend analysis unit, the system can predict in advance the long-term fatigue damage caused by vibration to the device and provide data support for the maintenance, repair and replacement of the device in production. The innovation and practicality of this unit enable the system to better cope with the impact of continuous vibration on the device and improve the long-term reliability of the device and the stability of the production line.

[0238] Among them, the work process of the service life modeling sub-unit is as follows:

[0239] Input of device vibration tolerance parameters: The service life modeling sub-unit first receives the vibration tolerance parameters of the device, including the vibration trigger threshold, vibration tolerance ability, etc. of the device. These parameters provide the basic data for subsequent service life modeling.

[0240] Analysis of material yield limit and structural deformation ability: This subunit also needs to further analyze the durability of the equipment based on the material yield limit and structural deformation ability of the equipment. The yield limit reflects the maximum stress that the material can withstand, while the structural deformation ability indicates the deformation ability of the equipment under vibration. These factors directly affect the service life of the equipment and its ability to withstand long-term vibration.

[0241] Combination of historical operation data: The life modeling subunit will also combine the historical operation data of the equipment, including information such as the vibration load and working hours experienced by the equipment during use. Through these data, the system can predict the long-term fatigue loss of the equipment and model the remaining life of the equipment.

[0242] Generate the equipment service life model: Finally, the life modeling subunit generates the equipment service life model based on the above data to predict the fatigue loss that the equipment may face during future operation. This model provides data support for the life management and maintenance strategy of the equipment and can evaluate the anti-fatigue ability of the equipment in advance during an earthquake.

[0243] Through this process, the life modeling subunit provides accurate life assessment data for fatigue trend analysis, helps the system identify the long-term operation risks of the equipment, and provides a basis for subsequent maintenance and emergency handling.

[0244] Among them, the stress conversion subunit has the following workflow:

[0245] Input the vibration cumulative impact value: The stress conversion subunit first receives the vibration cumulative impact value from the time-weighted integration unit. These impact values reflect the vibration intensity and duration of the equipment during an earthquake and provide basic data for fatigue assessment.

[0246] Convert to an equivalent periodic stress sequence: Through the stress conversion algorithm, the subunit converts the vibration cumulative impact value into an equivalent periodic stress sequence. The periodic stress sequence represents the stress fluctuations experienced by the equipment during vibration, and the equivalent stress is to convert these fluctuations into standardized stress values for fatigue analysis of the equipment.

[0247] Compare with the service life model: The stress conversion subunit compares the converted stress sequence with the service life model of the equipment to analyze the fatigue evolution trend of the equipment under the vibration cumulative impact. Through the comparison, the system can evaluate the anti-fatigue ability of the equipment and predict the remaining life of the equipment.

[0248] Output the fatigue stress change trend: Finally, the subunit outputs the fatigue stress change trend of the equipment and provides data support for subsequent trend assessment. Through this process, the system can judge the fatigue change of the equipment during future operation and provide a basis for the maintenance and safety management of the equipment.

[0249] Through this process, the stress conversion subunit enables the system to accurately predict the long-term fatigue loss of the device in a vibration environment, ensuring that the service life of the device can be reasonably extended within a safe range.

[0250] The above is the preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. An earthquake emergency disposal system for an automated production line, characterized in that, The system includes: A production process status acquisition module, which is used to acquire the process type, equipment operation status and its vibration tolerance parameters of each production process, and generate operation status data; An earthquake impact analysis module, which is used to calculate the expected vibration amplitude, equipment damage risk degree and cumulative vibration impact of different production processes according to earthquake data and operation status data, and obtain process impact analysis data; A hierarchical disposal strategy generation module, which is used to determine the risk levels of different production processes according to the process impact analysis data, and generate emergency disposal instructions for production processes with different risk levels, including an immediate shutdown instruction for processes with low vibration tolerance, a continuous monitoring instruction for processes with high vibration tolerance, and a safety restoration plan for different production processes; A control execution module, which is used to receive the hierarchical emergency disposal strategy and execute the corresponding emergency disposal operations.

2. The earthquake emergency disposal system for the automated production line according to claim 1, characterized in that The production process status acquisition module includes: A process type identification sub-module, which is used to obtain the process stage, processing method and key equipment category of each production process, and form process type data; An equipment status monitoring sub-module, which is used to monitor the operation mode, load level and real-time power consumption of equipment in each production process according to the process type information, and generate equipment operation status data; 3. The earthquake emergency disposal system for the automated production line according to claim 2, wherein A vibration tolerance calculation sub-module, which is used to calculate the vibration trigger threshold and vibration cumulative bearing capacity of equipment according to the equipment operation status data, combined with the equipment structure parameters and historical vibration response data, and generate vibration tolerance parameters. The earthquake impact analysis module includes: A vibration amplitude calculation sub-module, which is used to calculate the expected vibration amplitude of each production process according to earthquake data, combined with the geographical location coordinates, equipment installation height and ground vibration amplification effect parameters of each production process; An equipment damage risk assessment sub-module, which is used to calculate the vibration stress distribution of each equipment according to vibration data, combined with the equipment structure characteristics, vibration tolerance parameters and historical damage data of each production process, and predict the equipment damage risk degree; 4. The earthquake emergency disposal system for the automated production line according to claim 3, characterized in that, A cumulative vibration effect calculation sub-module, which is used to analyze the cumulative vibration impact of the earthquake on the production process according to vibration data, expected vibration amplitude and equipment damage risk degree. The hierarchical disposal strategy generation module includes: A risk level determination sub-module, which is used to evaluate the risk levels of different production processes according to the process impact analysis data; A shutdown decision sub-module, which is used to generate an immediate shutdown instruction for processes with low vibration tolerance according to the risk level, and set a shutdown buffer time in combination with the production task priority; A monitoring and regulation sub-module, which is used to generate a continuous monitoring instruction for processes with high vibration tolerance according to the risk level, and perform real-time trend analysis on vibration data. If a secondary vibration amplification effect is detected, the monitoring frequency is dynamically adjusted; 5. The earthquake emergency disposal system for the automated production line according to claim 2, wherein, A restoration plan formulation sub-module, which is used to generate a safe production restoration plan according to the risk level and process impact analysis data. The vibration tolerance calculation sub-module includes: A structure response modeling unit, which is used to extract the structural characteristic parameters of the equipment according to the equipment operation status data, and establish an equipment structure response model according to the installation method, support structure type and mass distribution of the equipment; A dynamic threshold generation unit, which is used to fit the structural response model with historical vibration response data, calculate the preliminary trigger thresholds corresponding to each device according to the fitting results, and dynamically adjust the preliminary trigger thresholds according to the current state of the device to obtain vibration trigger thresholds; A vibration adaptability evaluation unit, which is used to calculate the vibration cumulative bearing capacity of the device according to the vibration trigger threshold and the vibration stability index of the device, and generate vibration tolerance parameters.

6. The earthquake emergency disposal system for the automated production line according to claim 3, wherein The cumulative vibration effect calculation sub-module includes: A time-weighted integration unit, which is used to perform time-series segmentation processing on vibration data, introduce a time decay factor, and perform weighted integration on the vibration intensities at different times to generate a vibration cumulative impact value; A fatigue trend analysis unit, which is used to compare the vibration cumulative impact value with the vibration tolerance parameters of each device, and predict the structural fatigue trend of the device due to continuous vibration based on the device service life model; A damage potential discrimination unit, which is used to determine whether the current device is in a safe operation area, a warning area or a risk area according to the structural fatigue trend and in combination with a preset fatigue threshold range, and generate a cumulative vibration impact result.

7. The earthquake emergency disposal system for the automated production line according to claim 4, wherein The risk level determination sub-module includes: A multi-parameter fusion unit, which is used to extract the expected vibration amplitude, the degree of equipment damage risk and the cumulative vibration impact according to the process impact analysis data, and calculate a comprehensive risk score according to a preset weight factor; A fuzzy rule matching unit, which is used to input the comprehensive risk score into a fuzzy rule system, and infer the fuzzy risk level of each production process according to a preset fuzzy membership function and risk judgment rules; A risk level mapping unit, which is used to output a clear risk level label according to the clarification standard corresponding to the fuzzy risk level.

8. The earthquake emergency disposal system for the automated production line according to claim 5, wherein The structural response modeling unit includes: A structural parameter extraction sub-unit, which is used to extract the installation method, connection bracket configuration, component material type and mass distribution information of the device according to the device operation state data to form structural basic parameters; A modeling template selection sub-unit, which is used to select a matching template from a preset multi-type device structure modeling template according to the structural basic parameters, and the matching template includes a rigid structure model, a hierarchical structure model and a flexible connection model; A response model construction sub-unit, which is used to map the structural basic parameters into the matching template to construct a device structural response model including multi-degree-of-freedom vibration characteristics.

9. The earthquake emergency disposal system for the automated production line according to claim 5 or 8, characterized in that The dynamic threshold generation unit includes: A state factor matching sub-unit, which is used to construct a corresponding state factor vector based on the current operation mode, load level and historical abnormal records of the device; An empirical model fitting sub-unit, which is used to perform regression fitting on the state factor vector and historical vibration response data to establish a dynamic fitting function of the preliminary vibration trigger threshold; A threshold adaptive adjustment sub-unit, which is used to real-time correct the preliminary vibration trigger threshold according to the output result of the dynamic fitting function, the current state of the device and the feedback result of the device structural response model to generate the vibration trigger threshold corresponding to the device.

10. The earthquake emergency disposal system for the automated production line according to claim 6, wherein The fatigue trend analysis unit includes: A life modeling sub-unit, which is used to construct a service life model of the corresponding device according to the vibration tolerance parameters of the device, in combination with its material yield limit, structural deformation ability and operation historical data; A stress conversion sub-unit, which is used to convert the vibration cumulative influence value into an equivalent periodic stress sequence, map and compare it with the service life model, and generate the structural fatigue change trend; A trend evaluation sub-unit, which is used to calculate the fatigue life consumption ratio according to the structural fatigue change trend, and combine the vibration historical fluctuation range to predict the fatigue evolution path during the future operation of the device, and generate the structural fatigue trend data.

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