Emergency command system informatization guarantee system full life cycle management method and system

Abstract

The invention relates to an emergency command system informatization guarantee system full life cycle management method and system, and the method comprises the steps: obtaining the operation parameters and technical parameters of all equipment; at least one equipment influence factor is introduced, the fault rate and the service life of the equipment are predicted in combination with the operation parameters and the technical parameters of all the equipment, a fault rate change curve graph and a half-decay value of the equipment are obtained, and the service life residual value of each piece of equipment is determined; automatically scanning whether each device has an unexpected behavior or not, and performing corresponding correction operation on the device having the unexpected behavior; and when the unexpected formation of the equipment is not automatically solved and the service life residual value of the equipment is lower than a preset threshold value or is close to a half-decay value, sending an alarm prompt to a user side, and pushing an emergency disposal scheme to request a user to intervene in processing. The method has the remarkable beneficial effects of improving the operation efficiency of the system, accelerating the fault response speed, improving the fault prediction capability, reducing the maintenance cost and the like.

Description

Technical Field

[0001] The present invention relates to the field of computer information technology, and in particular to a full life cycle management method and system for an emergency command system information support system. Background Art

[0002] The information security system of the emergency command system is a highly integrated, multi-system coordinated complex network. In this type of system, a large number of information equipment of different models and specifications are widely used, ranging from more than one thousand to nearly ten thousand. The life cycles of these devices vary, making management extremely difficult. At present, the existing systems and technologies mainly focus on real-time monitoring of basic conditions such as temperature, voltage and alarm information of the equipment.

[0003] However, this monitoring method has obvious limitations. It cannot prejudge possible equipment failures and can only respond and handle them after the equipment actually fails. In this case, the failure of a single device is likely to cause the entire system to paralyze, seriously affecting the continuity and stability of emergency command.

[0004] In addition, when a fault occurs, the existing troubleshooting process is cumbersome and inefficient. It is usually necessary to analyze the fault phenomenon to identify the system that may have a problem, and then check and compare all the devices in the system one by one. This method is not only time-consuming and labor-intensive, but also difficult to quickly and accurately locate the faulty device. Even if the faulty device is found, further professional testing is required to determine the specific cause of the fault. Summary of the invention

[0005] 1. Technical issues to be resolved

[0006] In view of the above-mentioned shortcomings and deficiencies of the prior art, the present invention provides a full life cycle management method and system for an information security system of an emergency command system, which solves many deficiencies in the existing information security system of an emergency command system at the technical and management levels, such as low efficiency, slow fault response speed, lack of fault prediction capability, high maintenance cost and other technical problems.

[0007] (II) Technical solution

[0008] In order to achieve the above object, the main technical solutions adopted by the present invention include:

[0009] In a first aspect, an embodiment of the present invention provides a method for managing the entire life cycle of an information security system of an emergency command system, including:

[0010] Obtain the operating parameters and technical parameters of each device in the emergency command system information support system in real time;

[0011] Introduce at least one equipment influencing factor, combine the operating parameters and technical parameters of each equipment, predict the failure rate and life of the equipment, obtain the equipment failure rate change curve and half-decay value, and determine the remaining life value of each equipment;

[0012] Automatically scan each device for unexpected behavior, perform corresponding corrective actions on devices with unexpected behavior, and send automatic processing prompts to the user end;

[0013] When the unexpected formation of equipment is not automatically resolved, the remaining life value of the equipment is lower than the preset threshold or the half-life value is approaching, an alarm prompt is sent to the user end, and at least one emergency disposal plan is pushed to request user intervention to ensure that each equipment in the information support system of the emergency command system is within the set failure rate range.

[0014] Optionally, before obtaining the operating parameters and technical parameters of each device in the information support system of the emergency command system in real time, the method further includes:

[0015] Receive and analyze input business demand parameters, and combine them with the information in the equipment database to screen and combine equipment to develop equipment procurement plans;

[0016] Procurement of equipment through the preset procurement system according to the equipment procurement plan and recording of procurement information;

[0017] When new equipment enters the warehouse, it is registered, a unique equipment code is generated, and the new equipment information is entered;

[0018] In response to a user's request for use, the device is issued after approval according to preset conditions, and the deployment location information of the corresponding device is determined;

[0019] All devices are divided into several regional network groups according to their geographical locations, and the geographical coordinates, topological relationships and link structures of each device are established to form an information support system for the emergency command system, which is displayed to users in a visual way.

[0020] Optionally, after obtaining the operating parameters and technical parameters of each device in the emergency command system information support system in real time, the method further includes:

[0021] According to the geographical coordinates, topological relationship and link structure of the equipment, the status parameters and technical parameters collected by the sensor are classified and stored in the equipment database;

[0022] Sort the data stored in the device database and organize it into logical entities in the subject domain;

[0023] Construct the mapping relationship between logical entities and external devices to form a visual knowledge map for users to call in real time;

[0024] Create multiple independent virtual ports inside each device, each of which corresponds to a specific operating parameter or technical parameter and has a corresponding independent control mechanism;

[0025] Conduct simulation tests on all possible parameter combinations for each device, evaluate and compare the results, find the best parameter combination and deploy it on the corresponding device.

[0026] Optionally, at least one device influencing factor is introduced, and the failure rate and life of the device are predicted in combination with the operating parameters and technical parameters of each device, so as to obtain a failure rate variation curve and a half-decay value of the device, and determine the remaining life value of each device, including:

[0027] The obtained operating parameters and technical parameters of each device are preprocessed including cleaning to remove abnormal values, duplicate values ​​and missing values;

[0028] Extracting features associated with equipment failure rate and life span from the preprocessed data, and combining at least one equipment influencing factor to construct a composite feature that may affect the equipment failure rate and life span;

[0029] Select a machine learning algorithm to build a model for predicting equipment failure rate and lifespan, and use the constructed composite features as input, the equipment failure conditions and lifespan data as output labels to build a training data set;

[0030] Deploy the trained model to the production environment and use it to predict the failure rate and lifespan data of the equipment.

[0031] Based on the failure rate predicted by the model, draw a failure rate change curve according to the time series or equipment use stage;

[0032] Based on the failure rate change curve, determine the time point or usage stage corresponding to when the equipment performance drops to half of the initial performance, and obtain the half-life value;

[0033] According to the life data and failure rate change curve predicted by the model, the remaining life value of each device in the current state is estimated, and the key points of the life of each device, including the initial point when the device is put into use and the point where the performance drops to half, are located to form a life curve chart;

[0034] in,

[0035] Characteristics that correlate with equipment failure rate and equipment life include:

[0036] Time series characteristics of temperature / humidity fluctuation range:

[0037]

[0038] In the formula, x(t) is the original time series data, which represents the temperature / humidity value at time point t, a is the scale parameter, b is the displacement parameter, It is the mother wavelet function, which is used to convolve with the original time series data to extract the characteristics of the time series;

[0039] Distance characteristics of dynamic time warping:

[0040]

[0041] Where k is an alignment path between time series A and B, d(a i ,b j ) is point a in time series A i and point b in time series B j The distance between

[0042] Equipment influencing factors include: equipment usage time, maintenance records, workload, performance index ratio before and after maintenance, and performance index difference before and after maintenance;

[0043] The composite features are:

[0044]

[0045] In the formula, F1 is the first composite sub-feature, F2 is the second composite sub-feature, α i is the first weight coefficient, β i is the second weight coefficient, f i is the value of the i-th influencing factor.

[0046] Optionally, automatically scanning each device for unexpected behavior, performing corresponding corrective operations on the device with unexpected behavior, and sending an automatic processing prompt to the user terminal includes:

[0047] Standardize the collected operating parameters and technical parameters of each device;

[0048] Match the standardized parameters with the pre-defined rule set, and determine whether the device behavior is unexpected by comparing the data values, thresholds or conditions in the rule set;

[0049] When unexpected behavior is detected, corrective actions are automatically triggered, including restarting the device, restoring default configurations, shutting down abnormal processes, and updating software patches;

[0050] Generate automatic processing prompt information including unexpected behavior, corrective operation content and processing suggestions, and send the automatic processing prompt information to the user end in real time through a preset communication channel.

[0051] Optionally, when the unexpected formation of the equipment is not automatically resolved, the remaining life value of the equipment is lower than a preset threshold, or the half-life value is approaching, an alarm prompt is sent to the user terminal, and at least one emergency disposal plan is pushed to request the user to intervene and handle, ensuring that each device of the emergency command system information security system is in a set failure rate occurrence range, including:

[0052] When it is detected that the unexpected behavior of the device cannot be automatically resolved within the preset time, or the remaining life value of the device is lower than the preset threshold, or the half-life value of the device is approaching, the alarm condition is triggered;

[0053] Automatically generate alarm information including device identification, alarm type, description of triggering conditions and alarm occurrence time according to the triggered alarm conditions;

[0054] The alarm information is split into a word or phrase set, and a preliminary screening is performed in the emergency response solution library based on the word or phrase set in the alarm information to find solutions containing these keywords as a candidate solution set;

[0055] According to the remaining life value of the equipment, with reference to a preset acceptable range or threshold, at least one emergency disposal solution suitable for the current equipment life stage is selected from the candidate solution set;

[0056] The emergency response plan and alarm information are pushed to the user end so that the user can intervene in time;

[0057] Based on user feedback, update the status information of each device, including whether unexpected behaviors have been resolved, changes in the remaining life value and half-life value;

[0058] Continuously track the status of each device to ensure that each device in the emergency command system's information support system is always within the set failure rate range.

[0059] Optionally, it also includes:

[0060] Regularly evaluate each device based on the collected equipment failure rate, lifespan, and preset scrapping criteria;

[0061] Automatically identify devices that have reached scrap standards and update their status to pending scrapping in the system, so that users can physically isolate the corresponding devices;

[0062] Generate a scrapping analysis report containing equipment data throughout its entire life cycle, and output at least one disposal method based on the scrapping analysis report.

[0063] In a second aspect, an embodiment of the present invention provides a full life cycle management system for an emergency command system information support system, including:

[0064] Equipment database, used to store the operating parameters, technical parameters and equipment influencing factors of each device;

[0065] User terminal, used to display the visualized 3D image of the device to the user and receive the user's operation instructions and feedback information;

[0066] The backend management platform is connected to the equipment database and the user terminal respectively, and is used to execute the full life cycle management method of the emergency command system information support system as described above.

[0067] Optionally, the backend management platform includes:

[0068] Parameter acquisition module, used to obtain the operating parameters and technical parameters of each device in the information support system of the emergency command system in real time;

[0069] The failure rate and life prediction module is used to introduce at least one equipment influencing factor, combine the operating parameters and technical parameters of each equipment, predict the failure rate and life of the equipment, obtain the failure rate change curve and half-decay value of the equipment, and determine the remaining life value of each equipment;

[0070] The automatic correction module is used to automatically scan each device for unexpected behavior, perform corresponding correction operations on the device with unexpected behavior, and send automatic processing prompts to the user end;

[0071] The passive correction module is used to send an alarm to the user end when the unexpected formation of the equipment is not automatically resolved, the remaining life value of the equipment is lower than the preset threshold or the half-life value is approaching, and push at least one emergency response plan to request user intervention to ensure that each device in the information support system of the emergency command system is within the set failure rate range.

[0072] Optionally, the backend management platform also includes:

[0073] The equipment procurement module is used to receive and analyze the input business demand parameters, and screen and combine the equipment in combination with the information in the equipment database to formulate an equipment procurement plan; according to the equipment procurement plan, the equipment is purchased through the preset procurement system, and the procurement information is recorded;

[0074] The warehouse management module is used to register new equipment when it enters the warehouse, generate a unique equipment code, and enter the new equipment information;

[0075] The equipment allocation module is used to respond to the user's request for use, issue the equipment after approval according to the preset conditions, and determine the deployment location information of the corresponding equipment;

[0076] The device grouping module is used to divide all devices into several regional network groups according to their geographical locations, and establish the geographical coordinates, topological relationships and link structures of each device to form an information security system for the emergency command system, and display it to users in a visual way;

[0077] The scrap management module is used to conduct regular evaluation of each device based on the collected equipment failure rate, lifespan and preset scrap standards; automatically identify equipment that has reached the scrap standards and update the status to pending scrapping in the system so that users can physically isolate the corresponding equipment; generate a scrap analysis report containing equipment data for the entire life cycle, and output at least one disposal method based on the scrap analysis report.

[0078] (III) Beneficial effects

[0079] The beneficial effects of the present invention are:

[0080] The present invention first obtains the operating parameters and technical parameters of each device in the system in real time, which is the basis for ensuring efficient and stable operation of the system. By continuously monitoring these parameters, the working status of the equipment can be grasped in real time, and any abnormal situation of the equipment can be discovered in time, thereby greatly improving the speed of fault response. At the same time, it provides an accurate and reliable data source for subsequent data analysis and prediction.

[0081] Secondly, the present invention uses advanced data analysis and machine learning algorithms, combined with various influencing factors in equipment operation, to accurately predict the failure rate and life of the equipment. This can not only generate a failure rate change curve of the equipment and determine the half-decay value, but also clarify the remaining life value of each device. Such prediction capabilities are of great significance for preventing equipment failures and reasonably arranging maintenance plans, providing users with more accurate maintenance plans and extending the service life of the equipment.

[0082] In addition, the present invention also has the ability to automatically scan and correct unexpected device behaviors. Once an abnormality is found in the device, it can respond quickly, perform necessary corrective operations, and send automatic processing prompts to the user end. This automated fault handling mechanism can greatly reduce the need for manual intervention, improve the system's self-healing ability, and ensure the stable operation of the system at critical moments.

[0083] Finally, when a problem cannot be solved automatically, or the remaining life of the equipment is lower than the safety threshold, or the half-life value is about to be reached, an alarm will be sent to the user in a timely manner, and at least one emergency disposal plan will be provided. This early warning and emergency response mechanism can ensure that users understand the potential risks of the system at the first time and guide them to intervene effectively, thereby preventing the expansion of faults and ensuring that each device of the emergency command system information security system always operates within the set fault rate range. Overall, this method has a significant effect on improving the overall effectiveness and safety of the emergency command system.

[0084] Therefore, the full life cycle management solution for the information support system of the emergency command system provided by the present invention has shown significant beneficial effects in improving system operation efficiency, accelerating fault response speed, improving fault prediction capabilities and reducing maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0085] Figure 1 A flowchart of a method for managing the entire life cycle of an emergency command system information support system provided by an embodiment of the present invention;

[0086] Figure 2 A schematic diagram of a specific process before step S1 of a method for managing the entire life cycle of an information security system of an emergency command system provided by an embodiment of the present invention;

[0087] Figure 3 A schematic diagram of a specific process after step S1 of a full life cycle management method for an information security system of an emergency command system provided by an embodiment of the present invention;

[0088] Figure 4 A specific flow chart of step S2 of a method for managing the entire life cycle of an information-based support system for an emergency command system provided by an embodiment of the present invention;

[0089] Figure 5 A specific flow chart of step S3 of a method for managing the entire life cycle of an information-based support system for an emergency command system provided by an embodiment of the present invention;

[0090] Figure 6 A specific flow chart of step S4 of a method for managing the entire life cycle of an emergency command system information support system provided by an embodiment of the present invention

[0091] Figure 7 An overall logical schematic diagram of a full life cycle management method for an emergency command system information support system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0092] In order to better explain the present invention and facilitate understanding, the present invention is described in detail below through specific implementation modes in conjunction with the accompanying drawings.

[0093] like Figure 1 As shown, an embodiment of the present invention proposes a full life cycle management method for an emergency command system information security system, including: real-time acquisition of operating parameters and technical parameters of each device in the emergency command system information security system; introducing at least one device influencing factor, combining the operating parameters and technical parameters of each device, predicting the failure rate and life of the device, obtaining the failure rate change curve and half-decay value of the device, and determining the remaining life value of each device; automatically scanning whether each device has unexpected behavior, performing corresponding corrective operations on the device with unexpected behavior and sending automatic processing prompts to the user end; when the unexpected formation of the device is not automatically resolved, the remaining life value of the device is lower than the preset threshold or the half-decay value is approaching, sending an alarm prompt to the user end, and pushing at least one emergency disposal plan to request user intervention to ensure that each device in the emergency command system information security system is in the set failure rate occurrence range.

[0094] The present invention first obtains the operating parameters and technical parameters of each device in the system in real time, which is the basis for ensuring efficient and stable operation of the system. By continuously monitoring these parameters, the working status of the equipment can be grasped in real time, and any abnormal situation of the equipment can be discovered in time, thereby greatly improving the speed of fault response. At the same time, it provides an accurate and reliable data source for subsequent data analysis and prediction.

[0095] Secondly, the present invention uses advanced data analysis and machine learning algorithms, combined with various influencing factors in equipment operation, to accurately predict the failure rate and life of the equipment. This can not only generate a failure rate change curve of the equipment and determine the half-decay value, but also clarify the remaining life value of each device. Such prediction capabilities are of great significance for preventing equipment failures and reasonably arranging maintenance plans, providing users with more accurate maintenance plans and extending the service life of the equipment.

[0096] In addition, the present invention also has the ability to automatically scan and correct unexpected device behaviors. Once an abnormality is found in the device, it can respond quickly, perform necessary corrective operations, and send automatic processing prompts to the user end. This automated fault handling mechanism can greatly reduce the need for manual intervention, improve the system's self-healing ability, and ensure the stable operation of the system at critical moments.

[0097] Finally, when a problem cannot be solved automatically, or the remaining life of the equipment is lower than the safety threshold, or the half-life value is about to be reached, an alarm will be sent to the user in a timely manner, and at least one emergency disposal plan will be provided. This early warning and emergency response mechanism can ensure that users understand the potential risks of the system at the first time and guide them to intervene effectively, thereby preventing the expansion of faults and ensuring that each device of the emergency command system information security system always operates within the set fault rate range. Overall, this method has a significant effect on improving the overall effectiveness and safety of the emergency command system.

[0098] Therefore, the full life cycle management solution for the information support system of the emergency command system provided by the present invention has shown significant beneficial effects in improving system operation efficiency, accelerating fault response speed, improving fault prediction capabilities and reducing maintenance costs.

[0099] In order to better understand the above technical solution, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to enable a clearer and more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0100] Specifically, an embodiment of the present invention provides a method for managing the entire life cycle of an information security system of an emergency command system, including:

[0101] S1. Obtain the operating parameters and technical parameters of each device in the information support system of the emergency command system in real time.

[0102] Further, before step S1, Figure 2 As shown, it also includes:

[0103] F11. Receive and parse the input business demand parameters, and combine the information in the equipment database to screen and combine equipment to formulate an equipment procurement plan.

[0104] In this step, the business requirement parameters input by the user are received, including but not limited to equipment performance requirements, cost budget, scalability requirements, etc. The input parameters are parsed and converted into a format that can be processed by the system for subsequent equipment selection and recommendation.

[0105] Next, run the built-in intelligent selection algorithm, which screens and combines devices based on business demand parameters and information in the device database. The algorithm comprehensively considers multiple dimensions such as performance, cost, and scalability, and automatically recommends the optimal device combination through optimization algorithms (such as multi-objective optimization, genetic algorithms, etc.). At the same time, it integrates a dynamic budget management module that can monitor equipment market price fluctuations in real time. According to market price changes, dynamically adjust equipment costs and budget allocations to ensure that the selection plan is always within the budget.

[0106] For each recommended equipment combination, we evaluate the cost performance and calculate the cost performance index. Based on the cost performance evaluation results, we select the equipment combination with the highest cost performance as the optimal solution and output it to the user.

[0107] F12. Purchase equipment through the preset procurement system according to the equipment procurement plan and record the procurement information.

[0108] F13. When new equipment enters the warehouse, it is registered, a unique equipment code is generated, and the new equipment information is entered.

[0109] F14. In response to the user's request for use, the device is issued after approval according to the preset conditions, and the deployment location information of the corresponding device is determined.

[0110] F15. Divide all devices into several regional network groups according to their geographical locations, and establish the geographical coordinates, topological relationships, and link structures of each device to form an information security system for the emergency command system, and display it to users in a visual way.

[0111] Among them, geographic coordinates refer to the specific geographical location of each device, usually expressed as two values: longitude and latitude. Topology refers to the connection relationship or network layout between devices. It describes how devices are connected to each other and the overall structure formed by these connections. Link structure refers to the path and method of communication or data transmission between devices. It focuses on how information flows between different devices and the characteristics and quality of these paths. In complex network systems, understanding the link structure is crucial to optimizing data transmission and ensuring the stability of communication.

[0112] Further, after step S1, Figure 3 As shown, it also includes:

[0113] A11. Classify the status parameters and technical parameters collected by the sensor according to the geographical coordinates, topological relationship and link structure of the device, and store them in the device database.

[0114] A12. Sort the data stored in the device database and organize it into logical entities in the subject domain.

[0115] Select data related to a specific subject domain from the equipment database. For example, if the subject domain is "equipment failure", select the state parameters, technical parameters, and time and location of the failure related to the failure. Clean the selected data and aggregate the cleaned data according to a certain logic or rule. For example, the state parameters of the same equipment at different time points can be aggregated to form the state change trend of the equipment.

[0116] Define the corresponding logical entities based on the aggregated data. Logical entities should be able to reflect the essential characteristics of the data and the core concepts of the subject domain. For example, in the "equipment failure" subject domain, you can define logical entities such as "faulty equipment", "fault type", and "fault impact".

[0117] Determine the relationships between different logical entities. These relationships can be hierarchical, causal, associative, etc. For example, there may be a containment relationship between "faulty device" and "fault type", that is, a device may contain multiple fault types.

[0118] A13. Build a mapping relationship between logical entities and external devices to form a visual knowledge map for users to call in real time.

[0119] Determine the correspondence between logical entities and external devices. This correspondence can be one-to-one, one-to-many, or many-to-many. For example, a logical entity "faulty device" may correspond to multiple actual physical devices. Use visualization technology to graphically display logical entities, external devices, and the relationships between them to form a knowledge map. The knowledge map should be able to clearly display the associations and hierarchical structures between different entities and devices.

[0120] A14. Create multiple independent virtual ports inside each device, each of which corresponds to a specific operating parameter or technical parameter and has a corresponding independent control mechanism.

[0121] Inside each device, a corresponding number of virtual ports are created depending on the number of operating parameters and technical parameters that need to be monitored and controlled. These ports are logical, not physical, and they exist at the software or firmware level of the device. Each virtual port is associated with a specific operating parameter or technical parameter. For example, one port may be dedicated to monitoring the temperature of the device, while another port is used to control the operating speed of the device.

[0122] Next, design independent control mechanisms for each virtual port. These mechanisms allow specific parameters of the device to be read, written, or adjusted through the corresponding port. The implementation of the control mechanism may involve device drivers, embedded system programming, or network communication protocols.

[0123] In a specific example, let P be a set of operating parameters and technical parameters of the equipment, that is, P = {p1, p2, ..., p n}.

[0124] Let V be the set of virtual ports, that is, V = {v1, v2, ..., v n}.

[0125] There exists a one-to-one correspondence f:P→V such that every parameter p i Each has a unique virtual port v i Corresponding to it.

[0126] Each virtual port v i Each has an independent control mechanism i , which allows the parameter p i Read, write, or adjust.

[0127] A15. Perform simulation tests on all possible parameter combinations for each device, evaluate and compare the results, find the best parameter combination and deploy it on the corresponding device.

[0128] S2. Introduce at least one equipment influencing factor, combine the operating parameters and technical parameters of each equipment, predict the failure rate and life of the equipment, obtain the equipment failure rate change curve and half-decay value, and determine the remaining life value of each equipment.

[0129] Furthermore, if Figure 4 As shown, step S2 includes:

[0130] S21. Perform preprocessing including cleaning on the acquired operating parameters and technical parameters of each device to remove abnormal values, duplicate values ​​and missing values.

[0131] S22. Extract features associated with equipment failure rate and life span from the preprocessed data, and construct composite features that may affect equipment failure rate and life span by combining at least one equipment influencing factor.

[0132] S23. Select a machine learning algorithm to construct a model for predicting equipment failure rate and lifespan, and use the constructed composite features as input and the equipment failure conditions and lifespan data as output labels to construct a training data set.

[0133] Select a suitable algorithm from the existing machine learning algorithm library to build a prediction model for equipment failure rate and life. The selected algorithm should be able to handle multi-dimensional feature input and have good prediction performance. The algorithms considered may include but are not limited to: linear regression, logistic regression, support vector machine (SVM), random forest, gradient boosting tree (GBM), neural network, etc.

[0134] The extracted composite features are used as input, and the actual failure conditions and life data of the equipment are used as output labels to construct a training data set. The selected machine learning model is trained using the training data set. By adjusting the model parameters and optimizing the algorithm, the model can learn the mapping relationship between the input features and the output labels. During the training process, the model performance is monitored and evaluated using appropriate evaluation indicators (such as accuracy, recall, F1 score, etc.). The trained model is deployed to the production environment to predict the failure rate and life of the equipment in real time or regularly. According to the prediction results of the model, appropriate maintenance measures are taken or replacement plans are formulated to reduce the risk of equipment failure and extend the service life of the equipment.

[0135] S24. Deploy the trained model to the production environment, and use the trained model to predict the failure rate and life data of the equipment.

[0136] S25. Based on the failure rate predicted by the model, a failure rate variation curve is drawn according to the time series or equipment usage stage.

[0137] S26. Based on the failure rate variation curve, determine the time point or usage stage corresponding to when the equipment performance drops to half of the initial performance, and obtain the half-attenuation value.

[0138] S27. Estimate the remaining life value of each device in the current state based on the life data and failure rate change curve predicted by the model, and form a life curve by locating the key points of each device's life, including the initial point when the device is put into use and the point where the performance drops to half.

[0139] In a specific embodiment, the features associated with the equipment failure rate and equipment lifespan include: time series features of the fluctuation range of temperature and humidity and distance features of dynamic time curvature.

[0140] Use time series analysis technology to predict the normal fluctuation range of temperature / humidity. Then, calculate the deviation between the actual temperature and humidity data and the predicted value as the characteristic of abnormal fluctuation, and obtain the time series characteristics of the fluctuation range of temperature / humidity:

[0141]

[0142] In the formula, x(t) is the original time series data, which represents the temperature / humidity value at time point t, a is the scale parameter, b is the displacement parameter, It is the mother wavelet function, which is used to convolve with the original time series data to extract the characteristics of the time series.

[0143] By calculating the DTW distance between the current temperature and humidity pattern and the normal pattern, we can quantify the degree of abnormal fluctuation and obtain the distance characteristics of dynamic time bending:

[0144]

[0145] Where k is an alignment path between time series A and B, d(a i ,b j ) is point a in time series A i and point b in time series B j The distance between them; i and j are used as index variables to specify the sequence a i and b j The specific points in the image to be aligned or matched.

[0146] Equipment influencing factors include: equipment usage time, maintenance record, workload, performance index ratio before and after maintenance, and performance index difference before and after maintenance; equipment influencing factors can be expressed as a vector f = [f1, f2, ..., f n ], where f i is the value of the i-th influencing factor.

[0147] On the one hand, the time series features are combined with the equipment influencing factors to construct the first composite sub-feature:

[0148]

[0149] On the other hand, the distance feature of dynamic time bending is combined with the device influencing factor to construct the second composite sub-feature:

[0150]

[0151] Finally, we can combine the composite features F1 and F2 calculated above to obtain the final composite feature:

[0152]

[0153] In the formula, F1 is the first composite sub-feature, F2 is the second composite sub-feature, α i is the first weight coefficient, β i is the second weight coefficient, f i is the value of the i-th influencing factor. i , β i Determined through regression analysis, machine learning algorithms, or expert scoring.

[0154] This composite feature vector combines the wavelet transform of time series data, dynamic time warping distance and equipment influencing factors, and can be used for equipment failure prediction and life estimation.

[0155] S3. Automatically scan each device to see if there is any unexpected behavior, perform corresponding corrective operations on the device that has the unexpected behavior, and send an automatic processing prompt to the user end.

[0156] Furthermore, if Figure 5 As shown, step S3 includes:

[0157] S31. Standardize the collected operating parameters and technical parameters of each device.

[0158] S32. Match the standardized parameters with a predefined rule set, and determine whether the device behavior is unexpected by comparing the data values, thresholds or conditions in the rule set.

[0159] When device data exceeds the normal range defined by the rules, it is identified as unexpected behavior. Identification includes performance degradation, abnormally high resource consumption, frequent error log records, etc.

[0160] S33. When unexpected behavior is detected, corrective actions including restarting the device, restoring the default configuration, shutting down abnormal processes, and updating software patches are automatically triggered.

[0161] S34: Generate automatic processing prompt information including unexpected behavior, corrective operation content and processing suggestions, and send the automatic processing prompt to the user end in real time through a preset communication channel (such as email, SMS, APP push, etc.).

[0162] S4. When the unexpected formation of equipment is not automatically resolved, the remaining life value of the equipment is lower than the preset threshold or the half-life value is approaching, an alarm prompt is sent to the user end, and at least one emergency disposal plan is pushed to request user intervention to ensure that each equipment of the emergency command system information support system is within the set failure rate range.

[0163] Furthermore, if Figure 6 As shown, step S4 includes:

[0164] S41. When it is detected that the unexpected behavior of the device cannot be automatically resolved within the preset time, or the remaining life value of the device is lower than the preset threshold, or the half-life value of the device is approaching, an alarm condition is triggered.

[0165] S42. Automatically generate alarm information including device identification, alarm type, description of the triggering condition, and alarm occurrence time according to the triggered alarm condition.

[0166] S43, splitting the alarm information into a set of words or phrases, and performing a preliminary screening in the emergency response solution library based on the set of words or phrases in the alarm information to find solutions containing these keywords as a candidate solution set.

[0167] S44. Based on the remaining life value of the equipment and with reference to a preset acceptable range or threshold, at least one emergency disposal solution suitable for the current equipment life stage is selected from the candidate solution set.

[0168] In a specific embodiment, the alarm information A is mapped to a keyword set K through a function f1, and then the emergency disposal solution library P is searched for solutions containing these keywords to obtain a candidate solution set C. This process is expressed as:

[0169]

[0170] Where K is the keyword set obtained by splitting the alarm information A, and p is a solution in the emergency response solution library P.

[0171] Next, a function f2 is used to select the emergency disposal solution set S suitable for the current equipment life stage from the candidate solution set C according to the remaining life Lr of the equipment and a preset life range or threshold T, which can be expressed as:

[0172] S=f2(C,Lr,T)={c∈C|g(c,Lr,T)}

[0173] Wherein, g(c, Lr, T) is a judgment function used to determine whether solution c is applicable to the remaining life Lr of the current equipment and the preset life range or threshold T.

[0174] S45. Push the obtained emergency response plan and alarm information to the user terminal so that the user can intervene and handle it in time.

[0175] S46. Based on user feedback, update status information of each device including whether unexpected behaviors have been resolved, changes in the remaining life value and half-life value.

[0176] S47. Continuously track the status of each device to ensure that each device in the emergency command system's information support system is always within the set failure rate range.

[0177] In addition, after step S4, it also includes: regularly evaluating each device based on the collected failure rate, lifespan and preset scrapping standards of the equipment; automatically identifying equipment that reaches the scrapping standards, and updating the status to pending scrapping in the system so that users can physically isolate the corresponding equipment; generating a scrapping analysis report containing equipment data for the entire life cycle, and outputting at least one disposal method based on the scrapping analysis report.

[0178] refer to Figure 7, a comprehensive evaluation process was constructed to predict and manage the failure rate and life of equipment in the emergency command system information security system. It takes the individual design service life of all equipment in the emergency command system information security system as the base, the positive and negative variables of the temperature and humidity environment, the repaired faulty components, the overall high and low intensity operation time of the equipment as variables and influencing factors, and refers to the service life of the main chips and components. It estimates the overall failure rate change curve and half-life value of the emergency command system information security system, and locates the life curve of each independent individual device.

[0179] When the remaining life value is lower than 60% of the design service life or is about to reach the half-life value, a warning signal will be issued, marked with a prominent color in the equipment visualization 3D diagram, and linked to the SMS forecast platform to issue alarm information in advance to prompt replacement or maintenance, ensuring that the overall information support system of the emergency command system is in a low failure rate range.

[0180] In order to ensure the continuous and stable operation of the emergency command system information support system, we have also preset a variety of emergency response plans. When it is detected that the equipment needs to be replaced or maintained, it will automatically screen out suitable temporary connectivity support plans or suggestions. These plans are designed to ensure that during the equipment replacement or maintenance period, the emergency command system information support system can still be used uninterruptedly at all times, thereby meeting the continuity needs of emergency command.

[0181] In addition, an embodiment of the present invention provides a full life cycle management system for an emergency command system information support system, including:

[0182] The equipment database is used to store the operating parameters, technical parameters and equipment influencing factors of each equipment.

[0183] The present invention adopts relational database (such as MySQL, Oracle) or non-relational database (such as MongoDB, Cassandra), and selects according to the data volume, read-write performance requirements and scalability requirements. At the same time, a data table is designed to store detailed information of the equipment, including a basic information table of the equipment (equipment number, name, model, specification, purchase date, etc.), a purchase information table (supplier, purchase price, purchase contract, etc.), a usage record table (user, date of receipt, return date, etc.), a maintenance record table (maintenance date, maintenance content, maintenance personnel, etc.), and a scrapping information table (scrapping date, scrapping reason, disposal method, etc.). All kinds of unstructured data such as documents, pictures, videos related to the equipment are managed using a file system or object storage, and their storage paths are recorded in the database. A data backup and recovery mechanism is established to ensure the security and availability of data.

[0184] The user terminal is used to display the device's visualized 3D image to the user and receive the user's operation instructions and feedback information.

[0185] In the user terminal, a front-end application interface is specially designed. This interface is developed based on the Web or mobile terminal, aiming to provide managers and ordinary users with a simple and intuitive operation experience. In order to adapt to the screen sizes of different devices, a responsive layout is adopted to ensure a good user experience on various devices.

[0186] The user terminal is deployed with multiple functional modules. For example, the equipment query module supports users to quickly locate the required equipment information through keywords and screening conditions; the application module allows users to conveniently submit requests for equipment collection, maintenance, etc.; the approval module provides managers with efficient approval tools, who can easily approve applications and choose options such as agree, reject or return, and fill in approval opinions; the statistical report module displays key statistical data such as equipment usage status, maintenance costs, and scrap rates in the form of intuitive charts, helping users to better understand and manage equipment.

[0187] The backend management platform is connected to the equipment database and the user terminal respectively, and is used to execute the full life cycle management method of the emergency command system information support system as described above.

[0188] Furthermore, the backend management platform includes:

[0189] The parameter acquisition module is used to obtain the operating parameters and technical parameters of each device in the information support system of the emergency command system in real time.

[0190] The failure rate and life prediction module is used to use data analysis and machine learning algorithms to introduce at least one equipment influencing factor, combine the operating parameters and technical parameters of each device, predict the failure rate and life of the equipment, obtain the equipment's failure rate change curve and half-life value, and determine the remaining life value of each device.

[0191] The automatic correction module is used to automatically scan each device for unexpected behavior, perform corresponding corrective operations on the device with unexpected behavior, and send automatic processing prompts to the user end.

[0192] The passive correction module is used to send an alarm to the user end when the unexpected formation of the equipment is not automatically resolved, the remaining life value of the equipment is lower than the preset threshold or the half-life value is approaching, and push at least one emergency response plan to request user intervention to ensure that each device in the information support system of the emergency command system is within the set failure rate range.

[0193] In addition, the backend management platform also includes:

[0194] The equipment procurement module is used to receive and parse the input business demand parameters, and combine the equipment with the information in the equipment database to formulate an equipment procurement plan; according to the equipment procurement plan, equipment procurement is carried out through the preset procurement system, and procurement information is recorded.

[0195] The warehouse management module is used to register new equipment when it enters the warehouse, generate a unique equipment code, and enter the new equipment information.

[0196] The equipment allocation module is used to respond to the user's request for use, issue the equipment after approval according to preset conditions, and determine the deployment location information of the corresponding equipment.

[0197] The device grouping module is used to divide all devices into several regional network groups according to their geographical locations, and to establish the geographical coordinates, topological relationships and link structures of each device to form an information security system for the emergency command system, and to display it to users in a visual manner.

[0198] The scrap management module is used to conduct regular evaluation of each device based on the collected equipment failure rate, lifespan and preset scrap standards; automatically identify equipment that has reached the scrap standards and update the status to pending scrapping in the system so that users can physically isolate the corresponding equipment; generate a scrap analysis report containing equipment data for the entire life cycle, and output at least one disposal method based on the scrap analysis report.

[0199] In a specific embodiment, the background management platform builds a comprehensive equipment management system, covering the entire life cycle management from procurement to scrapping, mainly including the following functional modules:.

[0200] (1) Equipment procurement management module, which is responsible for formulating procurement plans based on equipment demand forecasts and current inventory status, maintaining supplier information and evaluating their performance, as well as creating and managing the execution of purchase orders.

[0201] (2) is the inventory management module, which handles the registration of newly purchased equipment and the real-time update of inventory quantity. It also manages the equipment outbound, including receipt and issuance, and ensures the accuracy of data through regular inventory counts.

[0202] (3) The allocation management module allocates devices to appropriate users based on user applications and business needs, and supports the smooth transfer of devices between different users.

[0203] (4) The maintenance management module formulates regular maintenance plans based on equipment type and usage status, receives and processes equipment failure repair applications, and records in detail all maintenance work content, related costs and maintenance personnel information.

[0204] (5) When the equipment reaches its service life or cannot be used anymore due to damage, the scrap management module will identify whether the equipment should be scrapped according to relevant standards and properly dispose of the scrapped equipment, such as recycling or destroying it, while recording the entire disposal process.

[0205] In order to more effectively support management decision-making, it is also equipped with:

[0206] (6) Data analysis module: This module deeply analyzes the usage, maintenance cost and scrapping trend of equipment, thus providing strong data support for decision-makers.

[0207] (7) Data collection and integration capability module, which can collect and integrate multi-source data from the equipment information database and various business modules to ensure data consistency and accuracy.

[0208] (8) Analysis model and algorithm module: With the help of advanced analysis models and algorithms, such as predictive analysis, cluster analysis, and cost analysis, the system can accurately predict equipment failures and lifespans, deeply analyze equipment usage patterns, and calculate maintenance and procurement costs in detail.

[0209] (9) Decision support module: In order to intuitively display the analysis results and support management decision-making, the system can generate various analysis reports and visual charts, covering key areas such as procurement decisions, maintenance strategy adjustments, and equipment update plans.

[0210] (10) Real-time monitoring and early warning. By real-time monitoring of key indicators such as equipment failure rate and inventory level, the system can issue early warning information in a timely manner when abnormal situations occur, thereby ensuring the continuous stability and efficient operation of equipment management.

[0211] To sum up, the embodiments of the present invention provide a full life cycle management method and method for an emergency command system information support system, covering each link of equipment planning, procurement, warehousing, collection, use, maintenance, and scrapping, realizing full process tracking and management of equipment, thereby achieving the purpose of reducing use costs and improving system stability and security.

[0212] During the planning stage, we carefully formulate equipment procurement plans based on business needs and development strategies to ensure that the selection and configuration of equipment can perfectly meet future usage needs.

[0213] Entering the procurement stage, we use a professional procurement system to execute equipment procurement and record all key information in the procurement process in detail to ensure the transparency and traceability of procurement.

[0214] When new equipment is put into storage, a strict registration procedure is carried out to generate a unique code for each device and enter its relevant information in detail, so as to establish a complete equipment file.

[0215] During the collection stage, we respond to users' collection applications, issue equipment after a strict approval process, and accurately record collection information to achieve clear tracking of equipment flow.

[0216] After the equipment is put into use, real-time monitoring is implemented to closely track the equipment's usage status and performance, including usage time, fault conditions, etc., to provide a strong basis for subsequent maintenance and management.

[0217] Entering the maintenance phase, scientifically arrange maintenance work based on the equipment maintenance plan and real-time fault reports, and record the maintenance content and results in detail to ensure that the equipment is always in good working condition.

[0218] When the equipment reaches the scrap standard, the standardized scrapping process is implemented, and the reasons for scrapping and disposal methods are recorded to achieve reasonable recovery of resources and proper protection of the environment.

[0219] It should be emphasized that the present invention collects important parameters such as the usage time of a single device, the type and number of faults, and intelligently compares data such as the attenuation curve of electronic components and the timeline of fault occurrence, thereby analyzing the possibility of equipment failure and issuing early warnings, reminding technical personnel to focus on strengthening inspections and be prepared to replace spare parts, and to replace or repair them at any time; at the same time, the present invention intelligently and comprehensively evaluates the overall usage status of the system, improves the overall safety and stability of the system, reduces construction costs and the number of useless spare parts, and ensures that efficient protection and strong technical support are provided for the command and decision-making of leaders at all levels at all times and in all domains.

[0220] Through this series of refined management measures, not only can the construction costs and the number of useless spare parts be effectively reduced, but it can also ensure that the system can provide efficient command decision-making guarantees and strong technical support for leaders at all levels at any time and any place.

[0221] Since the system / device described in the above embodiments of the present invention is a system / device used to implement the method of the above embodiments of the present invention, a person skilled in the art can understand the specific structure and deformation of the system / device based on the method described in the above embodiments of the present invention, and thus will not be described in detail here. All systems / devices used in the method of the above embodiments of the present invention belong to the scope of protection of the present invention.

[0222] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0223] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present invention. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions.

[0224] It should be noted that in the claims, any reference numerals placed between brackets shall not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claims. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The invention may be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In the claims enumerating several means, several of these means may be embodied by the same hardware. The use of the words first, second, third, etc., is for convenience of expression only and does not indicate any order. These words may be understood as part of the component name.

[0225] In addition, it should be noted that, in the description of this specification, the description of the terms "one embodiment", "some embodiments", "embodiment", "example", "specific example" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0226] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments after knowing the basic creative concept. Therefore, the claims should be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present invention.

[0227] Obviously, those skilled in the art can make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention should also include these modifications and variations.

Claims

1. A full life cycle management method for an emergency command system information support system, characterized in that: include: Obtain the operating parameters and technical parameters of each device in the emergency command system information support system in real time; Introduce at least one equipment influencing factor, combine the operating parameters and technical parameters of each equipment, predict the failure rate and life of the equipment, obtain the equipment failure rate change curve and half-decay value, and determine the remaining life value of each equipment; Automatically scan each device for unexpected behavior, perform corresponding corrective actions on devices with unexpected behavior, and send automatic processing prompts to the user end; When the unexpected formation of equipment is not automatically resolved, the remaining life value of the equipment is lower than the preset threshold or the half-life value is approaching, an alarm prompt is sent to the user end, and at least one emergency disposal plan is pushed to request user intervention to ensure that each equipment in the information support system of the emergency command system is within the set failure rate range.

2. The method for managing the entire life cycle of an information security system for an emergency command system according to claim 1, characterized in that: Before obtaining the operating parameters and technical parameters of each device in the emergency command system information support system in real time, it also includes: Receive and analyze input business demand parameters, and combine them with the information in the equipment database to screen and combine equipment to develop equipment procurement plans; Procurement of equipment through the preset procurement system according to the equipment procurement plan and recording of procurement information; When new equipment enters the warehouse, it is registered, a unique equipment code is generated, and the new equipment information is entered; In response to a user's request for use, the device is issued after approval according to preset conditions, and the deployment location information of the corresponding device is determined; All devices are divided into several regional network groups according to their geographical locations, and the geographical coordinates, topological relationships and link structures of each device are established to form an information support system for the emergency command system, which is displayed to users in a visual way.

3. The method for managing the entire life cycle of an information security system for an emergency command system as claimed in claim 2, characterized in that: After obtaining the operating parameters and technical parameters of each device in the emergency command system information support system in real time, it also includes: According to the geographical coordinates, topological relationship and link structure of the equipment, the status parameters and technical parameters collected by the sensor are classified and stored in the equipment database; Sort the data stored in the device database and organize it into logical entities in the subject domain; Construct the mapping relationship between logical entities and external devices to form a visual knowledge map for users to call in real time; Create multiple independent virtual ports inside each device, each of which corresponds to a specific operating parameter or technical parameter and has a corresponding independent control mechanism; Conduct simulation tests on all possible parameter combinations for each device, evaluate and compare the results, find the best parameter combination and deploy it on the corresponding device.

4. The method for managing the entire life cycle of an information security system for an emergency command system according to claim 1, characterized in that: Introduce at least one equipment influencing factor, combine the operating parameters and technical parameters of each equipment, predict the failure rate and life of the equipment, obtain the equipment failure rate change curve and half-decay value, and determine the remaining life value of each equipment, including: The obtained operating parameters and technical parameters of each device are preprocessed including cleaning to remove abnormal values, duplicate values ​​and missing values; Extracting features associated with equipment failure rate and life span from the preprocessed data, and combining at least one equipment influencing factor to construct a composite feature that may affect the equipment failure rate and life span; Select a machine learning algorithm to build a model for predicting equipment failure rate and lifespan, and use the constructed composite features as input, the equipment failure conditions and lifespan data as output labels to build a training data set; Deploy the trained model to the production environment and use it to predict the failure rate and lifespan data of the equipment. Based on the failure rate predicted by the model, draw a failure rate change curve according to the time series or equipment use stage; Based on the failure rate change curve, determine the time point or usage stage corresponding to when the equipment performance drops to half of the initial performance, and obtain the half-life value; According to the life data and failure rate change curve predicted by the model, the remaining life value of each device in the current state is estimated, and the key points of the life of each device, including the initial point when the device is put into use and the point where the performance drops to half, are located to form a life curve chart; in, Characteristics that correlate with equipment failure rate and equipment life include: Time series characteristics of temperature / humidity fluctuation range: In the formula, x(t) is the original time series data, which represents the temperature / humidity value at time point t, a is the scale parameter, b is the displacement parameter, It is the mother wavelet function, which is used to convolve with the original time series data to extract the characteristics of the time series; Distance characteristics of dynamic time warping: Where k is an alignment path between time series A and B, d(a i ,b j ) is point a in time series A i and point b in time series B j The distance between Equipment influencing factors include: equipment usage time, maintenance records, workload, performance index ratio before and after maintenance, and performance index difference before and after maintenance; The composite features are: In the formula, F1 is the first composite sub-feature, F2 is the second composite sub-feature, α i is the first weight coefficient, β i is the second weight coefficient, f i is the value of the i-th influencing factor.

5. The method for managing the entire life cycle of an information-based support system for an emergency command system according to claim 1, characterized in that: Automatically scan each device for unexpected behavior, perform corresponding corrective actions on devices with unexpected behavior, and send automatic processing prompts to the user end, including: Standardize the collected operating parameters and technical parameters of each device; Match the standardized parameters with the pre-defined rule set, and determine whether the device behavior is unexpected by comparing the data values, thresholds or conditions in the rule set; When unexpected behavior is detected, corrective actions are automatically triggered, including restarting the device, restoring default configurations, shutting down abnormal processes, and updating software patches; Generate automatic processing prompt information including unexpected behavior, corrective operation content and processing suggestions, and send the automatic processing prompt information to the user end in real time through a preset communication channel.

6. The method for managing the entire life cycle of an information-based support system for an emergency command system according to claim 1, characterized in that: When the unexpected formation of the equipment is not automatically resolved, the remaining life value of the equipment is lower than the preset threshold or the half-life value is approaching, an alarm prompt is sent to the user end, and at least one emergency disposal plan is pushed to request user intervention to ensure that each device of the emergency command system information support system is within the set failure rate range, including: When it is detected that the unexpected behavior of the device cannot be automatically resolved within the preset time, or the remaining life value of the device is lower than the preset threshold, or the half-life value of the device is approaching, the alarm condition is triggered; Automatically generate alarm information including device identification, alarm type, description of triggering conditions and alarm occurrence time according to the triggered alarm conditions; The alarm information is split into a word or phrase set, and a preliminary screening is performed in the emergency response solution library based on the word or phrase set in the alarm information to find solutions containing these keywords as a candidate solution set; According to the remaining life value of the equipment, with reference to a preset acceptable range or threshold, at least one emergency disposal solution suitable for the current equipment life stage is selected from the candidate solution set; The emergency response plan and alarm information are pushed to the user end so that the user can intervene in time; Based on user feedback, update the status information of each device, including whether unexpected behaviors have been resolved, changes in the remaining life value and half-life value; Continuously track the status of each device to ensure that each device in the emergency command system's information support system is always within the set failure rate range.

7. The method for managing the entire life cycle of an information-based support system for an emergency command system according to claim 1, characterized in that: Also includes: Regularly evaluate each device based on the collected equipment failure rate, lifespan, and preset scrapping criteria; Automatically identify devices that have reached scrap standards and update their status to pending scrapping in the system, so that users can physically isolate the corresponding devices; Generate a scrapping analysis report containing equipment data throughout its entire life cycle, and output at least one disposal method based on the scrapping analysis report.

8. A full life cycle management system for the information support system of an emergency command system, characterized in that: include: Equipment database, used to store the operating parameters, technical parameters and equipment influencing factors of each device; User terminal, used to display the visualized 3D image of the device to the user and receive the user's operation instructions and feedback information; The backend management platform is connected to the device database and the user terminal respectively, and is used to execute the full life cycle management method of the emergency command system information support system as described in any one of claims 1 to 7.

9. The emergency command system information support system full life cycle management system according to claim 8, characterized in that: The backend management platform includes: Parameter acquisition module, used to obtain the operating parameters and technical parameters of each device in the information support system of the emergency command system in real time; The failure rate and life prediction module is used to introduce at least one equipment influencing factor, combine the operating parameters and technical parameters of each equipment, predict the failure rate and life of the equipment, obtain the failure rate change curve and half-decay value of the equipment, and determine the remaining life value of each equipment; The automatic correction module is used to automatically scan each device for unexpected behavior, perform corresponding correction operations on the device with unexpected behavior, and send automatic processing prompts to the user end; The passive correction module is used to send an alarm to the user end when the unexpected formation of the equipment is not automatically resolved, the remaining life value of the equipment is lower than the preset threshold or the half-life value is approaching, and push at least one emergency response plan to request user intervention to ensure that each device in the information support system of the emergency command system is within the set failure rate range.

10. The emergency command system information support system full life cycle management system according to claim 8, characterized in that: The backend management platform also includes: The equipment procurement module is used to receive and analyze the input business demand parameters, and screen and combine the equipment in combination with the information in the equipment database to formulate an equipment procurement plan; according to the equipment procurement plan, the equipment is purchased through the preset procurement system, and the procurement information is recorded; The warehouse management module is used to register new equipment when it enters the warehouse, generate a unique equipment code, and enter the new equipment information; The equipment allocation module is used to respond to the user's request for use, issue the equipment after approval according to the preset conditions, and determine the deployment location information of the corresponding equipment; The device grouping module is used to divide all devices into several regional network groups according to their geographical locations, and establish the geographical coordinates, topological relationships and link structures of each device to form an information security system for the emergency command system, and display it to users in a visual way; The scrap management module is used to conduct regular evaluation of each device based on the collected equipment failure rate, lifespan and preset scrap standards; automatically identify equipment that has reached the scrap standards and update the status to pending scrapping in the system so that users can physically isolate the corresponding equipment; generate a scrap analysis report containing equipment data for the entire life cycle, and output at least one disposal method based on the scrap analysis report.

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