Abnormality monitoring method and system for gas meter power adapter

Abstract

The present application relates to the technical field of power adapters, and in particular to a method and system for monitoring anomalies of a gas meter power adapter, the method comprising: obtaining assembly structure information, real-time application data, and real-time environment information, constructing a first adapter model according to the assembly structure information and the real-time application data, collecting first performance data, and mapping and binding the first performance data with the first adapter model to obtain a second adapter model, collecting second performance data and third performance data, and mapping and binding the second performance data and the third performance data with the second adapter model to obtain a third adapter model, determining whether there is an anomaly in the gas meter power adapter, and if so, performing an anomaly analysis on the gas meter power adapter to obtain a target anomaly set and a probability value corresponding to the target anomaly set. The present application improves the reliability and maintenance efficiency of the equipment and the user's equipment application experience.

Description

Technical Field

[0001] The present application relates to the technical field of power adapters, and in particular to an abnormality monitoring method and system for a gas meter power adapter. Background Art

[0002] With the widespread application of gas meters and their intelligent and networked development, the gas meter power adapter, as a key device connecting the power grid and the gas meter, its stability and reliability are crucial to ensuring the normal operation of the gas meter and user safety.

[0003] At present, the abnormal monitoring of gas meter power adapters mainly relies on basic electrical protection mechanisms, such as overcurrent protection, overvoltage protection, short circuit protection, etc. Although these protection mechanisms can prevent the power adapter from being damaged due to abnormalities to a certain extent, they cannot accurately know the root cause of the abnormality in the first time, and thus cannot accurately maintain the power adapter in a short time. In addition, when the user of the gas meter power adapter maintains it, it is necessary to spend a certain maintenance fee to find maintenance personnel to maintain the gas meter power adapter, thereby reducing the maintenance efficiency of the gas meter power adapter and the user application experience. Summary of the invention

[0004] In order to solve at least one of the above technical problems, the present application provides a method and system for monitoring an abnormality of a gas meter power adapter.

[0005] In a first aspect, the present application provides a method for monitoring an abnormality of a gas meter power adapter, which adopts the following technical solution:

[0006] Obtain assembly structure information, real-time application data, and real-time environmental information of the gas meter power adapter;

[0007] Constructing a first adapter model of the gas meter power adapter according to the assembly structure information and the real-time application data;

[0008] Collecting first performance data corresponding to different structures in the assembly structure information of the gas meter power adapter under different environmental parameter information after different application durations, and performing data mapping and binding with the first adapter model according to the structural correspondence, to obtain a second adapter model of the gas meter power adapter;

[0009] Collect the second performance data of different structures in the assembly structure information when different abnormalities occur and the third performance data of other structures that do not have abnormalities when different abnormalities occur, and perform data mapping and binding with the second adapter model according to the structural correspondence, so as to obtain the third adapter model of the gas meter power adapter;

[0010] Performing application security detection on the gas meter power adapter based on the real-time application data to determine whether the gas meter power adapter has an abnormality; if so, performing an abnormality analysis on the gas meter power adapter based on the third adapter model and the real-time environment information to obtain a target abnormality set and a probability value corresponding to the target abnormality set;

[0011] The target anomaly set and the probability value are bound and marked with the third adapter model according to the structural position, and the third adapter model after the binding mark is controlled to be displayed.

[0012] By adopting the above technical solution, the assembly structure information, real-time application data and real-time environmental information of the gas meter power adapter are obtained, which constitutes the basis for a comprehensive analysis of the performance and status of the gas meter power adapter, and provides detailed data support for the subsequent model construction. The first adapter model is constructed based on the assembly structure information and real-time application data, which realizes the preliminary simulation of the gas meter power adapter under normal working conditions and sets a benchmark for the subsequent performance change analysis. The first performance data of the gas meter power adapter after different environmental parameters and different application durations are collected, and the data is mapped and bound to the first adapter model to generate the second adapter model. This process fully considers the impact of environmental and application conditions on the performance of the power adapter, making the model closer to actual use and improving the accuracy of the analysis. The second performance data of different structures when abnormalities occur and the third performance data of non-abnormal structures are collected, and the data is mapped and bound to the second adapter model to obtain the third adapter model. By comparing the data under abnormal and normal conditions, the understanding of the abnormal behavior of the gas meter power adapter is deepened, providing more refined model support for abnormal analysis. Based on real-time application data, the gas meter power adapter is tested for application security, and the detected anomalies are deeply analyzed in combination with the third adapter model and real-time environmental information to obtain the target anomaly set and its probability value. The analysis method that combines real-time data with a refined model can quickly and accurately locate the root cause of the anomaly and improve the efficiency and accuracy of anomaly handling. The target anomaly set and its probability value are bound and marked with the third adapter model according to the structural position, and the bound marked model is controlled and displayed. This step intuitively displays the abnormal status and location of the gas meter power adapter, providing users with convenient troubleshooting and maintenance guidance, further improving the reliability and maintenance efficiency of the equipment and the user's equipment application experience.

[0013] In a possible implementation, the step of obtaining the assembly structure information, real-time application data, and real-time environment information of the gas meter power adapter further includes:

[0014] Determine whether the current application power of the gas meter power adapter is the preset application power based on the real-time application data; if it is the preset application power, monitor the current application power in real time to determine whether the current application power meets the application requirements of the gas meter power adapter;

[0015] If the current application power supply does not meet the application requirements of the gas meter power adapter, a backup power supply application instruction is generated to control the power input end of the gas meter power adapter to switch from the current application power supply to the backup application power supply.

[0016] In a possible implementation, the controlling the power input terminal of the gas meter power adapter to switch from the current application power supply to the backup application power supply also includes:

[0017] A power supply detection is performed on the backup application power supply to determine whether the remaining power of the backup application power supply meets the preset warning power range. If yes, power supply application abnormality information is generated and sent to the target terminal.

[0018] In a possible implementation manner, constructing a first adapter model of the gas meter power adapter according to the assembly structure information and the real-time application data includes:

[0019] Determine structural image information, structural material information and relative position information of different components of the gas meter power adapter according to the assembly structure information;

[0020] Performing object detection on the structural image information to obtain a node coordinate sequence of different components of the gas meter power adapter;

[0021] Determine a framework node coordinate sequence and an internal node coordinate sequence according to the node coordinate sequence;

[0022] The first node coordinate in the framework node coordinate sequence is used as the origin of the modeling three-dimensional coordinate system, the connecting line segment between the second node coordinate in the framework node coordinate sequence and the first node coordinate is used as the y-axis of the modeling three-dimensional coordinate system, the connecting line segment between the third node coordinate in the framework node coordinate sequence and the first node coordinate is used as the x-axis of the modeling three-dimensional coordinate system, and the connecting line segment between the fourth node coordinate in the framework node coordinate sequence and the first node coordinate is used as the z-axis of the modeling three-dimensional coordinate system;

[0023] Based on the relative position information, the remaining node coordinates in the frame node coordinate system sequence and the internal node coordinate sequence are mapped into the modeling three-dimensional coordinate system to obtain the frame model position corresponding to the frame node coordinate sequence and the internal model position corresponding to the internal node coordinate sequence;

[0024] Acquire a first component model corresponding to the structural image information in a preset model library;

[0025] Collecting material rendering effects corresponding to the structural material information in a preset standard material library, and rendering and updating the first component model based on the material rendering effects to obtain a second component model;

[0026] Binding the real-time application data to the second component model accordingly to obtain a third component model;

[0027] The third component model is assembled according to the position of the internal model to obtain the first adapter model of the gas meter power adapter.

[0028] In a possible implementation, performing application security detection on the gas meter power adapter based on the real-time application data to determine whether the gas meter power adapter is abnormal includes:

[0029] Acquire the abnormal data standard of the gas meter power adapter, and perform data security detection on the real-time application data based on the abnormal data standard to obtain a data security detection result;

[0030] It is determined whether there is an abnormality in the gas meter power adapter according to the data security detection result.

[0031] In a possible implementation, performing an abnormality analysis on the gas meter power adapter based on the third adapter model and the real-time environment information to obtain a target abnormality set and a probability value corresponding to the target abnormality set includes:

[0032] Determine the real-time application duration corresponding to the gas meter power adapter according to the real-time application data;

[0033] According to the real-time environment information and the real-time application duration, the environmental parameter information and the application duration corresponding to the first performance data in the third adapter model are matched to obtain characteristic performance data of different structures of the gas meter power adapter;

[0034] Inputting the characteristic performance data into a preset abnormality monitoring model for detection to obtain a structural abnormality probability corresponding to the characteristic performance data;

[0035] Determine whether the structural abnormality probability exceeds a preset abnormality probability; if so, match the abnormal structural position corresponding to the structural abnormality probability with the second performance data in the third adapter model and the structural position in the third performance data to obtain abnormal performance data of the abnormal structural position when different abnormalities occur and a set of associated data of other non-abnormal structures of the abnormal structural position when different abnormalities occur;

[0036] Binding the abnormal performance data and the associated data set according to the abnormality type to obtain multiple groups of performance data sets;

[0037] Determine abnormal feature data and normal feature data existing in the real-time application data based on the data security detection result, and compare the abnormal feature data and the normal feature data with each performance data set in the multiple performance data sets for similarity, to obtain a performance data set sequence whose similarity meets a preset similarity;

[0038] Data simplification and binding are performed on the performance data set sequence and the similarity corresponding to each performance data set in the performance data set sequence to obtain a target anomaly set and a probability value corresponding to the target anomaly set.

[0039] In a possible implementation, the performing application security detection on the gas meter power adapter based on the real-time application data to determine whether the gas meter power adapter is abnormal may also include:

[0040] Acquire the user's real-time behavior and user behavior criteria, wherein the user's real-time behavior is the real-time behavior corresponding to the user when applying any device related to the gas meter power adapter, and the user behavior criteria is the behavior actions allowed by the user under different environmental information of the gas meter power adapter;

[0041] Determining a user's standard behavior characteristics based on the user behavior criteria and the real-time environment information;

[0042] Determine a real-time behavior feature according to the real-time behavior of the user, and compare the real-time behavior feature with the standard behavior feature by Mahalanobis distance similarity to determine whether the real-time behavior feature has a feature anomaly; if so, generate an application behavior feature set corresponding to the feature anomaly according to the correlation between the real-time behavior feature and the standard behavior feature;

[0043] A behavior demonstration animation corresponding to the user's real-time behavior is generated based on the application behavior feature set and a preset behavior demonstration library.

[0044] In a second aspect, the present application provides an abnormality monitoring system for a gas meter power adapter, which adopts the following technical solution:

[0045] A gas meter power adapter abnormality monitoring system, comprising:

[0046] An information acquisition module, used to acquire assembly structure information, real-time application data and real-time environmental information of a gas meter power adapter;

[0047] A model building module, used for building a first adapter model of the gas meter power adapter according to the assembly structure information and the real-time application data;

[0048] A first model updating module is used to collect first performance data corresponding to different structures in the assembly structure information of the gas meter power adapter under different environmental parameter information after different application durations, and perform data mapping and binding with the first adapter model according to the structural correspondence, so as to obtain a second adapter model of the gas meter power adapter;

[0049] A second model updating module is used to collect second performance data of different structures in the assembly structure information when different abnormalities occur and third performance data of other structures that do not have abnormalities when different abnormalities occur, and perform data mapping and binding with the second adapter model according to the structural correspondence relationship, so as to obtain a third adapter model of the gas meter power adapter;

[0050] A device monitoring module, configured to perform application security detection on the gas meter power adapter based on the real-time application data, determine whether the gas meter power adapter has an abnormality, and if so, perform an abnormality analysis on the gas meter power adapter based on the third adapter model and the real-time environment information to obtain a target abnormality set and a probability value corresponding to the target abnormality set;

[0051] The control display module is used to bind and mark the target anomaly set and the probability value with the third adapter model according to the structural position, and control the display of the third adapter model after the binding mark.

[0052] In a possible implementation, the system further includes: a power monitoring module and a power switching module, wherein:

[0053] The power monitoring module is used to determine whether the current application power of the gas meter power adapter is the preset application power based on the real-time application data, and if it is the preset application power, monitor the current application power in real time to determine whether the current application power meets the application requirements of the gas meter power adapter;

[0054] The power switching module is used to generate a backup power application instruction when the current application power does not meet the application requirements of the gas meter power adapter, and control the power input end of the gas meter power adapter to switch from the current application power to the backup application power.

[0055] In another possible implementation, the system further includes: a power warning module, wherein:

[0056] The power warning module is used to perform power detection on the backup application power supply to determine whether the remaining power of the backup application power supply meets the preset warning power range. If yes, power application abnormality information is generated and sent to the target terminal.

[0057] In another possible implementation, when the model building module builds the first adapter model of the gas meter power adapter according to the assembly structure information and the real-time application data, it is specifically used to:

[0058] Determine structural image information, structural material information and relative position information of different components of the gas meter power adapter according to the assembly structure information;

[0059] Performing object detection on the structural image information to obtain a node coordinate sequence of different components of the gas meter power adapter;

[0060] Determine a framework node coordinate sequence and an internal node coordinate sequence according to the node coordinate sequence;

[0061] The first node coordinate in the framework node coordinate sequence is used as the origin of the modeling three-dimensional coordinate system, the connecting line segment between the second node coordinate in the framework node coordinate sequence and the first node coordinate is used as the y-axis of the modeling three-dimensional coordinate system, the connecting line segment between the third node coordinate in the framework node coordinate sequence and the first node coordinate is used as the x-axis of the modeling three-dimensional coordinate system, and the connecting line segment between the fourth node coordinate in the framework node coordinate sequence and the first node coordinate is used as the z-axis of the modeling three-dimensional coordinate system;

[0062] Based on the relative position information, the remaining node coordinates in the frame node coordinate system sequence and the internal node coordinate sequence are mapped into the modeling three-dimensional coordinate system to obtain the frame model position corresponding to the frame node coordinate sequence and the internal model position corresponding to the internal node coordinate sequence;

[0063] Acquire a first component model corresponding to the structural image information in a preset model library;

[0064] Collecting material rendering effects corresponding to the structural material information in a preset standard material library, and rendering and updating the first component model based on the material rendering effects to obtain a second component model;

[0065] Binding the real-time application data to the second component model accordingly to obtain a third component model;

[0066] The third component model is assembled according to the position of the internal model to obtain the first adapter model of the gas meter power adapter.

[0067] In another possible implementation, when the device monitoring module performs application security detection on the gas meter power adapter based on the real-time application data to determine whether the gas meter power adapter is abnormal, it is specifically used to:

[0068] Acquire the abnormal data standard of the gas meter power adapter, and perform data security detection on the real-time application data based on the abnormal data standard to obtain a data security detection result;

[0069] It is determined whether there is an abnormality in the gas meter power adapter according to the data security detection result.

[0070] In another possible implementation, when the device monitoring module performs an abnormality analysis on the gas meter power adapter based on the third adapter model and the real-time environmental information to obtain a target abnormality set and a probability value corresponding to the target abnormality set, it is specifically used to:

[0071] Determine the real-time application duration corresponding to the gas meter power adapter according to the real-time application data;

[0072] According to the real-time environment information and the real-time application duration, the environmental parameter information and the application duration corresponding to the first performance data in the third adapter model are matched to obtain characteristic performance data of different structures of the gas meter power adapter;

[0073] Inputting the characteristic performance data into a preset abnormality monitoring model for detection to obtain a structural abnormality probability corresponding to the characteristic performance data;

[0074] Determine whether the structural abnormality probability exceeds a preset abnormality probability; if so, match the abnormal structural position corresponding to the structural abnormality probability with the second performance data in the third adapter model and the structural position in the third performance data to obtain abnormal performance data of the abnormal structural position when different abnormalities occur and a set of associated data of other non-abnormal structures of the abnormal structural position when different abnormalities occur;

[0075] Binding the abnormal performance data and the associated data set according to the abnormality type to obtain multiple groups of performance data sets;

[0076] Determine abnormal feature data and normal feature data existing in the real-time application data based on the data security detection result, and compare the abnormal feature data and the normal feature data with each performance data set in the multiple performance data sets for similarity, to obtain a performance data set sequence whose similarity meets a preset similarity;

[0077] Data simplification and binding are performed on the performance data set sequence and the similarity corresponding to each performance data set in the performance data set sequence to obtain a target anomaly set and a probability value corresponding to the target anomaly set.

[0078] In another possible implementation, the system further includes: a behavior acquisition module, a feature determination module, a feature comparison module, and an animation generation module, wherein:

[0079] The behavior acquisition module is used to acquire the user's real-time behavior and user behavior criteria, wherein the user's real-time behavior is the real-time behavior corresponding to the user when applying any device related to the gas meter power adapter, and the user behavior criteria is the behavior actions allowed by the user under different environmental information of the gas meter power adapter;

[0080] The feature determination module is used to determine the user's standard behavior features based on the user behavior criteria and the real-time environment information;

[0081] The feature comparison module is used to determine the real-time behavior feature according to the real-time behavior of the user, and compare the real-time behavior feature with the standard behavior feature by Mahalanobis distance similarity to determine whether the real-time behavior feature has feature anomalies, and if so, generate an application behavior feature set corresponding to the feature anomaly according to the correlation between the real-time behavior feature and the standard behavior feature;

[0082] The animation generation module is used to generate a behavior demonstration animation corresponding to the user's real-time behavior based on the application behavior feature set and a preset behavior demonstration library.

[0083] In a third aspect, the present application provides an electronic device, which adopts the following technical solution:

[0084] at least one processor;

[0085] Memory;

[0086] At least one application, wherein at least one application is stored in a memory and configured to be executed by at least one processor, and at least one application is configured to: execute a method for monitoring an abnormality of a gas meter power adapter as described in any one of the first aspects.

[0087] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution:

[0088] A computer-readable storage medium stores a computer program, which, when executed in a computer, causes the computer to execute any method for monitoring an abnormality of a gas meter power adapter as described in the first aspect.

[0089] In summary, the present application includes at least one of the following beneficial technical effects:

[0090] By adopting the above technical solution, the assembly structure information, real-time application data and real-time environmental information of the gas meter power adapter are obtained, which constitutes the basis for a comprehensive analysis of the performance and status of the gas meter power adapter, and provides detailed data support for the subsequent model construction. The first adapter model is constructed based on the assembly structure information and real-time application data, which realizes the preliminary simulation of the gas meter power adapter under normal working conditions and sets a benchmark for the subsequent performance change analysis. The first performance data of the gas meter power adapter after different environmental parameters and different application durations are collected, and the data is mapped and bound to the first adapter model to generate the second adapter model. This process fully considers the impact of environmental and application conditions on the performance of the power adapter, making the model closer to actual use and improving the accuracy of the analysis. The second performance data of different structures when abnormalities occur and the third performance data of non-abnormal structures are collected, and the data is mapped and bound to the second adapter model to obtain the third adapter model. By comparing the data under abnormal and normal conditions, the understanding of the abnormal behavior of the gas meter power adapter is deepened, providing more refined model support for abnormal analysis. Based on real-time application data, the gas meter power adapter is tested for application security, and the detected anomalies are deeply analyzed in combination with the third adapter model and real-time environmental information to obtain the target anomaly set and its probability value. The analysis method that combines real-time data with a refined model can quickly and accurately locate the root cause of the anomaly and improve the efficiency and accuracy of anomaly handling. The target anomaly set and its probability value are bound and marked with the third adapter model according to the structural position, and the bound marked model is controlled and displayed. This step intuitively displays the abnormal status and location of the gas meter power adapter, providing users with convenient troubleshooting and maintenance guidance, further improving the reliability and maintenance efficiency of the equipment and the user's equipment application experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0091] Figure 1A flow chart of a method for monitoring an abnormality of a gas meter power adapter provided in an embodiment of the present application.

[0092] Figure 2 A schematic diagram of the structure of an abnormality monitoring system for a gas meter power adapter provided in an embodiment of the present application.

[0093] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0094] The following is combined with Figure 1-3 This application is described in further detail.

[0095] This specific embodiment is merely an explanation of the present application and is not a limitation of the present application. After reading this specification, a person skilled in the art may make non-creative modifications to the present embodiment as needed, but such modifications are protected by the patent law as long as they are within the scope of the present application.

[0096] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0097] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0098] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0099] The embodiment of the present application provides a method for monitoring an abnormality of a gas meter power adapter, which is performed by an electronic device, wherein the electronic device may be an independent physical electronic device, or an electronic device cluster or distributed system composed of multiple physical electronic devices, or a cloud electronic device providing cloud computing services. The embodiment of the present application is not limited here, such as Figure 1 As shown, the method includes:

[0100] Step S10: obtaining assembly structure information, real-time application data and real-time environment information of the gas meter power adapter.

[0101] For the embodiment of the present application, the assembly structure information refers to the detailed data of the physical properties such as the layout, connection method, material, etc. of each component inside the gas meter power adapter. This information is crucial for analyzing the performance of the adapter, predicting potential failures, and optimizing power supply efficiency. Real-time application data is used for data generated by different internal components of the gas meter power adapter during actual application, including but not limited to current, voltage, power consumption, operating temperature, etc. These data can reflect the real-time working status and performance of the gas meter power adapter. Real-time environmental information represents the external environmental conditions of the gas meter power adapter, such as temperature, humidity, air pressure, electromagnetic interference, etc. These factors have a direct or indirect impact on the performance and stability of the gas meter power adapter. Therefore, monitoring environmental information helps to ensure the normal operation of the gas meter power adapter.

[0102] Specifically, an IoT sensor is installed on the gas meter power adapter to monitor real-time application data and real-time environmental information such as current, voltage, and temperature. The sensor is then connected to the cloud server to achieve remote transmission and storage of data. The electronic device uses the powerful data processing capabilities of the cloud server to analyze and process the collected data and extract useful assembly structure information and performance parameters.

[0103] Step S11: construct a first adapter model of the gas meter power adapter according to the assembly structure information and the real-time application data.

[0104] For the embodiments of the present application, the structural image information, structural material information and relative position information of different parts of the gas meter power adapter are determined according to the assembly structure information, object target detection is performed on the structural image information, and the node coordinate sequence of the different parts of the gas meter power adapter is obtained. The framework node coordinate sequence and the internal node coordinate sequence are determined according to the node coordinate sequence, and the first node coordinate in the framework node coordinate sequence is used as the origin of the modeling three-dimensional coordinate system, and the connecting line segment between the second node coordinate and the first node coordinate in the framework node coordinate sequence is used as the y-axis of the modeling three-dimensional coordinate system, and the connecting line segment between the third node coordinate in the framework node coordinate sequence and the first node coordinate sequence is used as the x-axis of the modeling three-dimensional coordinate system, and the fourth node coordinate in the framework node coordinate sequence and the first node coordinate sequence are used as the origin of the modeling three-dimensional coordinate system. The connecting line segment between the coordinates is used as the z-axis of the modeling three-dimensional coordinate system. Based on the relative position information, the remaining node coordinates in the framework node coordinate system sequence and the internal node coordinate sequence are mapped to the modeling three-dimensional coordinate system to obtain the framework model position corresponding to the framework node coordinate sequence and the internal model position corresponding to the internal node coordinate sequence. The first component model corresponding to the structural image information in the preset model library is collected, and the material rendering effect corresponding to the structural material information in the preset standard material library is collected. The first component model is rendered and updated based on the material rendering effect to obtain the second component model, and the real-time application data is bound to the second component model to obtain the third component model. The third component model is assembled according to the internal model position to obtain the first adapter model of the gas meter power adapter.

[0105] Step S12: collect first performance data corresponding to different structures in the assembly structure information of the gas meter power adapter under different environmental parameter information after different application durations, and perform data mapping and binding with the first adapter model according to the structural correspondence to obtain a second adapter model of the gas meter power adapter.

[0106] Specifically, virtual simulation technology is used to simulate the working environment of the gas meter power adapter. In the simulation environment, different environmental parameter information is set, and a three-dimensional model of the gas meter power adapter is constructed. Through simulation operation, the performance data of different structures after different application durations are simulated. Subsequently, the performance data obtained by simulation is mapped and bound with the structural information in the three-dimensional model using the data processing function of the simulation software. Finally, a second adapter model file containing detailed performance data is exported.

[0107] Step S13, collecting the second performance data of different structures in the assembly structure information when different abnormalities occur and the third performance data of other structures that do not have abnormalities when different abnormalities occur, and mapping and binding the second performance data and the third performance data with the second adapter model according to the structural correspondence to obtain the third adapter model of the gas meter power adapter.

[0108] For the embodiment of the present application, a multi-parameter monitoring system is pre-deployed, which can monitor the various performance indicators of the gas meter power adapter in real time, including voltage, current, temperature, etc., as the basis for collecting the second and third performance data. Secondly, based on the monitored data, the data analysis software is used to automatically identify and classify the abnormal performance of different structures, and the second performance data is extracted. At the same time, for the structure where no abnormality occurs, its operating status during the abnormality occurs is recorded as the third performance data. Finally, through the programming interface or data exchange protocol, the collected data is automatically mapped to the second adapter model to generate the third adapter model.

[0109] Step S14: perform application security detection on the gas meter power adapter based on the real-time application data to determine whether there is an abnormality in the gas meter power adapter. If so, perform an abnormality analysis on the gas meter power adapter based on the third adapter model and real-time environmental information to obtain a target abnormality set and a probability value corresponding to the target abnormality set.

[0110] Specifically, the abnormal data standard of the gas meter power adapter is obtained, and the real-time application data is subjected to data security detection based on the abnormal data standard to obtain the data security detection result, and then the gas meter power adapter is judged whether there is an abnormality according to the data security detection result; the real-time application time corresponding to the gas meter power adapter is determined according to the real-time application data, and then the real-time environmental information and the real-time application time are matched with the environmental parameter information and the application time corresponding to the first performance data in the third adapter model to obtain the characteristic performance data of different structures of the gas meter power adapter, and the characteristic performance data is input into the preset abnormality monitoring model for detection to obtain the structural abnormality probability corresponding to the characteristic performance data, and then it is judged whether the structural abnormality probability exceeds the preset abnormality probability, and if it exceeds, the abnormal structure position corresponding to the structural abnormality probability is matched with the second performance data in the third adapter model. The data and the structural position in the third performance data are matched to obtain the abnormal performance data of the abnormal structural position when different abnormalities occur and the associated data set of other non-abnormal structures when different abnormalities occur in the abnormal structural position, the abnormal performance data and the associated data set are data-bound according to the abnormal type to obtain multiple groups of performance data sets, the abnormal feature data and the normal feature data existing in the real-time application data are determined based on the data security detection result, and the abnormal feature data and the normal feature data are respectively compared with each group of performance data sets in the multiple groups of performance data sets for similarity to obtain a performance data set sequence whose similarity meets the preset similarity, the performance data set sequence and the similarity corresponding to each performance data set in the performance data set sequence are data simplified and bound to obtain a target abnormal set and a probability value corresponding to the target abnormal set.

[0111] Step S15: Bind and mark the target anomaly set and the probability value with the third adapter model according to the structural position, and control the display of the third adapter model after the binding mark.

[0112] Specifically, when collecting real-time monitored power parameters within a preset time and determining whether an abnormal event has occurred in the real-time monitored power parameters based on the abnormal event monitoring standard, it includes: creating a real-time power event coordinate system, and mapping the real-time monitored power parameters to the real-time power event coordinate system according to the time nodes to obtain a real-time power waveform diagram, the X-axis of the real-time power event coordinate system is different time nodes, and the Y-axis of the real-time power event coordinate system is different power parameter values, collecting the highest critical value, the lowest critical value and the critical cycle time period corresponding to different peak change cycles in the real-time power waveform diagram, and calculating the difference between the highest critical value and the lowest critical value to obtain the real-time power difference corresponding to each peak change cycle, and then using the real-time power difference as the numerator and the duration corresponding to the critical cycle time period as the denominator to calculate to obtain the real-time power mean of the real-time power waveform diagram, and then matching the real-time power mean with the power change mean range in the event monitoring standard to determine whether an abnormal event has occurred in the real-time monitored power parameters corresponding to the real-time power mean.

[0113] In the embodiment of the present application, the assembly structure information, real-time application data and real-time environment information of the gas meter power adapter are obtained, which constitutes the basis for a comprehensive analysis of the performance and status of the gas meter power adapter, and provides detailed data support for subsequent model construction. The first adapter model is constructed according to the assembly structure information and real-time application data, which realizes the preliminary simulation of the gas meter power adapter under normal working conditions and sets a benchmark for subsequent performance change analysis. The first performance data of the gas meter power adapter after different environmental parameters and different application durations are collected, and the data is mapped and bound to the first adapter model to generate a second adapter model. This process fully considers the impact of environmental and application conditions on the performance of the power adapter, making the model closer to actual use and improving the accuracy of the analysis. The second performance data of different structures when abnormalities occur and the third performance data of non-abnormal structures are collected, and the data is mapped and bound to the second adapter model to obtain the third adapter model. By comparing the data in abnormal and normal states, the understanding of the abnormal behavior of the gas meter power adapter is deepened, and a more refined model support is provided for abnormal analysis. Based on the real-time application data, the gas meter power adapter is subjected to application security detection, and the detected anomalies are deeply analyzed in combination with the third adapter model and the real-time environment information to obtain the target anomaly set and its probability value. The analysis method that combines real-time data with refined models can quickly and accurately locate the root cause of abnormalities and improve the efficiency and accuracy of abnormality handling. The target abnormality set and its probability value are bound and marked with the third adapter model according to the structural position, and the bound and marked model is controlled and displayed. This step intuitively displays the abnormal status and location of the gas meter power adapter, providing users with convenient troubleshooting and maintenance guidance, further improving the reliability and maintenance efficiency of the equipment and the user's equipment application experience.

[0114] A possible implementation method of an embodiment of the present application obtains assembly structure information, real-time application data and real-time environmental information of the gas meter power adapter, and then also includes: determining whether the current application power supply of the gas meter power adapter is the preset application power supply based on the real-time application data; if it is the preset application power supply, real-time monitoring of the current application power supply is performed to determine whether the current application power supply meets the application requirements of the gas meter power adapter; if the current application power supply does not meet the application requirements of the gas meter power adapter, generating a backup power supply application instruction to control the power input terminal of the gas meter power adapter to switch from the current application power supply to the backup application power supply.

[0115] In addition, the power input end of the gas meter power adapter is controlled to switch from the current application power supply to the backup application power supply, which also includes: performing power detection on the backup application power supply to determine whether the remaining power of the backup application power supply meets the preset warning power range. If yes, power application exception information is generated and sent to the target terminal.

[0116] A possible implementation method of the embodiment of the present application is to perform application security detection on the gas meter power adapter based on real-time application data to determine whether there is an abnormality in the gas meter power adapter, and the previous method also includes: obtaining the user's real-time behavior and user behavior criteria, wherein the user's real-time behavior is the real-time behavior corresponding to the user when applying any device related to the gas meter power adapter, and the user behavior criteria is the behavioral actions allowed by the user under different environmental information of the gas meter power adapter, and the user's standard behavior characteristics are determined based on the user behavior criteria and the real-time environmental information, and then the real-time behavior characteristics are determined according to the user's real-time behavior, and the real-time behavior characteristics are compared with the standard behavior characteristics by Mahalanobis distance similarity to determine whether there is a feature abnormality in the real-time behavior characteristics. If so, based on the correlation between the real-time behavior characteristics and the standard behavior characteristics, an application behavior feature set corresponding to the feature abnormality is generated, and then a behavior demonstration animation corresponding to the user's real-time behavior is generated based on the application behavior feature set and a preset behavior demonstration library.

[0117] For the embodiment of the present application, the real-time behavior of the user represents the immediate and continuous sequence of behavioral actions generated by the user when using any device related to the gas meter power adapter (such as a mobile phone APP, a control panel, etc.). These behaviors can be operation instructions, clicks, slides, inputs, etc., which can reflect the user's operation intention and status in real time. User behavior criteria refer to the behavioral norms or allowed behavioral action sets that users should follow when using the gas meter power adapter under different environmental information (such as temperature, humidity, voltage stability, etc.). These criteria are intended to ensure the safety of user operations and the normal operation of the equipment. Real-time environmental information refers to the specific environmental conditions in which the gas meter power adapter is currently located, such as parameters such as temperature, humidity, voltage, and current of the surrounding environment. Standard behavior features are a set of behavioral features that users should have under normal operation, which are obtained through analysis and synthesis based on user behavior criteria and real-time environmental information. These features represent the standard behavior patterns of users who follow the behavioral criteria and under specific environmental conditions. Real-time behavior features extract the behavioral feature set of users at the current time point or time period by directly observing and recording the real-time behavior of users. These features reflect the current actual operation status of the user. Mahalanobis distance similarity comparison is a statistical method for measuring the similarity between two feature data points. In the embodiment of the present application, it is used to compare the similarity between the real-time behavior features and the standard behavior features to determine whether the user's real-time behavior conforms to the expected standard behavior pattern. Feature abnormality means that after the Mahalanobis distance similarity comparison, it is found that there is a significant difference between the real-time behavior features and the standard behavior features, indicating that the user's real-time behavior may deviate from the normal behavior pattern. The application behavior feature set is a series of normal behavior features related to abnormal behavior that are sorted out based on the correlation between the real-time behavior features and the standard behavior features when feature abnormalities are detected. The preset behavior demonstration library is a database containing a variety of standard or example behavior animations, which is used to provide users with behavior guidance or demonstrations when needed. The behavior demonstration animation is an animation generated based on the application behavior feature set and the preset behavior demonstration library, which is used to intuitively display the user's real-time behavior and the abnormal parts therein, to help users understand and correct improper operations.

[0118] The following is an introduction to an abnormality monitoring system for a gas meter power adapter provided in an embodiment of the present application. The abnormality monitoring system for a gas meter power adapter described below and the abnormality monitoring method for a gas meter power adapter described above can be referred to in correspondence with each other. Please refer to Figure 2 , Figure 2 : is a structural diagram of an abnormality monitoring system 20 for a gas meter power adapter provided in an embodiment of the present application, including:

[0119] The information acquisition module 21 is used to acquire the assembly structure information, real-time application data and real-time environment information of the gas meter power adapter;

[0120] A model building module 22, used to build a first adapter model of the gas meter power adapter according to the assembly structure information and the real-time application data;

[0121] The first model updating module 23 is used to collect first performance data corresponding to different structures in the assembly structure information of the gas meter power adapter under different environmental parameter information after different application durations, and perform data mapping and binding with the first adapter model according to the structural correspondence, so as to obtain a second adapter model of the gas meter power adapter;

[0122] The second model updating module 24 is used to collect second performance data of different structures in the assembly structure information when different abnormalities occur and third performance data of other structures that do not have abnormalities when different abnormalities occur, and perform data mapping and binding with the second adapter model according to the structural correspondence, so as to obtain a third adapter model of the gas meter power adapter;

[0123] The device monitoring module 25 is used to perform application security detection on the gas meter power adapter based on the real-time application data, determine whether the gas meter power adapter has an abnormality, and if so, perform an abnormality analysis on the gas meter power adapter based on the third adapter model and the real-time environment information to obtain a target abnormality set and a probability value corresponding to the target abnormality set;

[0124] The control display module 26 is used to bind and mark the target abnormality set and the probability value with the third adapter model according to the structural position, and control the display of the third adapter model after the binding mark.

[0125] In a possible implementation of the embodiment of the present application, the system 20 further includes: a power monitoring module and a power switching module, wherein:

[0126] A power monitoring module is used to determine whether the current application power of the gas meter power adapter is the preset application power based on real-time application data. If it is the preset application power, the current application power is monitored in real time to determine whether the current application power meets the application requirements of the gas meter power adapter;

[0127] The power switching module is used to generate a backup power application instruction when the current application power does not meet the application requirements of the gas meter power adapter, and control the power input end of the gas meter power adapter to switch from the current application power to the backup application power.

[0128] In another possible implementation of the embodiment of the present application, the system 20 further includes: a power warning module, wherein:

[0129] The power warning module is used to perform power detection on the backup application power supply to determine whether the remaining power of the backup application power supply meets the preset warning power range. If yes, power application abnormality information is generated and sent to the target terminal.

[0130] In another possible implementation, when the model building module 22 builds the first adapter model of the gas meter power adapter according to the assembly structure information and the real-time application data, it is specifically used to:

[0131] Determine structural image information, structural material information and relative position information of different parts of the gas meter power adapter according to the assembly structure information;

[0132] Perform object detection on the structural image information to obtain the node coordinate sequence of different parts of the gas meter power adapter;

[0133] Determine the frame node coordinate sequence and the internal node coordinate sequence according to the node coordinate sequence;

[0134] The first node coordinate in the framework node coordinate sequence is used as the origin of the modeling three-dimensional coordinate system, the connecting line segment between the second node coordinate and the first node coordinate in the framework node coordinate sequence is used as the y-axis of the modeling three-dimensional coordinate system, the connecting line segment between the third node coordinate in the framework node coordinate sequence and the first node coordinate sequence is used as the x-axis of the modeling three-dimensional coordinate system, and the connecting line segment between the fourth node coordinate in the framework node coordinate sequence and the first node coordinate is used as the z-axis of the modeling three-dimensional coordinate system;

[0135] Based on the relative position information, the remaining node coordinates in the frame node coordinate system sequence and the internal node coordinate sequence are mapped to the modeling three-dimensional coordinate system to obtain the frame model position corresponding to the frame node coordinate sequence and the internal model position corresponding to the internal node coordinate sequence;

[0136] Acquire a first component model corresponding to the structural image information in a preset model library;

[0137] Collecting material rendering effects corresponding to the structural material information in a preset standard material library, and rendering and updating the first component model based on the material rendering effects to obtain a second component model;

[0138] Binding the real-time application data to the second component model accordingly to obtain a third component model;

[0139] The third component model is assembled according to the position of the internal model to obtain a first adapter model of the gas meter power adapter.

[0140] In another possible implementation of the embodiment of the present application, the device monitoring module 25 performs application security detection on the gas meter power adapter based on real-time application data to determine whether the gas meter power adapter is abnormal, specifically for:

[0141] Acquire the abnormal data standard of the gas meter power adapter, and perform data security detection on the real-time application data based on the abnormal data standard to obtain the data security detection result;

[0142] Determine whether there is any abnormality in the gas meter power adapter based on the data security test results.

[0143] In another possible implementation of the embodiment of the present application, the device monitoring module 25 performs an abnormality analysis on the gas meter power adapter based on the third adapter model and the real-time environmental information to obtain a target abnormality set and a probability value corresponding to the target abnormality set, specifically for:

[0144] Determine the real-time application duration corresponding to the gas meter power adapter according to the real-time application data;

[0145] According to the real-time environment information and the real-time application duration, the environment parameter information and the application duration corresponding to the first performance data in the third adapter model are matched to obtain characteristic performance data of different structures of the gas meter power adapter;

[0146] Input the characteristic performance data into a preset abnormality monitoring model for detection, and obtain the structural abnormality probability corresponding to the characteristic performance data;

[0147] Determine whether the structural abnormality probability exceeds the preset abnormality probability. If so, match the abnormal structure position corresponding to the structural abnormality probability with the second performance data in the third adapter model and the structure position in the third performance data to obtain the abnormal performance data of the abnormal structure position when different abnormalities occur and the associated data set of other abnormal structures that do not occur when different abnormalities occur at the abnormal structure position;

[0148] Bind the abnormal performance data and the associated data sets according to the abnormal type to obtain multiple groups of performance data sets;

[0149] Based on the data security detection result, abnormal feature data and normal feature data existing in the real-time application data are determined, and the abnormal feature data and the normal feature data are respectively compared with each performance data set in the multiple performance data sets for similarity, so as to obtain a performance data set sequence whose similarity meets the preset similarity;

[0150] Data simplification and binding are performed on the performance data set sequence and the similarity corresponding to each performance data set in the performance data set sequence to obtain a target anomaly set and a probability value corresponding to the target anomaly set.

[0151] In another possible implementation of the embodiment of the present application, the system 20 further includes: a behavior acquisition module, a feature determination module, a feature comparison module, and an animation generation module, wherein:

[0152] The behavior acquisition module is used to acquire the user's real-time behavior and user behavior criteria. The user's real-time behavior is the real-time behavior corresponding to the user when applying any device related to the gas meter power adapter. The user behavior criteria are the behavioral actions allowed by the user under different environmental information of the gas meter power adapter;

[0153] A feature determination module, used to determine the user's standard behavior features based on the user's behavior criteria and real-time environmental information;

[0154] A feature comparison module is used to determine the real-time behavior features according to the real-time behavior of the user, and compare the real-time behavior features with the standard behavior features by Mahalanobis distance similarity to determine whether there are feature anomalies in the real-time behavior features. If there are, then based on the correlation between the real-time behavior features and the standard behavior features, a set of application behavior features corresponding to the feature anomalies is generated;

[0155] The animation generation module is used to generate a behavior demonstration animation corresponding to the user's real-time behavior based on the application behavior feature set and the preset behavior demonstration library.

[0156] The present application embodiment provides an electronic device, such as Figure 3 As shown, Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application, Figure 3 The electronic device 300 shown includes: a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, such as through a bus 302. Optionally, the electronic device 300 may also include a transceiver 304. It should be noted that in actual applications, the transceiver 304 is not limited to one, and the structure of the electronic device 300 does not constitute a limitation on the embodiments of the present application.

[0157] The processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of the embodiments of the present application. The processor 301 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.

[0158] The bus 302 may include a path to transmit information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0159] The memory 303 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0160] The memory 303 is used to store application code for executing the solution of the embodiment of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the content shown in the above method embodiment.

[0161] Among them, electronic devices include but are not limited to: mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 3 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0162] A computer-readable storage medium provided in an embodiment of the present application is introduced below. The computer-readable storage medium described below and the method described above can be referenced to each other.

[0163] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned method for monitoring an abnormality of a gas meter power adapter are implemented.

[0164] Since the embodiments of the computer-readable storage medium part and the embodiments of the method part correspond to each other, the embodiments of the computer-readable storage medium part refer to the description of the embodiments of the method part.

[0165] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0166] The above are only some implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for monitoring abnormality of a gas meter power adapter, characterized in that: include: Obtain assembly structure information, real-time application data, and real-time environmental information of the gas meter power adapter; Constructing a first adapter model of the gas meter power adapter according to the assembly structure information and the real-time application data; The step of constructing a first adapter model of the gas meter power adapter according to the assembly structure information and the real-time application data includes: Determine structural image information, structural material information and relative position information of different components of the gas meter power adapter according to the assembly structure information; Performing object detection on the structural image information to obtain a node coordinate sequence of different components of the gas meter power adapter; Determine a framework node coordinate sequence and an internal node coordinate sequence according to the node coordinate sequence; The first node coordinate in the framework node coordinate sequence is used as the origin of the modeling three-dimensional coordinate system, the connecting line segment between the second node coordinate in the framework node coordinate sequence and the first node coordinate is used as the y-axis of the modeling three-dimensional coordinate system, the connecting line segment between the third node coordinate in the framework node coordinate sequence and the first node coordinate is used as the x-axis of the modeling three-dimensional coordinate system, and the connecting line segment between the fourth node coordinate in the framework node coordinate sequence and the first node coordinate is used as the z-axis of the modeling three-dimensional coordinate system; Based on the relative position information, the remaining node coordinates in the frame node coordinate system sequence and the internal node coordinate sequence are mapped into the modeling three-dimensional coordinate system to obtain the frame model position corresponding to the frame node coordinate sequence and the internal model position corresponding to the internal node coordinate sequence; Acquire a first component model corresponding to the structural image information in a preset model library; Collecting material rendering effects corresponding to the structural material information in a preset standard material library, and rendering and updating the first component model based on the material rendering effects to obtain a second component model; Binding the real-time application data to the second component model accordingly to obtain a third component model; Assembling the third component model according to the position of the internal model to obtain a first adapter model of the gas meter power adapter; Collecting first performance data corresponding to different structures in the assembly structure information of the gas meter power adapter under different environmental parameter information after different application durations, and performing data mapping and binding with the first adapter model according to the structural correspondence, to obtain a second adapter model of the gas meter power adapter; Collect the second performance data of different structures in the assembly structure information when different abnormalities occur and the third performance data of other structures that do not have abnormalities when different abnormalities occur, and perform data mapping and binding with the second adapter model according to the structural correspondence, so as to obtain the third adapter model of the gas meter power adapter; Performing application security detection on the gas meter power adapter based on the real-time application data to determine whether the gas meter power adapter has an abnormality; if so, performing an abnormality analysis on the gas meter power adapter based on the third adapter model and the real-time environment information to obtain a target abnormality set and a probability value corresponding to the target abnormality set; The target anomaly set and the probability value are bound and marked with the third adapter model according to the structural position, and the third adapter model after the binding mark is controlled to be displayed.

2. The method for monitoring abnormality of a gas meter power adapter according to claim 1, characterized in that: The step of obtaining the assembly structure information, real-time application data and real-time environment information of the gas meter power adapter further includes: Determine whether the current application power of the gas meter power adapter is the preset application power based on the real-time application data; if it is the preset application power, monitor the current application power in real time to determine whether the current application power meets the application requirements of the gas meter power adapter; If the current application power supply does not meet the application requirements of the gas meter power adapter, a backup power supply application instruction is generated to control the power input end of the gas meter power adapter to switch from the current application power supply to the backup application power supply.

3. The method for monitoring abnormality of a gas meter power adapter according to claim 2, characterized in that: The step of controlling the power input terminal of the gas meter power adapter to switch from the current application power supply to the standby application power supply also includes: A power supply detection is performed on the backup application power supply to determine whether the remaining power of the backup application power supply meets the preset warning power range. If yes, power supply application abnormality information is generated and sent to the target terminal.

4. The method for monitoring abnormality of a gas meter power adapter according to claim 1, characterized in that: The performing application security detection on the gas meter power adapter based on the real-time application data to determine whether the gas meter power adapter is abnormal includes: Acquire the abnormal data standard of the gas meter power adapter, and perform data security detection on the real-time application data based on the abnormal data standard to obtain a data security detection result; It is determined whether there is an abnormality in the gas meter power adapter according to the data security detection result.

5. The method for monitoring abnormality of a gas meter power adapter according to claim 4, characterized in that: The performing anomaly analysis on the gas meter power adapter based on the third adapter model and the real-time environment information to obtain a target anomaly set and a probability value corresponding to the target anomaly set includes: Determine the real-time application duration corresponding to the gas meter power adapter according to the real-time application data; According to the real-time environment information and the real-time application duration, the environment parameter information and the application duration corresponding to the first performance data in the third adapter model are matched to obtain characteristic performance data of different structures of the gas meter power adapter; Inputting the characteristic performance data into a preset abnormality monitoring model for detection to obtain a structural abnormality probability corresponding to the characteristic performance data; Determine whether the structural abnormality probability exceeds a preset abnormality probability; if so, match the abnormal structural position corresponding to the structural abnormality probability with the second performance data in the third adapter model and the structural position in the third performance data to obtain abnormal performance data of the abnormal structural position when different abnormalities occur and a set of associated data of other non-abnormal structures of the abnormal structural position when different abnormalities occur; Binding the abnormal performance data and the associated data set according to the abnormality type to obtain multiple groups of performance data sets; Determine abnormal feature data and normal feature data existing in the real-time application data based on the data security detection result, and compare the abnormal feature data and the normal feature data with each performance data set in the multiple performance data sets for similarity, to obtain a performance data set sequence whose similarity meets a preset similarity; Data simplification and binding are performed on the performance data set sequence and the similarity corresponding to each performance data set in the performance data set sequence to obtain a target anomaly set and a probability value corresponding to the target anomaly set.

6. The method for monitoring abnormality of a gas meter power adapter according to claim 1, characterized in that: The performing application security detection on the gas meter power adapter based on the real-time application data to determine whether the gas meter power adapter has an abnormality, further includes: Acquire the user's real-time behavior and user behavior criteria, wherein the user's real-time behavior is the real-time behavior corresponding to the user when applying any device related to the gas meter power adapter, and the user behavior criteria is the behavior actions allowed by the user under different environmental information of the gas meter power adapter; Determining a user's standard behavior characteristics based on the user behavior criteria and the real-time environment information; Determine a real-time behavior feature according to the real-time behavior of the user, and compare the real-time behavior feature with the standard behavior feature by Mahalanobis distance similarity to determine whether the real-time behavior feature has a feature anomaly; if so, generate an application behavior feature set corresponding to the feature anomaly according to the correlation between the real-time behavior feature and the standard behavior feature; A behavior demonstration animation corresponding to the user's real-time behavior is generated based on the application behavior feature set and a preset behavior demonstration library.

7. An abnormality monitoring system for a gas meter power adapter, characterized in that: include: An information acquisition module, used to acquire assembly structure information, real-time application data and real-time environmental information of a gas meter power adapter; A model building module, used for building a first adapter model of the gas meter power adapter according to the assembly structure information and the real-time application data; When the model building module builds the first adapter model of the gas meter power adapter according to the assembly structure information and the real-time application data, it is specifically used to: Determine structural image information, structural material information and relative position information of different components of the gas meter power adapter according to the assembly structure information; Performing object detection on the structural image information to obtain a node coordinate sequence of different components of the gas meter power adapter; Determine a framework node coordinate sequence and an internal node coordinate sequence according to the node coordinate sequence; The first node coordinate in the framework node coordinate sequence is used as the origin of the modeling three-dimensional coordinate system, the connecting line segment between the second node coordinate in the framework node coordinate sequence and the first node coordinate is used as the y-axis of the modeling three-dimensional coordinate system, the connecting line segment between the third node coordinate in the framework node coordinate sequence and the first node coordinate is used as the x-axis of the modeling three-dimensional coordinate system, and the connecting line segment between the fourth node coordinate in the framework node coordinate sequence and the first node coordinate is used as the z-axis of the modeling three-dimensional coordinate system; Based on the relative position information, the remaining node coordinates in the frame node coordinate system sequence and the internal node coordinate sequence are mapped into the modeling three-dimensional coordinate system to obtain the frame model position corresponding to the frame node coordinate sequence and the internal model position corresponding to the internal node coordinate sequence; Acquire a first component model corresponding to the structural image information in a preset model library; Collecting material rendering effects corresponding to the structural material information in a preset standard material library, and rendering and updating the first component model based on the material rendering effects to obtain a second component model; Binding the real-time application data to the second component model accordingly to obtain a third component model; Assembling the third component model according to the position of the internal model to obtain a first adapter model of the gas meter power adapter; A first model updating module is used to collect first performance data corresponding to different structures in the assembly structure information of the gas meter power adapter under different environmental parameter information after different application durations, and perform data mapping and binding with the first adapter model according to the structural correspondence, so as to obtain a second adapter model of the gas meter power adapter; A second model updating module is used to collect second performance data of different structures in the assembly structure information when different abnormalities occur and third performance data of other structures that do not have abnormalities when different abnormalities occur, and perform data mapping and binding with the second adapter model according to the structural correspondence relationship, so as to obtain a third adapter model of the gas meter power adapter; A device monitoring module, configured to perform application security detection on the gas meter power adapter based on the real-time application data, determine whether the gas meter power adapter has an abnormality, and if so, perform an abnormality analysis on the gas meter power adapter based on the third adapter model and the real-time environment information to obtain a target abnormality set and a probability value corresponding to the target abnormality set; The control display module is used to bind and mark the target anomaly set and the probability value with the third adapter model according to the structural position, and control the display of the third adapter model after the binding mark.

8. An electronic device, characterized in that: The electronic device includes: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute an abnormality monitoring method for a gas meter power adapter according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that: include: A computer program is stored which can be loaded by a processor and executes a method for monitoring an abnormality of a gas meter power adapter as described in any one of claims 1 to 6.

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