Electrical fault monitoring system for smart city

Abstract

The invention discloses an electrical fault monitoring system for a smart city. The electrical fault monitoring system comprises an electrical acquisition box, an edge gateway, an Internet of Things platform and a local large model. The electrical acquisition box can acquire environmental parameters and line current load characteristics; the edge gateway comprises a microcomputer and a communication module; the Internet of Things platform can perform bidirectional interaction with a local large model, can perform analysis, aggregation and permanent storage on received data, is integrated with a data visualization module, can dynamically display an electrochemical corrosion process of a line interface, and performs dynamic interaction with a user through a data large screen. According to the method, the load characteristics of the line are captured by using the current sensor, a mathematical model is established to predict the temperature change of the line in real time, the fire caused by line degradation is predicted, and visualization is performed through a digital twinborn technology subsequently.

Description

Technical Field

[0001] The present invention relates to the field of edge computing, and in particular to an electrical fault monitoring system for smart cities. Background Art

[0002] With the rapid development of smart cities, the efficiency of social operations has been greatly improved. However, electrical safety remains an important challenge. It not only affects the normal operation of public facilities, but also directly affects the quality of life of residents and the sustainable development of cities. With the advancement of technology, the field of electrical safety actively integrates modern technologies such as the Internet of Things, big data and artificial intelligence to ensure the normal operation of the power supply system under various environmental conditions and reduce accidents and disasters caused by electrical failures.

[0003] Line interfaces are prone to electrochemical corrosion in humid environments, a process that is mainly reflected in changes in resistance and increases in temperature. When electrochemical corrosion occurs, the resistance R gradually increases, causing the heat 𝑄 generated when current passes through the interface to increase accordingly. As time goes by, corrosion intensifies, and the heat caused by the current not only exceeds the heat dissipation capacity of the interface, but also causes the interface temperature to continue to rise, increasing the risk of fire. The continued increase in interface temperature not only affects the performance of electrical equipment, but also accelerates the aging and destruction of materials, forming a vicious cycle. For example: Line electrochemical corrosion can also lead to poor contact, local overheating and arc discharge, resulting in additional loss and instability of the line, further damaging the normal operation of the equipment. Therefore, it is particularly important to monitor and evaluate the electrochemical corrosion status of the line interface in a timely manner.

[0004] At present, there are some electrical fault monitoring technologies for smart cities on the market. For example, Chinese patent CN202410391517.1 discloses a smart city fire detection method, device and readable storage medium, which can identify and process small flames and smoke through a pre-trained fire detection model, achieve the technical effect of early warning of fire, and improve the real-time detection and emergency needs of fire safety supervision. However, the image discrimination-based method has obvious disadvantages, specifically: 1. Low accuracy: The accuracy of the camera is limited, and it is difficult to collect the degradation process of the line in humid air, and it cannot accurately measure the change trend of the cable diameter; 2. The scheme is not suitable for small spaces: In order to obtain high-definition images, the image acquisition process needs to be matched with a light source module, a power supply module and an image transmission module. However, the location where the line fire occurs is generally located in the power control box, and its space cannot effectively accommodate the camera system; 3. Poor timeliness: The scheme can only remedy the fire after it occurs, and inform the management personnel of the fire information in time through technologies such as the Internet of Things. The core purpose is not to avoid losses, but how to reduce losses, and the overall practicality is limited.

[0005] In order to reduce the risk of electrical failure and fire, we have developed an electrical failure monitoring system for smart cities, combining advanced sensing technology and intelligent algorithms to monitor the corrosion status and temperature changes of interfaces in real time. By analyzing the dynamic changes of resistance and temperature, the system can timely warn of potential dangers, greatly improve the safety of the line, and significantly reduce the risk of fire caused by electrochemical corrosion. Summary of the invention

[0006] In view of the above problems, the present invention provides an electrical fault monitoring system for smart cities, which uses current sensors to capture the load characteristics of the line, establishes a mathematical model to predict the temperature change of the line in real time, predicts the fire caused by line degradation, and then visualizes it through digital twin technology. It is characterized by comprising: an electrical acquisition box, an edge gateway, an Internet of Things platform and a local large model:

[0007] The electrical acquisition box includes a sensor acquisition module, a power management module, a microcontroller, a communication module, a signal conditioning circuit and an ADC module; the sensor acquisition module includes an environment acquisition module and a current acquisition module; the environment acquisition module includes a temperature and humidity sensor; the electrical acquisition box can support two power supply modes: lithium battery and Type-C. The power management module has a boost circuit that can convert the 3.7V power supply of the lithium battery into 5V; the microcontroller adopts the STM32L low-power chip; the communication module adopts a 485 interface to upload the data obtained by the sensor acquisition module to the edge gateway; the signal conditioning circuit includes a second-order filter circuit to effectively eliminate high-frequency noise; the ADC adopts a 24-bit chip;

[0008] The edge gateway includes a microcomputer and a communication module; the microcomputer has a 485 interface, which can receive data uploaded by the electrical acquisition box and obtain the ambient temperature, humidity and current amplitude; a mathematical model is established to quantify the degradation process and temperature change trend of the line and predict the life cycle of the line; the degradation process of the line describes the electrochemical corrosion of the cable interface in humid air, and its diameter Thinning, resistance and heat Increase; Over time, the electrochemical corrosion process continues to evolve, resulting in heat generated at the cable interface Greater than heat dissipation power , which causes the temperature of the entire structure to rise, eventually causing a fire. The specific process is as follows:

[0009] in The real-time temperature of the cable interface; is the specific heat capacity; is the heat dissipation power, The heat generated by the cable interface is:

[0010] in is the working current; for working hours; is the resistance of the cable interface, specifically:

[0011] in is the resistivity of the cable material, is the length of the cable interface, is the cross-sectional area of ​​the cable interface, specifically:

[0012] is the cable interface diameter, is the density of the cable material, Describe the quality of the cable after electrochemical corrosion, specifically:

[0013] is the initial mass, is the change in mass loss caused by electrochemical corrosion, specifically:

[0014] in is the model coefficient of electrochemical corrosion, a physical quantity that characterizes the mass loss rate of the cable interface. Indicates temperature, Indicates the ambient humidity. is the cable interface diameter; is the working time; heat dissipation power It can be expressed as:

[0015] in is the heat dissipation coefficient; is the cross-sectional area of ​​the cable interface; is the ambient temperature;

[0016] The IoT platform interacts bidirectionally with the edge gateway via the MQTT protocol; the IoT platform can analyze, aggregate and permanently store the received data; the IoT platform is integrated with a data visualization module, which can display the electrochemical corrosion process of the cable interface in a three-dimensional manner and dynamically interact with the user through a large data screen; the large data screen contains the load current of the line, the temperature and humidity of the environment, the cross-sectional area of ​​the cable interface, the resistance value and the predicted real-time temperature; the local IoT platform can issue instructions to actively query the status data of the cable interface;

[0017] The local large model can perform two-way data interaction with the Internet of Things platform; the Internet of Things platform transmits the ambient temperature, humidity, timestamp, cable physical size parameters, and historical load data obtained by the electrical acquisition box to the local large model to obtain the model coefficients of electrochemical corrosion , and finally sent to the edge gateway through the OTA module of the Internet of Things platform to realize intelligent monitoring of the line degradation process; the local big model adopts an open source big model, and obtains a local big model for smart city electrical fault monitoring through parameter fine-tuning-quantification-deployment; the parameter fine-tuning is based on the cable electrochemical corrosion dataset.

[0018] Furthermore, the steps for preparing the cable electrochemical corrosion dataset are as follows:

[0019] S1: Obtain the performance degradation process of the cable at different temperatures and humidities through standard experiments, and obtain the corresponding model coefficients ;

[0020] S2: Establish a numerical simulation model and fit the material parameters of the finite element model through the experimental results obtained in S1;

[0021] S3: Write script information and obtain the performance degradation process of cables under different temperatures and humidity through batch tasks;

[0022] S4: Create a standard database for the cable performance degradation process, including ambient temperature, ambient humidity and electrochemical corrosion rate. Establish data labels through manual annotation. The specific format is: [ { "timestamp":1694505600, "temperature": 35, "humidity": 65, "load_current": 5.5, "interface_diameter": 2.5, "resistance": 0.125, "interface_temperature": 45},......, { "timestamp": 1694516400, "temperature": 38, "humidity": 60, "load_current":4.5, "interface_diameter": 2.5, "resistance": 0.126, "interface_temperature":48}].

[0023] The advantages of the present invention are:

[0024] 1. Strong adaptability: The present invention uses current sensors to capture the load characteristics of the line and establishes a mathematical model to predict the temperature change of the line in real time. The overall solution does not require the modification of the existing electrical lines and has strong applicability and excellent cost performance;

[0025] 2. Low fire hazard: This solution can predict the fire risk in advance and predict the temperature change trend through the real-time resistance of the cable interface and the load of the line, effectively reducing the fire risk;

[0026] 3. Low cost: Compared with the degradation process of camera monitoring lines, this solution has the advantages of high accuracy, simple system and high cost performance, and can be applied to fire monitoring in small spaces and under weak light sources;

[0027] 4. Convenience: The present invention provides an online cable resistance measurement technology, which can obtain the change trend of the cable interface resistance when the power is on, thus avoiding the impact of power outages on the quality of life of residents. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of the present invention, and do not constitute a limitation of the embodiments of the present invention.

[0029] Figure 1 : An implementation framework for electrical fault monitoring systems for smart cities.

[0030] Figure 2 : A specific example of an electrical fire.

[0031] Figure 3 : Evolution of line resistance.

[0032] Figure 4 :Functional module of Internet of Things platform.

[0033] Figure 5 : Description method of electrical data collection box on Internet of Things platform.

[0034] Figure 6 :Deployment example of local AI large model. DETAILED DESCRIPTION

[0035] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments and drawings. The exemplary embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention.

[0036] Implementation Example 1

[0037] Attached Figure 1 The paper demonstrates an implementation framework of an electrical fault monitoring system for smart cities. It uses current sensors to capture the load characteristics of the line, establishes a mathematical model to predict the temperature change of the line in real time, and predicts the fire caused by line degradation. The digital twin technology is then used for visualization. The system is characterized by: electrical acquisition box, edge gateway, IoT platform and local large model:

[0038] The electrical acquisition box includes a sensor acquisition module, a power management module, a microcontroller, a communication module, a signal conditioning circuit and an ADC module; the sensor acquisition module includes an environment acquisition module and a current acquisition module; the environment acquisition module includes a temperature and humidity sensor; the electrical acquisition box can support two power supply modes: lithium battery and Type-C. The power management module has a boost circuit that can convert the 3.7V power supply of the lithium battery into 5V; the microcontroller adopts the STM32L low-power chip; the communication module adopts a 485 interface to upload the data obtained by the sensor acquisition module to the edge gateway; the signal conditioning circuit includes a second-order filter circuit to effectively eliminate high-frequency noise; the ADC adopts a 24-bit chip;

[0039] The edge gateway includes a microcomputer and a communication module; the microcomputer has a 485 interface, which can receive data uploaded by the electrical acquisition box and obtain the ambient temperature, humidity and current amplitude; a mathematical model is established to quantify the degradation process and temperature change trend of the line and predict the life cycle of the line; the degradation process of the line describes the electrochemical corrosion of the cable interface in humid air, and its diameter Thinning, resistance and heat Increase; Over time, the electrochemical corrosion process continues to evolve, resulting in heat generated at the cable interface Greater than heat dissipation power , which causes the temperature of the entire structure to rise, eventually causing a fire. The specific process is as follows:

[0040] in The real-time temperature of the cable interface; is the specific heat capacity; is the heat dissipation power, The heat generated by the cable interface is:

[0041] in is the working current; for working hours; is the resistance of the cable interface, specifically:

[0042] in is the resistivity of the cable material, is the length of the cable interface, is the cross-sectional area of ​​the cable interface, specifically:

[0043] is the cable interface diameter, is the density of the cable material, Describe the quality of the cable after electrochemical corrosion, specifically:

[0044] is the initial mass, is the change in mass loss caused by electrochemical corrosion, specifically:

[0045] in is the model coefficient of electrochemical corrosion, a physical quantity that characterizes the mass loss rate of the cable interface. Indicates temperature, Indicates the ambient humidity. is the cable interface diameter; is the working time; heat dissipation power It can be expressed as:

[0046] in is the heat dissipation coefficient; is the cross-sectional area of ​​the cable interface; is the ambient temperature;

[0047] Furthermore, the steps for making the cable electrochemical corrosion dataset are as follows:

[0048] S1: Obtain the performance degradation process of the cable at different temperatures and humidities through standard experiments, and obtain the corresponding model coefficients ;

[0049] S2: Establish a numerical simulation model and fit the material parameters of the finite element model through the experimental results obtained in S1;

[0050] S3: Write script information and obtain the performance degradation process of cables under different temperatures and humidity through batch tasks;

[0051] S4: Create a standard database for the cable performance degradation process, including ambient temperature, ambient humidity and electrochemical corrosion rate. Establish data labels through manual annotation. The specific format is: [ { "timestamp":1694505600, "temperature": 35, "humidity": 65, "load_current": 5.5, "interface_diameter": 2.5, "resistance": 0.125, "interface_temperature": 45},......, { "timestamp": 1694516400, "temperature": 38, "humidity": 60, "load_current":4.5, "interface_diameter": 2.5, "resistance": 0.126, "interface_temperature":48}].

[0052] Implementation Example 2

[0053] Attached Figure 2-3 A specific example of electrical fire is shown. As can be seen from the figure, the wires in the electrical control box are made of aluminum wires, and the contact pieces of the air switch are made of copper sheets. Electrochemical reactions will occur in humid air, making the wire diameter at the interface thinner and thinner, and the resistance and heat generation larger and larger, eventually exceeding the tolerance temperature of the rubber. This section uses specific examples to show the process of obtaining the temperature rise amplitude of the cable interface. By consulting the data and recording the working status of the electrical acquisition box, the known parameters are:

[0054] Initial diameter of cable interface : 2 mm;

[0055] Aluminum wire length : 0.02 m;

[0056] Aluminum wire density : 2700 kg / m³;

[0057] Resistivity of aluminum :2.65×10 −8 Ω⋅m;

[0058] Ambient temperature : 25°C;

[0059] Ambient humidity : 42%;

[0060] Working current: : 5 A;

[0061] Heat dissipation coefficient :10,000 W / (m²·K);

[0062] The specific calculation process is:

[0063] S1: Initial parameter calculation

[0064] Initial cross-sectional area of ​​the line for:

[0065] Initial Quality for:

[0066] When the ambient temperature and humidity do not change significantly, the large model can be used to obtain , after the cable has been used for 3 years, the quality loss caused by the electrochemical corrosion process is:

[0067] Final Quality for:

[0068] S2: Resistance change calculation

[0069] Initial resistance for:

[0070] After electrochemical corrosion, the diameter of the cable interface for:

[0071] S3: Steady-state temperature calculation: When the heat generated by the cable interface gradually increases, the structural temperature rises, and the heat dissipation power of the overall system also increases, eventually reaching a metastable state. The temperature at this time is:

[0072] Heat dissipation power Depends on the heat dissipation factor , Final cross-sectional area and temperature difference, specifically:

[0073] Finally, the steady-state temperature °C

[0074] Implementation Example 3

[0075] Attached Figure 4 The functional modules of the IoT platform are demonstrated. The IoT platform is the foundation for building smart factories and deploying artificial intelligence algorithms. The project combines years of engineering implementation experience and can meet the needs of industrial robots, smart factories, aerospace, and electric energy. The IoT platform interacts with the edge gateway in a two-way manner through the MQTT protocol; the IoT platform can analyze, aggregate, and permanently store the received data; the IoT platform is integrated with a data visualization module, which can display the electrochemical corrosion process of the cable interface in a three-dimensional way and interact dynamically with the user through a large data screen; the large data screen contains the load current of the line, the temperature and humidity of the environment, the cross-sectional area of ​​the cable interface, the resistance value, and the predicted real-time temperature; the local IoT platform can issue instructions to actively query the status data of the cable interface.

[0076] The left side of the IoT platform is the navigation bar, which includes the following functional modules:

[0077] 1. Home page;

[0078] 2. Equipment management: products, equipment, and groups;

[0079] 3. Operation and maintenance monitoring: OTA upgrade, remote configuration, online debugging, and log service;

[0080] 4. System management: user management, role management, menu list, interface management, and log management.

[0081] The IoT platform is written in go + python, and uses MySQL and TDengine databases, where MySQL is used to store relational data and TDengine is used to store time series data. The IoT platform uses MinIO as an object storage server to store unstructured data such as videos and files.

[0082] Attached Figure 5 The method of describing the electrical data acquisition box in the IoT platform is demonstrated, and the electrical data acquisition box is divided into status, archive information and function definition using the object model. The status mainly describes the working status of the electrical data acquisition box, including online, offline, activated and unactivated; the archive information mainly describes the device number, SN sequence code and MQTT connection triple information of the electrical data acquisition box; the function definition includes three types of electrical data acquisition box attributes, services and events. The object model is defined in the form of a super table in the IoT platform, with a total of 5 different data types, namely:

[0083] 1. Integer type (Int): can be used for linearly changing integer variables. For example, the ambient humidity is an integer range. The specific code for creating a table is: CREATE STABLE IF NOT EXISTS `model_custom_property_00b_int` (`ts` timestamp,`param` BIGINT) TAGS (`product_id` BINARY(50),`device_name` BINARY(50),`property_type` BINARY(50)).

[0084] 2. Float: Function point with floating point precision. For example, for online monitoring of current value, the specific code for creating a table is: CREATE STABLE IF NOT EXISTS `model_custom_property_00b_float` (`ts` timestamp,`param` DOUBLE) TAGS (`product_id` BINARY(50),`device_name` BINARY(50),`property_type` BINARY(50)).

[0085] 3. Timestamp: UTC timestamp of String type. The specific code for creating the table is: CREATE STABLE IF NOT EXISTS `model_custom_property_00b_timestamp` (`ts`timestamp,`param` TIMESTAMP) TAGS (`product_id` BINARY(50),`device_name`BINARY(50),`property_type` BINARY(50)).

[0086] 4. Bool: A binary variable that is either true or false. For example, the working status of an electrical data acquisition box has only two properties: on and off. The specific code for creating a table is: CREATE STABLE IF NOT EXISTS `model_custom_property_00b_bool` (`ts` timestamp,`param` BOOL) TAGS (`product_id` BINARY(50),`device_name` BINARY(50),`property_type` BINARY(50)).

[0087] 5. String: Functional points expressed in string form. For example, the notes of the electrical data acquisition box, describing how to use it, etc. The specific code for creating a table is: CREATE STABLE IF NOT EXISTS `model_custom_property_00b_string` (`ts` timestamp,`param` BINARY(5000)) TAGS (`product_id` BINARY(50),`device_name` BINARY(50),`property_type` BINARY(50)).

[0088] Implementation Example 4

[0089] The local large model can interact with the IoT platform in a two-way manner. The IoT platform transmits the ambient temperature, humidity, timestamp, cable physical size parameters, and historical load data obtained by the electrical acquisition box to the local large model to obtain the model coefficients of electrochemical corrosion. , and finally sent to the edge gateway through the OTA module of the Internet of Things platform to realize intelligent monitoring of the line degradation process; the local big model adopts an open source big model, and obtains a local big model for smart city electrical fault monitoring through parameter fine-tuning-quantification-deployment; the parameter fine-tuning is based on the cable electrochemical corrosion dataset.

[0090] Figure 6 The local AI big model fine-tuning, quantization, and deployment examples are shown. In recent years, artificial intelligence technology has achieved rapid development, and AI big models have gradually become one of the core technologies in various industries, with broad application potential in natural language processing, time series data processing, and medical fields. The deployment process of AI big models is as follows:

[0091] S1: Dataset construction: A standard material property database is established, including ambient temperature, ambient humidity and electrochemical corrosion rate. Data labels are established through manual annotation, specifically: [ { "timestamp":1694505600, "temperature": 35, "humidity": 65, "load_current": 5.5, "interface_diameter": 2.5, "resistance": 0.125, "interface_temperature": 45}, ..., { "timestamp": 1694516400, "temperature": 38, "humidity": 60, "load_current":4.5, "interface_diameter": 2.5, "resistance": 0.126, "interface_temperature":48}];

[0092] S2: Model fine-tuning: fine-tune the AI ​​model based on PEFT and perform quantitative operations;

[0093] S3: Local AI large model deployment: Install LM Studio software locally to load the model;

[0094] S4: Parameter adjustment and API service of AI big model: adjust the batch size, GPU load and Temperature parameters, open the API, and integrate the AI ​​big model with the local IoT platform. The reference code for the IoT platform to call the AI ​​big model is:

[0095] from openai import OpenAI

[0096] client = OpenAI(base_url="http: / / localhost:7500 / v1", api_key="lm-studio")

[0097] def get_embedding(text, model="model-identifier"):

[0098] text = text.replace("\n", " ")

[0099] return client.embeddings.create(input = [text], model=model).data[0].embedding

[0100] print(get_embedding("The 𝑘(T, H, d) is 9*10 -9 ."))

[0101] S5: Data delivery: The data is transmitted to the local IoT platform and then sent to the edge gateway via OTA upgrade, ultimately achieving online monitoring and early warning of electrical fires.

[0102] The specific implementation method described above provides a detailed description of the objectives, technical solutions and beneficial effects of the present invention. It should be understood that the above is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. An electrical fault monitoring system for smart cities, which uses current sensors to capture the load characteristics of the line, establishes a mathematical model to predict the temperature change of the line in real time, predicts the fire caused by line degradation, and then visualizes it through digital twin technology, characterized by: Includes: electrical collection box, edge gateway, IoT platform and local large model: The electrical acquisition box includes a sensor acquisition module, a power management module, a microcontroller, a communication module, a signal conditioning circuit and an ADC module; the sensor acquisition module includes an environment acquisition module and a current acquisition module; the environment acquisition module includes a temperature and humidity sensor; The edge gateway includes a microcomputer and a communication module; the microcomputer has a 485 interface, which can receive data uploaded by the electrical acquisition box and obtain the ambient temperature, humidity and current amplitude; a mathematical model is established to quantify the degradation process and temperature change trend of the line and predict the life cycle of the line; the degradation process of the line describes the electrochemical corrosion of the cable interface in humid air, and its diameter Thinning, resistance and heat Increase; Over time, the electrochemical corrosion process continues to evolve, resulting in heat generated at the cable interface Greater than heat dissipation power , which causes the temperature of the entire structure to rise, eventually causing a fire. The specific process is as follows: in The real-time temperature of the cable interface; is the specific heat capacity; is the heat dissipation power, The heat generated by the cable interface is: in is the working current; for working hours; is the resistance of the cable interface, specifically: in is the resistivity of the cable material, is the length of the cable interface, is the cross-sectional area of ​​the cable interface, specifically: is the cable interface diameter, is the density of the cable material, Describe the quality of the cable after electrochemical corrosion, specifically: is the initial mass, is the change in mass loss caused by electrochemical corrosion, specifically: in is the model coefficient of electrochemical corrosion, a physical quantity that characterizes the mass loss rate of the cable interface. Indicates temperature, Indicates the ambient humidity. is the cable interface diameter; is the working time; heat dissipation power It can be expressed as: in is the heat dissipation coefficient; is the cross-sectional area of ​​the cable interface; is the ambient temperature; The IoT platform interacts bidirectionally with the edge gateway via the MQTT protocol; the IoT platform can analyze, aggregate and permanently store the received data; the IoT platform is integrated with a data visualization module, which can display the electrochemical corrosion process of the cable interface in a three-dimensional manner and dynamically interact with the user through a large data screen; the large data screen contains the load current of the line, the temperature and humidity of the environment, the cross-sectional area of ​​the cable interface, the resistance value and the predicted real-time temperature; the local IoT platform can issue instructions to actively query the status data of the cable interface; The local large model can perform two-way data interaction with the Internet of Things platform; the Internet of Things platform transmits the ambient temperature, humidity, timestamp, cable physical size parameters, and historical load data obtained by the electrical acquisition box to the local large model to obtain the model coefficients of electrochemical corrosion , and finally sent to the edge gateway through the OTA module of the Internet of Things platform to realize intelligent monitoring of the line degradation process; the local big model adopts an open source big model, and obtains a local big model for smart city electrical fault monitoring through parameter fine-tuning-quantification-deployment; the parameter fine-tuning is based on the cable electrochemical corrosion dataset.

2. The electrical fault monitoring system for smart cities according to claim 1, characterized in that: The steps for making the cable electrochemical corrosion dataset are as follows: S1: Obtain the performance degradation process of the cable at different temperatures and humidities through standard experiments, and obtain the corresponding model coefficients ; S2: Establish a numerical simulation model and fit the material parameters of the finite element model through the experimental results obtained in S1; S3: Write script information and obtain the performance degradation process of cables under different temperatures and humidity through batch tasks; S4: Create a standard database for the cable performance degradation process, including ambient temperature, ambient humidity and electrochemical corrosion rate. Establish data labels through manual annotation. The specific format is: [ { "timestamp":1694505600, "temperature": 35, "humidity": 65, "load_current": 5.5, "interface_diameter": 2.5, "resistance": 0.125, "interface_temperature": 45},......, { "timestamp": 1694516400, "temperature": 38, "humidity": 60, "load_current":4.5, "interface_diameter": 2.5, "resistance": 0.126, "interface_temperature":48}].

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