Fire safety management system for electrical circuits

Abstract

The invention discloses an electrical circuit fire safety management system, and relates to the technical field of electrical circuit safety. The invention comprises an electrical control module, a centralized analysis module, an early warning processing module, an emergency power-off module and a user interface; the electrical control module is used for real-time monitoring of current, voltage, temperature and other parameters of different electrical devices of the user; the electrical devices to be monitored and their characteristics are determined, and corresponding current, voltage and temperature sensors are configured for each electrical device; the invention significantly improves the safety of electrical circuits through an integrated monitoring and analysis method, can monitor key parameters such as current, voltage and temperature of electrical devices in real time, and adopts advanced data analysis technology to identify potential fire risks. Compared with traditional fire alarm systems, the system can achieve early warning, promptly notify users to take preventive measures, effectively reduce the occurrence of fire accidents, and protect people's lives and property.

Description

Technical Field

[0001] The present invention relates to the technical field of electrical circuit safety, in particular to an electrical circuit fire safety management system. Background Art

[0002] In the field of electrical circuit safety technology, existing electrical circuit fire safety management systems mostly adopt a single or decentralized monitoring method, lacking the ability to uniformly monitor and manage all the user's electrical appliances. These systems can often only monitor some parameters, such as current or temperature, but cannot comprehensively analyze the operating status of electrical equipment. Existing systems have limitations in data collection and analysis, and often alarm only after a fire occurs. There is a lack of effective early warning mechanisms, and it is impossible to achieve early detection and prevention of fire risks;

[0003] As the degree of electrification in society increases, the use of electrical equipment becomes more and more widespread, and the resulting fire risk is also increasing. Electrical fires not only cause huge economic losses, but may also cause personal injuries. Therefore, there is an urgent need for a safety management system that can monitor the status of electrical equipment in real time, accurately warn of fire risks, and take timely measures.

[0004] In order to solve the above defects, a technical solution is now provided. Summary of the invention

[0005] The purpose of the present invention is to solve the problems of decentralized monitoring, insufficient early warning mechanism and untimely response measures in the existing electrical circuit fire safety management system, and to propose an electrical circuit fire safety management system.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] Electrical circuit fire safety management system, including:

[0008] The electrical control module is used to monitor the operating parameters of different electrical equipment of the user in real time. The specific process is as follows:

[0009] Determine the electrical equipment to be monitored and its characteristics, and configure current, voltage and temperature sensors for each device;

[0010] Install the sensor at the designated location of the electrical equipment and ensure that it is connected correctly. Start the module and begin real-time monitoring of current, voltage and temperature.

[0011] Amplifies and filters sensor signals, performs analog-to-digital conversion, and transmits digital signals;

[0012] Calibrate and denoise the digital signal and store the pre-processed data;

[0013] Send data to the centralized analysis module via wired or wireless means to keep the module running continuously and monitor the status of electrical equipment;

[0014] Perform regular self-checks to verify module and sensor functions, analyze monitoring data, identify anomalies or faults, and provide users with clear operational feedback based on the status of electrical equipment;

[0015] Centralized analysis module, used to receive monitoring data of various electrical appliances and perform data integration and analysis;

[0016] The early warning processing module determines whether there is a fire risk for the electrical appliance based on the analysis results and issues an early warning signal when an abnormality is detected;

[0017] Emergency power-off module, when the system determines that there is a fire risk, it automatically cuts off the power supply of the problematic appliance;

[0018] The user interface provides users with system status display, early warning information prompts and remote control functions.

[0019] Furthermore, the specific process of performing regular self-checks in the electrical control module to verify the functions of the module and the sensor is as follows:

[0020] Set the self-check interval, which can be a fixed period or dynamically adjusted according to the system running time;

[0021] Hardware detection: Check whether the physical connections of all sensors and monitoring devices are normal, and whether the power supply is stable;

[0022] Software diagnosis: Ensure that the system software runs normally without errors or anomalies, and check the system logs for errors or warning messages;

[0023] Sensor calibration: perform zero point calibration and range calibration on the sensor;

[0024] Data consistency check: Compare the readings of different sensors or the same sensor at different time points to check the consistency and rationality of the data;

[0025] Communication test: Test whether the data transmission path is smooth, including wireless and wired communications;

[0026] Simulation test: simulate abnormal situations to check whether the system can respond correctly;

[0027] The self-test frequency is adaptively adjusted according to the following electrical parameters:

[0028] Frequency of use, operating hours, historical failure rates, environmental parameters, load changes, and performance indicators;

[0029] Assign weights to each electrical parameter based on its impact on system safety and reliability;

[0030] Collect all electrical parameters in real time, apply FMEA to evaluate the impact of different failure modes on the system and the probability of occurrence, and determine which parameters need to be adjusted for frequency monitoring;

[0031] Dynamically set the threshold of each appliance parameter based on real-time data and historical trends, and increase the self-check frequency when the parameter value approaches or exceeds the threshold;

[0032] Use historical data to train machine learning models to predict the probability of failure, adjust the self-test frequency based on the model's prediction results, and develop a rule engine to automatically adjust the self-test frequency based on current parameter values ​​and preset rules;

[0033] Design a comprehensive scoring mechanism to combine the real-time values ​​and weights of all parameters to calculate a comprehensive score, and adjust the self-check frequency based on the score;

[0034] Establish a feedback mechanism to use the self-check results to update the weights and thresholds of parameters;

[0035] When multiple parameters trigger self-tests at the same time, the order and frequency of self-tests are determined based on priority, allowing users to set the self-test frequency of certain parameters based on specific needs or preferences.

[0036] Furthermore, the specific operation steps of the centralized analysis module for data integration and analysis are as follows:

[0037] Receive and synchronize real-time data from each electrical control module to ensure the accuracy of timestamps and data sequence;

[0038] Clean the data, remove outliers and noise, and perform data transformation and standardization;

[0039] Integrate data from different appliances to form a comprehensive data set;

[0040] Extract key data features, including peak current, voltage fluctuation, and temperature change rate;

[0041] Identify normal and abnormal operating modes;

[0042] Assess fire risk, identify abnormal behavior, and predict future risks;

[0043] Analyze the correlation between different electrical appliance data;

[0044] Store analysis results for historical records and further analysis;

[0045] Generate regular or on-demand analytical reports;

[0046] Integrate the analysis results into the early warning processing module, emergency power off module and user interface.

[0047] Furthermore, the specific operation steps of analyzing the correlation between different electrical appliance data in the centralized analysis module are as follows:

[0048] Merge data from different appliances into a comprehensive dataset and extract features from the integrated data, including peak, mean, standard deviation, and trend;

[0049] Apply association rule learning methods to discover frequent item sets and association rules between appliance parameters, and identify appliance usage patterns and potential abnormal patterns;

[0050] Analyze the changing trends of electrical parameters over time and identify timing correlations;

[0051] Use clustering algorithms to group electrical appliances, find appliances with similar behavior characteristics, calculate correlation coefficients between different appliance parameters, and identify strongly or weakly correlated parameter pairs;

[0052] Use causal inference methods to determine the cause-effect relationships between parameters;

[0053] Detect abnormal behavior using integrated data;

[0054] Assess the fire risk caused by the interaction between different electrical appliances based on the results of the correlation analysis;

[0055] Use charts and network diagrams in the user interface to visualize the associations and interaction patterns between appliances, conduct comprehensive analysis in multiple dimensions including time, space, and frequency of use, simulate different usage scenarios, and analyze the association behaviors of appliances under specific conditions;

[0056] Formulate preventive measures and optimization strategies based on the results of correlation analysis;

[0057] Generate a correlation analysis report.

[0058] Furthermore, the specific operation steps of the early warning processing module to determine whether there is a fire risk in the electrical appliance according to the analysis results and to issue an early warning signal when an abnormality is detected are as follows:

[0059] Receive monitoring data from the centralized analysis module and set safety thresholds for current, voltage and temperature;

[0060] Compare monitoring data with safety thresholds in real time to detect abnormal patterns;

[0061] Comprehensively analyze anomalies and assess fire risk and severity;

[0062] Set different levels of warnings according to the severity of the risk;

[0063] Identify the anomaly as a fire risk and generate an early warning signal;

[0064] Send alerts via the user interface, SMS, email or mobile app;

[0065] Record detailed information of warning events, including time, level and affected equipment;

[0066] Optimize risk assessment and threshold setting based on feedback;

[0067] Conduct regular tests to ensure the accuracy and effectiveness of the early warning system.

[0068] Furthermore, the warning processing module sets the specific operation steps of different levels of warnings according to the severity of the risk as follows:

[0069] The severity of the risk is determined by collecting risk parameters for comprehensive assessment, including:

[0070] Current difference: the proportion and duration of the current exceeding the rated value of the equipment. After normalization, the proportion and duration are multiplied and recorded as the current difference;

[0071] Voltage difference: the magnitude and duration of the voltage deviation from the standard voltage. After normalization, the voltage difference value is obtained by multiplying the deviation magnitude by the duration.

[0072] Temperature difference: the value and duration of the temperature of the electrical equipment exceeding the safety threshold. After normalization, the value of the temperature exceeding the safety threshold is multiplied by the duration, which is recorded as the temperature difference value;

[0073] Load change rate: the sudden change rate of electrical load or the magnitude of change in a short period of time;

[0074] Failure frequency: the number of times an appliance fails within a certain period of time;

[0075] Device usage time: the total time the device is used, which records the time difference from the first time the device is powered on to the present;

[0076] Environmental factors: Collect the humidity, dust concentration and corrosive gas concentration of the environment around the electrical equipment, and calculate the difference with the preset standard humidity, standard dust concentration and standard corrosive gas concentration to obtain the wet difference value, dust difference value and corrosion difference value respectively. Then, after normalizing the obtained wet difference value, dust difference value and corrosion difference value, use the wet difference value, dust difference value and corrosion difference value as the three sides of the triangle to establish a triangle, and then establish a triangular pyramid model with the preset height, calculate the volume of the triangular pyramid model, and record it as the environmental judgment value;

[0077] Then normalize the obtained electrical difference, pressure difference, temperature difference, load change rate, fault frequency and equipment use time and substitute them into the following formula:

[0078] To obtain the basic judgment value JPZ, where dc, yc, wc, fb, gp and st are the electrical difference, pressure difference, temperature difference, load change rate, fault frequency and equipment use time respectively. The preset weight coefficients are respectively the sum of the electric difference value and the pressure difference value, the preset weight coefficient of the temperature difference value, the preset weight coefficient of the load change rate, the preset weight coefficient of the fault frequency and the weight coefficient of the equipment use time;

[0079] Then normalize the obtained base judgment value JPZ and ring judgment value and enter them into the following formula: To obtain the comprehensive evaluation value ZBZ, where HP is the ring judgment value, and the obtained comprehensive evaluation value ZBZ is used as the standard to measure the severity of the risk;

[0080] The obtained comprehensive evaluation value is then compared with the three preset comprehensive evaluation value intervals. The preset three comprehensive evaluation value intervals correspond to low, medium and high risk levels respectively. By determining the comprehensive evaluation value interval to which the comprehensive evaluation value belongs, the risk level to which the abnormal risk belongs can be determined.

[0081] Furthermore, when the emergency power-off module determines that there is a fire risk, the specific operation steps of automatically cutting off the power supply of the problematic electrical appliance are as follows:

[0082] Receive risk assessment results from the early warning processing module;

[0083] Compare the evaluation result with the safety threshold to determine whether power outage is required;

[0084] If the threshold is exceeded, a power-off instruction is generated, specifying the power-off equipment and sequence;

[0085] Select the optimal power-off path and cut off the power supply through automation or remote control;

[0086] Confirm that the power-off operation has been completed and the equipment has stopped running;

[0087] Safely lock the circuit breaker or switch to prevent accidental power-on;

[0088] Send outage notification to the user interface, including reason and status;

[0089] Record power outage event information in the system;

[0090] Display power-off status and warnings through indicator lights or signs;

[0091] Provide guidance on inspection and repair after power outage, and prepare to restore normal power supply after safety is confirmed;

[0092] Test the power-off module functionality regularly to ensure reliability, and optimize the power-off module performance based on the results and feedback.

[0093] Furthermore, the specific process of the user interface providing the user with system status display, warning information prompts and remote control functions is as follows:

[0094] After the authorized user logs in, real-time current, voltage and temperature data are displayed;

[0095] Display the running, stopping or fault status of electrical equipment in real time, and display the warning information from the warning processing module;

[0096] Provides historical warning and power failure event query functions, and allows users to remotely control the start, stop or reset of electrical equipment;

[0097] The user configures the parameters of the electrical equipment and sets the method for receiving early warning information;

[0098] Provide system usage assistance, operation guides and troubleshooting, and receive user feedback;

[0099] Use charts and graphs to display device status and trends, and allow users to export log files and reports.

[0100] Compared with the prior art, the present invention has the following beneficial effects:

[0101] The present invention significantly improves the safety of electrical circuits through an integrated monitoring and analysis method, can monitor key parameters such as current, voltage and temperature of electrical equipment in real time, and uses advanced data analysis technology to identify potential fire risks. Compared with traditional fire alarm systems, this system can achieve early warning, promptly notify users to take preventive measures, effectively reduce the occurrence of fire accidents, and protect people's lives and property.

[0102] The present invention has an automatic emergency power-off function. Once a possible fire risk is detected, the power supply can be quickly cut off to prevent the spread of the fire. The self-check frequency can be automatically adjusted according to the monitoring data, resource allocation can be optimized, and the response speed and accuracy of the system can be improved. The intelligent control strategy not only improves the reliability of the system, but also reduces the risks caused by human operation delays or errors.

[0103] The present invention provides users with an intuitive and easy-to-operate platform in the design of the user interface, allowing users to conveniently monitor the operating status of electrical equipment, receive warning information, and perform remote control. The system also provides detailed operation guides, troubleshooting help, and feedback mechanisms to enhance user experience. Users can customize the receiving method and safety threshold of warning information according to personal needs, making the system more personalized and flexible, meeting the needs of different users. Through these designs, not only the safety management level of electrical circuits is improved, but also an efficient and convenient operation experience is provided to users. BRIEF DESCRIPTION OF THE DRAWINGS

[0104] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0105] Figure 1 This is the overall system block diagram of the present invention. DETAILED DESCRIPTION

[0106] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0107] It should be understood that the terms "include" and "comprising" used in the specification and claims of the present disclosure indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0108] It should also be understood that the terms used in this disclosure are only for the purpose of describing specific embodiments and are not intended to limit the disclosure. As used in this disclosure and claims, the singular forms of "a", "an", and "the" are intended to include the plural forms unless the context clearly indicates otherwise. It should also be further understood that the term "and / or" used in this disclosure and claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations.

[0109] like Figure 1 As shown, the electrical circuit fire safety management system includes an electrical control module, a centralized analysis module, an early warning processing module, an emergency power-off module and a user interface;

[0110] The electrical control module is used to monitor the current, voltage, temperature and other parameters of different electrical equipment of the user in real time;

[0111] Determine the electrical equipment that needs to be monitored and its characteristics, and configure corresponding current, voltage, and temperature sensors for each electrical equipment; install current sensors, voltage sensors, and temperature sensors at the corresponding positions of each electrical equipment, and ensure that the connection between the sensors and the electrical equipment is correct; start the electrical control module of the electrical equipment to start real-time monitoring of current, voltage, and temperature, and the sensors collect real-time data of the electrical equipment during operation;

[0112] The analog signals collected by the sensor are conditioned, such as amplified and filtered, to adapt to the subsequent analog-to-digital conversion, and the conditioned analog signals are converted into digital signals for processing by the microprocessor or controller. The converted digital signals are pre-processed, such as calibrated and denoised, to ensure the accuracy of the data; the pre-processed data is stored for further analysis and historical record query; the monitoring data is transmitted to the centralized analysis module through wired or wireless communication. The electrical control module needs to run continuously to realize real-time monitoring of electrical equipment; self-checks are performed regularly to ensure the normal operation of the module and sensor. The self-check process is as follows:

[0113] Set the time interval for self-checking, which can be a fixed period (for example, daily, weekly) or dynamically adjusted according to the system running time. Hardware detection: check whether the physical connections of all sensors and monitoring devices are normal, and check whether the power supply is stable; Software diagnosis: ensure that the system software runs normally without errors or abnormalities, and check the system log to find any possible errors or warning messages; Sensor calibration: perform zero point calibration and range calibration on the sensor to ensure measurement accuracy; Data consistency check: compare the readings of different sensors or the same sensor at different time points to check the consistency and rationality of the data; Communication test: test whether the data transmission path is unobstructed, including wireless and wired communications; Simulation test: simulate abnormal conditions, such as overload, overheating, etc., to check whether the system can respond correctly;

[0114] The self-test frequency can be adaptively adjusted according to the following electrical parameters:

[0115] Frequency of use, operating time, historical failure rate, environmental parameters, load changes, and performance indicators; assign weights to each electrical parameter based on its impact on system safety and reliability, for example, historical failure rate may have a higher weight than frequency of use; collect all electrical parameters in real time, apply FMEA to evaluate the impact of different failure modes on the system and the likelihood of their occurrence, and thus determine which parameters require more frequent monitoring; dynamically set the threshold of each parameter based on real-time data and historical trends, and increase the self-test frequency when the parameter value approaches or exceeds the threshold; use historical data to train machine learning models to predict the probability of failure, adjust the self-test frequency based on the model's prediction results, and develop a rule engine to automatically adjust the self-test frequency based on current parameter values ​​and preset rules;

[0116] Design a comprehensive scoring system that combines the real-time values ​​and weights of all parameters to calculate a comprehensive score, and adjust the self-check frequency based on the score; establish a feedback mechanism to use the self-check results to update the weights and thresholds of the parameters so that the system can learn from experience and optimize the self-check frequency; when multiple parameters trigger self-checks at the same time, determine the order and frequency of self-checks based on their priorities, allowing users to set the self-check frequency of certain parameters based on specific needs or preferences.

[0117] Diagnose monitoring data and identify any possible anomalies or faults; provide users with feedback on the operating status of electrical equipment, such as normal, warning or error, as needed.

[0118] The centralized analysis module is used to receive monitoring data from various electrical appliances and perform data integration and analysis;

[0119] Receive real-time monitoring data from various electrical control modules, including parameters such as current, voltage, and temperature, and ensure that the received data is synchronized, that is, the timestamp and order of the data are accurate for easy analysis; clean the received data, remove outliers and noise, and perform data conversion or standardization for further analysis; integrate data from different electrical control modules to form a comprehensive data set for cross-device analysis;

[0120] Extract key features from raw data, including peak current, voltage fluctuation, and temperature change rate; use statistical analysis or machine learning methods to identify patterns in the data, such as normal operating modes and abnormal modes of electrical appliances; assess the fire risk of electrical appliances based on preset rules or algorithms, determine whether there is abnormal behavior, analyze the change trend of electrical appliance parameters over time, and predict possible future risks;

[0121] Then conduct correlation analysis on the data of different electrical appliances. The specific steps are as follows:

[0122] Combine data from different electrical appliances into a comprehensive data set, and extract useful features such as peak, mean, standard deviation, trend, etc. from the integrated data; apply association rule learning methods (such as Apriori, FP-Growth algorithm) to discover frequent item sets and association rules between electrical appliance parameters, identify electrical appliance usage patterns and potential abnormal patterns; analyze the changing trends of electrical appliance parameters over time and identify time series associations; use clustering algorithms (such as K-means, hierarchical clustering) to group electrical appliances, find appliances with similar behavioral characteristics, calculate the correlation coefficients between different electrical appliance parameters, and identify strongly or weakly correlated parameter pairs; use causal inference methods (such as Granger causality test) to determine the causal relationship between parameters; use integrated data to detect abnormal behavior, such as whether the sudden increase in current of some electrical appliances is related to the specific status of other electrical appliances, and evaluate the fire risk that may be caused by the interaction between different electrical appliances based on the results of association analysis;

[0123] Use charts and network diagrams in the user interface to visualize the associations and interaction patterns between appliances, conduct comprehensive analysis based on multiple dimensions such as time, space, and frequency of use, simulate different usage scenarios, and analyze the association behaviors of appliances under specific conditions; formulate preventive measures and optimization strategies based on the results of association analysis; generate association analysis reports to provide decision makers with data-driven insights and recommendations.

[0124] Provide decision support for the early warning processing module, such as risk level and possible causes, store analysis results and related data in the database for historical records and further analysis, generate regular or on-demand analysis reports, and provide detailed information for system users or administrators; integrate analysis results with the early warning processing module, emergency power off module and user interface to ensure the coordinated work of the system.

[0125] The early warning processing module is used to determine whether there is a fire risk in the electrical appliance based on the analysis results, and to issue an early warning signal when an abnormality is detected;

[0126] Receive integrated and analyzed monitoring data from the centralized analysis module, set safety thresholds for current, voltage and temperature parameters according to the specifications and safety standards of the electrical appliances, analyze the monitoring data in real time, and compare them with the preset safety thresholds; detect abnormal patterns in the data, such as sudden current or voltage peaks, continuous overheating, etc., comprehensively analyze the abnormal data, and assess whether there is a fire risk; set different levels of warnings (such as warnings, severe warnings, and emergencies) according to the severity of the risk, where the severity of the risk is judged by collecting risk parameters for comprehensive assessment, which include:

[0127] Current difference: the proportion and duration of the current exceeding the rated value of the equipment. After normalization, the proportion is multiplied by the duration and recorded as the current difference; Voltage difference: the magnitude and duration of the voltage deviation from the standard voltage. After normalization, the deviation magnitude is multiplied by the duration to obtain the voltage difference; Temperature difference: the value and duration of the temperature of the electrical equipment exceeding the safety threshold. After normalization, the value of the temperature exceeding the safety threshold is multiplied by the duration and recorded as the temperature difference; Load change rate: the sudden change rate of the electrical load or the amplitude of change in a short period of time; Fault frequency: the number of times the electrical equipment fails within a certain period of time; Equipment usage time: the total usage time of the equipment. Here, the time difference from the first power-on to the present is recorded. Aging equipment may have a higher risk of failure;

[0128] Environmental factors: Collect the humidity, dust concentration and corrosive gas concentration of the surrounding environment of the electrical equipment, and calculate the difference with the preset standard humidity, standard dust concentration and standard corrosive gas concentration to obtain the wet difference value, dust difference value and corrosion difference value respectively. The values ​​that do not exceed the preset standard are recorded as 0. Then, after normalizing the obtained wet difference value, dust difference value and corrosion difference value, use the wet difference value, dust difference value and corrosion difference value as the three sides of the triangle to establish a triangle, and then establish a triangular pyramid model with the preset height, calculate the volume of the triangular pyramid model, and record it as the ring judgment value, where the preset height is set between 1.88-6.52;

[0129] Then normalize the obtained electrical difference, pressure difference, temperature difference, load change rate, fault frequency and equipment use time and substitute them into the following formula:

[0130] To obtain the basic judgment value JPZ, where dc, yc, wc, fb, gp and st are the electrical difference, pressure difference, temperature difference, load change rate, fault frequency and equipment use time respectively. The preset weight coefficients are respectively the sum of the electric difference value and the pressure difference value, the preset weight coefficient of the temperature difference value, the preset weight coefficient of the load change rate, the preset weight coefficient of the fault frequency and the weight coefficient of the equipment use time;

[0131] Then normalize the obtained base judgment value JPZ and ring judgment value and enter them into the following formula: To obtain the comprehensive evaluation value ZBZ, where HP is the ring judgment value, and the obtained comprehensive evaluation value ZBZ is used as a standard to measure the severity of the risk; then the obtained comprehensive evaluation value ZBZ is compared with the three preset comprehensive evaluation value intervals, which correspond to low, medium and high risk levels respectively. By determining the comprehensive evaluation value interval to which the comprehensive evaluation value ZBZ belongs, the risk level to which the abnormal risk belongs is determined.

[0132] When an abnormality is detected and assessed as a fire risk, a corresponding warning signal is generated; a warning signal is sent to the user through the user interface, SMS, email or mobile application; all warning events are recorded in the system, including time, risk level, affected equipment, etc.; based on the warning results and user feedback, the risk assessment algorithm and threshold setting are optimized; simulation tests are conducted regularly to verify the accuracy of the warning processing module and the effectiveness of the response process.

[0133] The emergency power-off module is used to automatically cut off the power supply of the problematic appliance when the system determines that there is a fire risk;

[0134] Receive the risk assessment results from the early warning processing module, determine whether it is necessary to perform a power-off operation, judge the risk assessment results provided by the early warning processing module, and compare them with the preset safety threshold; when the assessment results exceed the safety threshold, confirm that emergency power-off needs to be performed on specific electrical appliances, generate a power-off instruction, clearly indicate the electrical appliances that need to be powered off and the order of power-off; determine the optimal power-off path, select the circuit breaker or switch with the least impact and the ability to quickly cut off the power supply, and execute the power-off instruction through the automated control system or remote control to cut off the power supply of the problematic electrical appliances;

[0135] Confirm that the power-off operation has been successfully executed and the electrical equipment has stopped running; after the power is off, the relevant circuit breakers or switches are safely locked to prevent the power from being turned on again due to accidental operation; send a power-off notification to the user interface to inform the user that the power-off operation has been completed and display the reason for the power-off; record detailed information of the power-off event in the system, including time, reason, and affected electrical equipment;

[0136] Display power-off status and safety warnings through on-site indicator lights or signs; provide follow-up processing guidance after power outage, such as checking electrical equipment, contacting maintenance services, etc.; prepare steps to restore normal power supply to the system after confirming safety; regularly test the functions of the emergency power-off module to ensure that it can be reliably executed when needed; use the results and feedback of the power-off operation for system optimization to improve the performance and response speed of the emergency power-off module.

[0137] The user interface provides users with system status display, warning information prompts and remote control functions;

[0138] After the authorized user logs in, the real-time current, voltage and temperature data collected from the user's different electrical control modules are displayed; the status of electrical equipment is monitored in real time, including operation, stop or failure; when the early warning processing module sends out an early warning signal, the early warning information is displayed on the user interface, and the query function of historical early warning records, power outage time and other important events is provided, and the user is allowed to remotely control the start, stop or reset of the electrical equipment through the user interface, which is used for the user to configure the parameters of the electrical equipment, including modifying the safety threshold or updating the user information; the user sets the way to receive early warning information through the user interface, including SMS, email or application notification, provides system instructions, operation guides and troubleshooting help, and can also provide feedback, report system problems or make suggestions for improvement; charts and graphs are used to intuitively display the operating status and trends of electrical equipment, allowing users to export log files and generated reports for recording or analysis.

[0139] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. Electrical circuit fire safety management system, characterized in that: include: The electrical control module is used to monitor the operating parameters of different electrical equipment of the user in real time. The specific process is as follows: Determine the electrical equipment to be monitored and its characteristics, and configure current, voltage and temperature sensors for each device; Install the sensor at the designated location of the electrical equipment and ensure that it is connected correctly. Start the module and begin real-time monitoring of current, voltage and temperature. Amplifies and filters sensor signals, performs analog-to-digital conversion, and transmits digital signals; Calibrate and denoise the digital signal and store the pre-processed data; Send data to the centralized analysis module via wired or wireless means to keep the module running continuously and monitor the status of electrical equipment; Perform regular self-checks to verify module and sensor functions, analyze monitoring data, identify anomalies or faults, and provide users with clear operational feedback based on the status of electrical equipment; Centralized analysis module, used to receive monitoring data of various electrical appliances and perform data integration and analysis; The early warning processing module determines whether there is a fire risk for the electrical appliance based on the analysis results and issues an early warning signal when an abnormality is detected. The specific process is as follows: Receive monitoring data from the centralized analysis module and set safety thresholds for current, voltage and temperature; Compare monitoring data with safety thresholds in real time to detect abnormal patterns; Comprehensively analyze anomalies and assess fire risk and severity; Set different levels of warnings according to the severity of the risk; Identify the anomaly as a fire risk and generate an early warning signal; Send alerts via the user interface, SMS, email or mobile app; Record detailed information of warning events, including time, level and affected equipment; Optimize risk assessment and threshold setting based on feedback; Conduct regular testing to ensure the accuracy and effectiveness of the early warning system; The specific steps for setting different levels of warnings according to the severity of the risk are as follows: The severity of the risk is determined by collecting risk parameters for comprehensive assessment, including: Current difference: the proportion and duration of the current exceeding the rated value of the equipment. After normalization, the proportion and duration are multiplied and recorded as the current difference; Voltage difference: the magnitude and duration of the voltage deviation from the standard voltage. After normalization, the voltage difference value is obtained by multiplying the deviation magnitude by the duration. Temperature difference: the value and duration of the temperature of the electrical equipment exceeding the safety threshold. After normalization, the value of the temperature exceeding the safety threshold is multiplied by the duration, which is recorded as the temperature difference value; Load change rate: the sudden change rate of electrical load or the magnitude of change in a short period of time; Fault frequency: the number of times an appliance fails within a preset time; Device usage time: the total time the device is used, which records the time difference from the first time the device is powered on to the present; Environmental factors: Collect the humidity, dust concentration and corrosive gas concentration of the environment around the electrical equipment, and calculate the difference with the preset standard humidity, standard dust concentration and standard corrosive gas concentration to obtain the wet difference value, dust difference value and corrosion difference value respectively. Then, after normalizing the obtained wet difference value, dust difference value and corrosion difference value, use the wet difference value, dust difference value and corrosion difference value as the three sides of the triangle to establish a triangle, and then establish a triangular pyramid model with the preset height, calculate the volume of the triangular pyramid model, and record it as the environmental judgment value; Then normalize the obtained electrical difference, pressure difference, temperature difference, load change rate, fault frequency and equipment use time and substitute them into the following formula: To obtain the basic judgment value JPZ, where dc, yc, wc, fb, gp and st are the electrical difference, pressure difference, temperature difference, load change rate, fault frequency and equipment use time respectively. The preset weight coefficients are respectively the sum of the electric difference value and the pressure difference value, the preset weight coefficient of the temperature difference value, the preset weight coefficient of the load change rate, the preset weight coefficient of the fault frequency and the weight coefficient of the equipment use time; Then normalize the obtained base judgment value JPZ and ring judgment value and enter them into the following formula: To obtain the comprehensive evaluation value ZBZ, where HP is the ring judgment value, and the obtained comprehensive evaluation value ZBZ is used as the standard to measure the severity of the risk; The obtained comprehensive evaluation value is then compared with the three preset comprehensive evaluation value intervals. The three preset comprehensive evaluation value intervals correspond to low, medium and high risk levels respectively. By determining the comprehensive evaluation value interval to which the comprehensive evaluation value belongs, the risk level to which it belongs is determined; Emergency power-off module, when the system determines that there is a fire risk, it automatically cuts off the power supply of the problematic appliance; The user interface provides users with system status display, early warning information prompts and remote control functions.

2. The electrical circuit fire safety management system according to claim 1, characterized in that: The specific process of performing regular self-test in the electrical control module to verify the module and sensor functions is as follows: Set the self-check interval, which can be a fixed period or dynamically adjusted according to the system running time; Hardware detection: Check whether the physical connections of all sensors and monitoring devices are normal, and whether the power supply is stable; Software diagnosis: Ensure that the system software runs normally without errors or anomalies, and check the system logs for errors or warning messages; Sensor calibration: perform zero point calibration and range calibration on the sensor; Data consistency check: Compare the readings of different sensors or the same sensor at different time points to check the consistency and rationality of the data; Communication test: Test whether the data transmission path is smooth, including wireless and wired communications; Simulation test: simulate abnormal situations to check whether the system can respond correctly; The self-test frequency is adaptively adjusted according to the following electrical parameters: Frequency of use, operating hours, historical failure rates, environmental parameters, load changes, and performance indicators; Assign weights to each electrical parameter based on its impact on system safety and reliability; Collect all electrical parameters in real time, apply FMEA to evaluate the impact of different failure modes on the system and the probability of occurrence, and determine which parameters need to be adjusted for frequency monitoring; Dynamically set the threshold of each appliance parameter based on real-time data and historical trends. When the parameter value exceeds the threshold, increase the self-check frequency. Use historical data to train machine learning models to predict the probability of failure, adjust the self-test frequency based on the model's prediction results, and develop a rule engine to automatically adjust the self-test frequency based on current parameter values ​​and preset rules; Design a comprehensive scoring mechanism to combine the real-time values ​​and weights of all parameters to calculate a comprehensive score, and adjust the self-check frequency based on the score; Establish a feedback mechanism to use the self-check results to update the weights and thresholds of parameters; When multiple parameters trigger self-tests at the same time, the order and frequency of self-tests are determined based on priority, allowing users to set the self-test frequency of certain parameters based on specific needs or preferences.

3. The electrical circuit fire safety management system according to claim 1, characterized in that: The specific operation steps of the centralized analysis module for data integration and analysis are as follows: Receive and synchronize real-time data from each electrical control module to ensure the accuracy of timestamps and data sequence; Clean the data, remove outliers and noise, and perform data transformation and standardization; Integrate data from different appliances to form a comprehensive data set; Extract key data features, including peak current, voltage fluctuation, and temperature change rate; Identify normal and abnormal operating modes; Assess fire risk, identify abnormal behavior, and predict future risks; Analyze the correlation between different electrical appliance data; Store analysis results for historical records and further analysis; Generate regular or on-demand analytical reports; Integrate the analysis results into the early warning processing module, emergency power off module and user interface.

4. The electrical circuit fire safety management system according to claim 3, characterized in that: The specific operation steps of analyzing the correlation between different electrical appliance data in the centralized analysis module are as follows: Merge data from different appliances into a comprehensive dataset and extract features from the integrated data, including peak, mean, standard deviation, and trend; Apply association rule learning methods to discover frequent item sets and association rules between appliance parameters, and identify appliance usage patterns and potential abnormal patterns; Analyze the changing trends of electrical parameters over time and identify timing correlations; Use clustering algorithms to group electrical appliances, find appliances with similar behavior characteristics, calculate correlation coefficients between different appliance parameters, and identify strongly or weakly correlated parameter pairs; Use causal inference methods to determine the cause-effect relationships between parameters; Detect abnormal behavior using integrated data; Assess the fire risk caused by the interaction between different electrical appliances based on the results of the correlation analysis; Use charts and network diagrams in the user interface to visualize the associations and interaction patterns between appliances, conduct comprehensive analysis in multiple dimensions including time, space, and frequency of use, simulate different usage scenarios, and analyze the association behaviors of appliances under specific conditions; Formulate preventive measures and optimization strategies based on the results of correlation analysis; Generate a correlation analysis report.

5. The electrical circuit fire safety management system according to claim 1, characterized in that: When the emergency power-off module determines that there is a fire risk, the specific operation steps of automatically cutting off the power supply of the problematic electrical appliance are as follows: Receive risk assessment results from the early warning processing module; Compare the evaluation result with the safety threshold to determine whether power outage is required; If the threshold is exceeded, a power-off instruction is generated, specifying the power-off equipment and sequence; Select the optimal power-off path and cut off the power supply through automation or remote control; Confirm that the power-off operation has been completed and the equipment has stopped running; Safely lock the circuit breaker or switch to prevent accidental power-on; Send outage notification to the user interface, including reason and status; Record power outage event information in the system; Display power-off status and warnings through indicator lights or signs; Provide guidance on inspection and repair after power outage, and prepare to restore normal power supply after safety is confirmed; Test the power-off module functionality regularly to ensure reliability, and optimize the power-off module performance based on the results and feedback.

6. The electrical circuit fire safety management system according to claim 1, characterized in that: The specific process of the user interface providing the user with system status display, warning information prompts and remote control functions is as follows: After the authorized user logs in, real-time current, voltage and temperature data are displayed; Display the running, stopping or fault status of electrical equipment in real time, and display the warning information from the warning processing module; Provides historical warning and power failure event query functions, and allows users to remotely control the start, stop or reset of electrical equipment; The user configures the parameters of the electrical equipment and sets the method for receiving early warning information; Provide system usage assistance, operation guides and troubleshooting, and receive user feedback; Use charts and graphs to display device status and trends, and allow users to export log files and reports.

Images