Electricity larceny prevention intelligent monitoring control method and system for electric energy metering box

Abstract

The invention discloses an electricity larceny prevention intelligent monitoring control method and system for an electric energy metering box. The system comprises a physical anti-disassembly monitoring unit, a multi-dimensional electrical feature recognition unit, a dual-mode communication control unit and a full-link evidence retention unit. The physical anti-disassembly monitoring unit monitors physical damage behaviors through dual verification and multi-sensor fusion, and the multi-dimensional electrical feature recognition unit collects 12 electrical parameters and recognizes electricity stealing behaviors based on a three-dimensional feature model and a dynamic weighted voting algorithm. The dual-mode communication control unit performs dual-mode data transmission with a Beidou short message through fifth-generation mobile communication and executes remote power-off, and the full-link evidence retention unit stores images, data and encrypted logs. The system forms a closed loop of monitoring, identification, alarm, control and evidence obtaining, improves the reliability of electricity larceny prevention, and guarantees the accuracy of electric power measurement and the legitimate rights and interests of power supply enterprises.

Description

Technical Field

[0001] This invention belongs to the field of power metering security technology, and relates to a method and system for intelligent monitoring and control of electricity metering boxes to prevent electricity theft. Background Technology

[0002] Electricity metering boxes are the core equipment for electricity metering, and their safe operation directly affects the accuracy of electricity metering and the legitimate rights and interests of power supply companies. Current anti-theft technologies have significant shortcomings in terms of physical protection, electrical identification, communication transmission, and evidence preservation.

[0003] Regarding physical anti-tampering, existing technologies mostly rely on a combination of mechanical locks and a single electronic lock. These can only monitor the opening and closing status of the cabinet door and cannot cope with concealed destructive acts such as prying and drilling. The locks are also easily cracked by professional tools. In terms of electrical theft detection, traditional solutions are mostly based on monitoring a single current or voltage parameter, which makes it difficult to distinguish between normal power fluctuations and electricity theft. They are also ineffective at detecting concealed electricity theft methods such as harmonic interference bypass wiring.

[0004] In terms of communication transmission, existing systems mostly employ a single communication method, which is prone to signal blind spots in remote areas or complex environments, leading to delays or loss of alarm information transmission. Regarding evidence preservation, current technologies only record basic data, lacking crucial evidence such as video recordings of the entire event and encrypted logs, resulting in an incomplete chain of evidence and difficulty in meeting the requirements for judicial accountability. These problems make it difficult to effectively curb electricity theft, causing significant economic losses to power supply companies. Therefore, a more reliable intelligent monitoring and control solution for preventing electricity theft is urgently needed. Summary of the Invention

[0005] To address the problems existing in the background technology, this invention proposes an intelligent monitoring and control method and system for preventing electricity theft in electricity metering boxes.

[0006] The first aspect of this application provides an intelligent monitoring and control system for preventing electricity theft in electricity metering boxes, comprising:

[0007] Physical tamper-proof monitoring unit, multi-dimensional electrical feature recognition unit, dual-mode communication control unit, and full-link evidence retention unit;

[0008] The physical anti-tamper monitoring unit monitors physical damage to the electricity metering box and outputs monitoring signals; the multi-dimensional electrical feature identification unit collects electrical parameters and identifies electricity theft; the dual-mode communication control unit receives monitoring signals and electricity theft identification results, transmits data, and executes remote control commands; the end-to-end evidence retention unit stores monitoring data, image information, and operation logs based on monitoring signals and electricity theft identification results.

[0009] Optionally, the physical anti-tamper monitoring unit includes a sealing structure, a conductive circuit assembly, a multi-sensor assembly, and an authorized opening assembly; the sealing structure is a one-piece stainless steel enclosure with laser-welded joints and an anti-drill steel plate fixedly installed inside the enclosure wall; the conductive circuit assembly is a flexible conductive sealing gasket that fits the enclosure door and the enclosure joint to form a closed conductive circuit; the multi-sensor assembly includes a triaxial accelerometer, an infrared distance sensor, and a Hall sensor, and the data collected by the three sensors are processed by a Kalman filter algorithm and then output to the dual-mode communication control unit.

[0010] Optionally, the authorization unlocking components include an encryption key and a facial recognition module; the encryption key has a built-in encryption chip that stores a unique device identification code; the facial recognition module performs offline authorization personnel identification, and the electronic lock unlocks only when the device identification code of the encryption key is verified and the facial recognition module is successfully identified.

[0011] Optionally, the multi-dimensional electrical feature identification unit includes a parameter acquisition module and a feature fusion identification module; the parameter acquisition module acquires 12 electrical parameters, including three-phase voltage, three-phase current, active power, reactive power, harmonic content, and power factor; the feature fusion identification module constructs a three-dimensional feature identification model based on time dimension abrupt change, frequency dimension distortion, and energy dimension balance, and outputs the electricity theft judgment result to the dual-mode communication control unit through a weighted voting algorithm.

[0012] Optionally, the time dimension abrupt change is achieved by calculating the electrical parameter abrupt change coefficient, the formula for which the electrical parameter abrupt change coefficient is: ,in, These are the electrical parameter values ​​at the current moment. These are the electrical parameter values ​​from the previous moment. The electrical parameter abrupt change coefficient; frequency dimension distortion is achieved by calculating harmonic distortion characteristic values, the formula for calculating the harmonic distortion characteristic values ​​is as follows: ,in, This represents the current total harmonic distortion (THD). The historical average harmonic distortion rate, This is the effective value of the harmonic current. This is the effective value of the fundamental current. The characteristic value is the harmonic distortion value; energy dimensional balance is achieved by calculating the power balance coefficient, and the formula for calculating the power balance coefficient is: ,in This refers to the active power on the incoming line side. For electricity meters to measure active power, B represents the theoretical line loss, and B is the power balance coefficient.

[0013] Optionally, the weighted voting algorithm of the feature fusion identification module dynamically adjusts the weights according to the type of electricity theft; when it is determined to be electricity theft due to harmonic interference, the weight of the harmonic distortion feature value is 0.5, the weight of the electrical parameter mutation coefficient is 0.3, and the weight of the power balance coefficient is 0.2.

[0014] Optionally, the dual-mode communication control unit includes a fifth-generation mobile communication module, a Beidou short message module, and an electromagnetic relay; the fifth-generation mobile communication module transmits high-definition images and electrical parameters; the Beidou short message module automatically switches when the fifth-generation mobile communication signal is interrupted, transmitting the device identification code, electricity theft type, and geographical location information; after receiving a remote power-off command, the dual-mode communication control unit controls the electromagnetic relay to cut off the incoming power supply.

[0015] Optionally, the end-to-end evidence retention unit includes an image acquisition module, a data storage module, and a log encryption module; the image acquisition module records a 5-second buffered video before triggering and a 5-second real-time video after triggering, and captures key frame photos of the door status, internal wiring, and abnormal areas; the data storage module stores the original electrical parameter data for 30 seconds before and after triggering; the log encryption module uses blockchain technology to store operation logs, with the blockchain deployed on three or more redundant nodes.

[0016] A second aspect of this application provides an intelligent monitoring and control method for preventing electricity theft in electricity metering boxes, comprising:

[0017] After the equipment completes its self-test, it synchronizes the user's historical electricity consumption data to build a normal electricity consumption characteristic database.

[0018] The physical anti-tamper monitoring unit collects and processes sensor data, while the multi-dimensional electrical feature recognition unit collects electrical parameters and calculates electrical parameter mutation coefficient, harmonic distortion characteristic value and power balance coefficient in real time.

[0019] When physical damage is detected, the image acquisition module is activated to record evidence and a level one alarm is sent through the dual-mode communication control unit. When electricity theft is detected, the image acquisition module is activated to record evidence, a level two alarm is sent through the dual-mode communication control unit, and the electromagnetic relay is controlled to cut off the incoming power supply.

[0020] After viewing alarm and evidence information and issuing control commands through the cloud management platform, managers can extract encrypted evidence files from the end-to-end evidence retention unit for judicial evidence collection.

[0021] Optionally, the remote power outage recovery process is as follows: after dual authorization through device identification code verification of the encryption key and identity recognition by the facial recognition module, the dual-mode communication control unit controls the electromagnetic relay to close and restore power supply.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] This invention provides an intelligent monitoring and control method and system for preventing electricity theft in electricity metering boxes. The physical anti-tamper monitoring unit, through structural sealing and multi-sensor fusion design, combined with a dual-authorization opening mechanism, comprehensively covers various physical destructive behaviors, effectively blocking illegal intrusion and improving the security of physical protection. The multi-dimensional electrical feature identification unit, based on a three-dimensional feature model and dynamic weighted voting algorithm, analyzes electrical parameters from three dimensions: time, frequency, and energy, accurately distinguishing between normal power fluctuations and electricity theft, covering multiple types of electricity theft, and reducing the risk of misjudgment and missed judgment. The dual-mode communication control unit uses a fifth-generation mobile communication module and a Beidou short message module for automatic switching, ensuring stable transmission of alarm information and monitoring data in different environments, and rapid execution of remote power-off commands, effectively curbing the continuous occurrence of electricity theft. The full-link evidence retention unit, through comprehensive storage of multiple types of evidence and blockchain encryption design, forms a complete and tamper-proof evidence chain, meeting the requirements of judicial evidence collection and providing strong support for pursuing accountability for electricity theft. The collaborative work of each unit forms a complete closed loop, comprehensively improving the anti-theft capability of the electricity metering box, ensuring the accuracy of power metering, power supply safety, and the legitimate rights and interests of power supply companies. Attached Figure Description

[0024] Figure 1 This is a schematic diagram of an intelligent monitoring and control system for preventing electricity theft in an electricity metering box according to one embodiment of the present invention;

[0025] Figure 2 This is a flowchart of an intelligent monitoring and control method for preventing electricity theft in an electricity metering box according to an embodiment of the present invention. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] In one embodiment, such as Figure 1 As shown, an intelligent monitoring and control system for preventing electricity theft in electricity metering boxes is provided. This intelligent monitoring and control system for preventing electricity theft in electricity metering boxes corresponds one-to-one with the intelligent monitoring and control method for preventing electricity theft in electricity metering boxes in the above embodiments. The intelligent monitoring and control system for preventing electricity theft in electricity metering boxes includes: a physical anti-tamper monitoring unit, a multi-dimensional electrical feature recognition unit, a dual-mode communication control unit, and a full-link evidence retention unit. The detailed description of each functional module is as follows:

[0028] The core function of the physical anti-tamper monitoring unit is to accurately capture various physical acts of damage to the electricity metering box and generate effective monitoring signals. The sealing structure adopts a one-piece stainless steel design, with laser-welded seams to resist external impacts and prying. An anti-drilling steel plate fixed inside the box wall prevents drilling tools from damaging the box. A flexible conductive gasket is attached to the seam between the door and the box body, forming a closed conductive circuit. When the box is pried open, causing the gasket to detach or be damaged by drilling, the conductive circuit breaks, immediately triggering the initial monitoring signal. The multi-sensor assembly includes a triaxial accelerometer that continuously detects vibrations within the box, an infrared distance sensor that monitors for foreign object intrusion, and a Hall effect sensor that specifically detects the opening and closing status of the door. Data collected by these three types of sensors is transmitted to a filtering module, where a Kalman filter algorithm removes invalid data caused by environmental interference, ensuring the accuracy of the monitoring results. The authorized unlocking component plays an auxiliary verification role in physical anti-tamper monitoring. The encrypted key has a built-in encryption chip and stores a unique device identification code. The facial recognition module performs offline authorized personnel identification. The electronic lock will only unlock when the device identification code of the encrypted key is verified and the facial recognition module is successfully identified. If the cabinet vibrates, foreign objects intrude, the door is opened, or the conductive circuit is broken without the above dual authorization, the physical anti-tamper monitoring unit will immediately output a clear monitoring signal. This unit achieves comprehensive coverage of various physical damage behaviors through the combination of structural protection and sensor monitoring, improves the reliability of physical anti-tampering, and effectively prevents unauthorized personnel from stealing electricity by damaging the cabinet.

[0029] The multi-dimensional electrical feature recognition unit effectively identifies electricity theft by comprehensively collecting and accurately analyzing electrical parameters. The parameter acquisition module collects 12 electrical parameters at a set frequency, including three-phase voltage, three-phase current, active power, reactive power, harmonic content, and power factor, ensuring comprehensive and complete data for subsequent feature analysis. The feature fusion recognition module constructs a three-dimensional feature recognition model based on time-dimensional abrupt changes, frequency-dimensional distortion, and energy-dimensional balance, analyzing electrical parameters from different perspectives. Time-dimensional abrupt changes are calculated by determining the abrupt change coefficient of electrical parameters, comparing the current and previous parameter values ​​to determine if abnormal abrupt changes exist. Frequency-dimensional distortion is determined by calculating harmonic distortion characteristic values, combining the current total harmonic distortion rate, historical average harmonic distortion rate, and the effective ratio of harmonic current to fundamental current to identify harmonic interference-related electricity theft. Energy-dimensional balance is determined by calculating the power balance coefficient, comparing the active power on the incoming side, the active power measured by the meter, and the theoretical line loss to determine if bypass wiring or other energy loss-causing electricity theft occurs. The feature fusion and identification module employs a weighted voting algorithm to fuse the analysis results from three dimensions. It dynamically adjusts the weights based on different types of electricity theft. When electricity theft is determined to be caused by harmonic interference, the weight of the harmonic distortion feature value is 0.5, the weight of the electrical parameter mutation coefficient is 0.3, and the weight of the power balance coefficient is 0.2. This reasonable weight allocation improves the accuracy of identification. This unit, through multi-dimensional feature analysis and dynamic weight fusion, avoids the limitations of single-parameter identification, accurately distinguishing between normal electricity fluctuations and electricity theft, thus improving the comprehensiveness and accuracy of electricity theft identification.

[0030] The dual-mode communication control unit, as the core of data transmission and command execution, ensures the timely transmission of monitoring signals and identification results, as well as the effective execution of remote control commands. The fifth-generation mobile communication module, with its high-speed transmission capability, is responsible for rapidly transmitting high-definition images stored in the end-to-end evidence storage unit and electrical parameters collected by the multi-dimensional electrical feature identification unit to the cloud management platform, ensuring that management personnel can obtain relevant information in real time. The Beidou short message module, as a backup communication method, automatically switches its operating state when the fifth-generation mobile communication signal is interrupted, promptly transmitting the device identification code, electricity theft type, and geographical location information, ensuring that alarm information is not lost in complex communication environments. When the dual-mode communication control unit receives monitoring signals from the physical tamper monitoring unit or electricity theft identification results from the multi-dimensional electrical feature identification unit, it will perform corresponding operations based on the signal type. If a monitoring signal of physical damage is received, a level one alarm will be sent; if an identification result of electricity theft is received, a level two alarm will be sent and a remote power-off command will be received from the cloud management platform, controlling the electromagnetic relay to cut off the incoming power supply and prevent the continued electricity theft. This unit solves the signal blind spot problem that may exist in a single communication method through the redundancy design of dual-mode communication, ensuring the reliability of communication, while responding quickly to remote control commands and effectively curbing electricity theft.

[0031] The end-to-end evidence retention unit comprehensively stores relevant evidence information based on the monitoring signals from the physical anti-tamper monitoring unit and the electricity theft identification results from the multi-dimensional electrical feature identification unit, providing strong support for subsequent judicial evidence collection. The video acquisition module immediately starts working after the monitoring signal or electricity theft identification result is triggered, recording 5 seconds of buffered video before the trigger and 5 seconds of real-time video after the trigger, completely recording the entire process of the event. Simultaneously, it captures key frame photos of the cabinet door status, internal wiring, and abnormal areas, clearly capturing core evidence. The data storage module specifically stores the original electrical parameter data for 30 seconds before and after the trigger, ensuring the integrity of the electrical data and providing original evidence for technical analysis. The log encryption module uses blockchain technology to store operation logs. The blockchain deploys at least three redundant nodes. The operation logs include equipment power-on time, authorized start records, alarm trigger time, remote control command execution status, etc. The encryption characteristics and redundant storage design of the blockchain ensure that the operation logs are tamper-proof and permanently preserved. This unit, through the comprehensive retention and encrypted storage of multiple types of evidence, forms a complete evidence chain, ensuring the authenticity and legality of the evidence, providing strong protection for judicial accountability, and enhancing the deterrent effect against electricity theft.

[0032] When all units work together, the physical anti-tamper monitoring unit and the multi-dimensional electrical feature identification unit continuously monitor the system. Once an anomaly is detected, the corresponding signal is immediately output. The dual-mode communication control unit transmits signals and executes control commands synchronously. The full-link evidence retention unit stores relevant evidence in real time, forming a complete closed loop from monitoring, identification, alarm, control to evidence retention. This comprehensively improves the anti-theft capability of the electricity metering box, ensuring the accuracy of electricity metering, power supply safety, and the legitimate rights and interests of power supply companies.

[0033] The authorization unlocking component is a crucial part of ensuring the legal opening of the electricity metering box and preventing unauthorized intrusion. It achieves precise control over authorized operations through a dual verification mechanism using an encrypted key and a facial recognition module. The encrypted key serves as a physical credential, integrating an encryption chip that employs a specific encryption algorithm to protect the data. Each encrypted key stores a unique device identification code, which is pre-bound to the intelligent monitoring and control system of the electricity metering box, ensuring that one encrypted key can only be matched with the corresponding electricity metering box device. The verification process between the encrypted key and the system is completed via short-range wireless communication. When a staff member brings the encrypted key close to the sensing area of ​​the electricity metering box, the system automatically reads the device identification code stored in the encrypted key and compares it with the pre-stored valid identification code, completing the first layer of verification.

[0034] The facial recognition module, serving as the second layer of verification, integrates offline recognition algorithms and can independently complete identity verification without relying on an external network. The system pre-collects facial image information of authorized personnel, extracts features, and stores it in local storage. The stored facial feature information is encrypted to prevent tampering or theft. When a staff member initiates an operation, the facial recognition module's camera automatically captures the operator's facial image, extracts real-time facial features using offline algorithms, and compares them with the locally stored authorized personnel facial features. The comparison process strictly adheres to preset recognition standards; facial recognition verification is only successful when the real-time extracted facial features completely match the pre-stored authorized personnel facial features.

[0035] The complete authorization process involves the staff first bringing the encrypted key close to the sensing area of ​​the electricity metering box. The system reads the device identification code and completes the verification. After successful verification, the facial recognition module automatically activates, capturing the operator's facial image and performing feature comparison. Only when both conditions are met—the encrypted key's device identification code verification and the facial recognition module's successful recognition—will the system send an unlock command to the electronic lock. Upon receiving the command, the electronic lock executes the unlocking action, allowing the staff to open the electricity metering box for legitimate operations, such as inspection, maintenance, and meter reading. If the encrypted key's device identification code does not match the pre-stored information, or if facial recognition fails, the system will not send an unlock command, the electronic lock will remain locked, and this unauthorized opening attempt will be recorded as an abnormal event, triggering the corresponding monitoring signal.

[0036] This dual-authorization unlocking mechanism combines device binding of an encrypted key with facial recognition for identity verification, effectively avoiding the security risks of a single authorization method. The unique device identification code of the encrypted key ensures a unique match between the device and the key, preventing illegally copied keys from opening the electricity metering box. The offline working mode of the facial recognition module ensures normal authorization operations in environments without network connectivity, while the liveness detection function effectively resists deception methods such as photos and videos, ensuring the operator's true identity. This dual-verification design significantly improves the security and reliability of authorization unlocking, ensuring convenient operation for legitimate personnel while strictly preventing unauthorized personnel from breaking into the electricity metering box to steal electricity by stealing keys, further improving the overall anti-theft system for the electricity metering box.

[0037] The multi-dimensional electrical feature recognition unit achieves accurate identification of electricity theft through the collaborative work of the parameter acquisition module and the feature fusion recognition module. The parameter acquisition module, equipped with a high-precision metering chip, continuously collects electrical parameters at a fixed frequency. The collected parameters include the voltage value of each phase of the three-phase voltage, the current value of each phase of the three-phase current, and active power, reactive power, harmonic content, and power factor—a total of 12 electrical parameters. These parameters cover core electrical indicators in the process of power transmission and consumption, comprehensively reflecting the power consumption status. The parameter acquisition module converts the collected analog signals into digital signals, which, after signal conditioning, are transmitted to the feature fusion recognition module, providing a complete and reliable data foundation for subsequent feature analysis and electricity theft determination.

[0038] The feature fusion and recognition module is the core component for identifying electricity theft. It constructs a three-dimensional feature recognition model based on time-dimensional abrupt changes, frequency-dimensional distortion, and energy-dimensional balance. Time-dimensional abrupt changes focus on the variations in electrical parameters over time. By calculating the abrupt change coefficient of electrical parameters and comparing the values ​​of the same electrical parameter at the current moment with those at the previous moment, it determines whether there are sudden parameter fluctuations. For example, during normal electricity use, electrical parameters usually show stable changes or slight fluctuations. However, when electricity theft occurs, such as a sudden connection to a bypass circuit, current or power parameters will show significant abrupt changes. This dimension of analysis can detect such anomalies.

[0039] Frequency distortion analysis primarily targets harmonic-related electricity theft. By calculating harmonic distortion characteristic values, combining the current total harmonic distortion rate with the historical average harmonic distortion rate and the effective ratio of harmonic current to fundamental current, it analyzes whether the frequency distribution of electrical signals is normal. Some electricity theft behaviors introduce specific harmonics, causing an abnormally high total harmonic distortion rate. This dimension analysis can accurately capture such frequency anomalies, thereby identifying the corresponding electricity theft behaviors.

[0040] Energy balance analysis, from the perspective of energy conservation, calculates the power balance coefficient and compares the relationship between the active power measured by the electricity meter on the incoming side and the theoretical line loss. The theoretical line loss is calculated based on conductor resistance, electricity usage time, and current magnitude. Under normal electricity usage, the active power on the incoming side should equal the sum of the active power measured by the meter and the theoretical line loss. When there is electricity theft such as bypass wiring, some electrical energy is used directly without being measured by the meter, resulting in a discrepancy between the active power on the incoming side and the sum of the active power measured by the meter and the theoretical line loss. This dimension analysis can identify this type of energy-loss-type electricity theft.

[0041] The feature fusion and identification module employs a weighted voting algorithm to fuse the analysis results from the three dimensions. Based on the characteristics of different types of electricity theft, the weights of the analysis results for each dimension are dynamically adjusted. For example, for harmonic interference-related electricity theft, the analysis result for frequency distortion has a higher weight, while for bypass wiring-related electricity theft, the analysis result for energy balance will have its weight adjusted accordingly. By reasonably allocating weights and comprehensively analyzing the conclusions from the three dimensions, a clear electricity theft determination result is finally output and transmitted to the dual-mode communication control unit.

[0042] This multi-dimensional electrical feature recognition unit overcomes the limitations of single-parameter or single-dimensional recognition. By comprehensively collecting 12 electrical parameters and analyzing them from three dimensions—time, frequency, and energy—and combining them with a dynamic weighted voting algorithm, it can accurately distinguish between normal electricity fluctuations and various types of electricity theft. Its technical advantages are reflected in improved comprehensiveness and accuracy of electricity theft identification, effectively avoiding false positives and false negatives, and the ability to effectively identify different types of electricity theft, providing a reliable basis for subsequent alarms and control.

[0043] The time-dimensional mutation is detected by calculating the electrical parameter mutation coefficient to capture abnormal changes in electrical parameters. In the formula for calculating the electrical parameter mutation coefficient, the current electrical parameter value is the electrical parameter data acquired by the parameter acquisition module in the current sampling period, and the previous electrical parameter value is the same type of electrical parameter data acquired in the previous sampling period. The formula for calculating the electrical parameter mutation coefficient is as follows: ,in, These are the electrical parameter values ​​at the current moment. These are the electrical parameter values ​​from the previous moment. This refers to the coefficient of electrical parameter mutation. For example, in residential electricity use, under normal circumstances, the current parameter changes smoothly with the starting and stopping of household appliances. If, at a certain moment, the current parameter value changes significantly compared to the previous moment, the coefficient of electrical parameter mutation calculated by the formula will exceed the normal range. In this case, it can be determined that the parameter has a sudden change in the time dimension. This calculation method can intuitively reflect the instantaneous change amplitude of electrical parameters, promptly capture parameter mutations caused by electricity theft, and provide a time-dimensional basis for subsequent electricity theft identification.

[0044] Frequency-dimensional distortion is used to identify harmonic-related electricity theft by calculating harmonic distortion characteristic values. The current total harmonic distortion rate (THD) is the proportion of harmonic components in the total electrical signal acquired in real-time by the parameter acquisition module. The historical average THD is the average value calculated by the system based on THD data collected over a past period. The effective value of harmonic current is the sum of the effective values ​​of all harmonic currents in the electrical signal, and the effective value of fundamental current is the effective value of the fundamental current in the electrical signal. The formula for calculating the harmonic distortion characteristic values ​​is as follows: ,in, This represents the current total harmonic distortion (THD). The historical average harmonic distortion rate, This is the effective value of the harmonic current. This is the effective value of the fundamental current. This refers to the harmonic distortion characteristic value. For example, some electricity theft activities generate a large number of harmonics by connecting specific devices, resulting in a current total harmonic distortion rate that is significantly higher than the historical average harmonic distortion rate. Simultaneously, the effective value of the harmonic current will also increase accordingly. The harmonic distortion characteristic value calculated by the formula will show obvious anomalies, thus identifying harmonic interference-related electricity theft. This calculation method combines real-time harmonic data with historical harmonic data, and considers the ratio between harmonic current and fundamental current, enabling precise detection of electrical anomalies in the frequency dimension.

[0045] Energy balance analysis identifies electricity theft from an energy conservation perspective by calculating the power balance coefficient. The active power on the incoming line is the active power input from the power supply side to the incoming end of the electricity metering box. The active power measured by the meter is the active power recorded by the meter in the electricity metering box. The theoretical line loss is the active power loss caused by the resistance of the conductors in the transmission line, and its value is calculated based on the conductor resistance, the time of electricity use, and the current magnitude. The formula for calculating the power balance coefficient is as follows: ,in This refers to the active power on the incoming line side. For electricity meters to measure active power, Let B be the theoretical line loss and B be the power balance coefficient. In industrial power consumption scenarios, under normal circumstances, the active power on the incoming line should be approximately equal to the sum of the active power measured by the meter and the theoretical line loss, and the power balance coefficient will be within a reasonable range. If there is bypass wiring for electricity theft, some electrical energy is used directly without being measured by the meter, which will cause the active power on the incoming line to be much greater than the sum of the active power measured by the meter and the theoretical line loss. The power balance coefficient will exceed the normal range, thus enabling the identification of this type of electricity theft. This calculation method is based on the principle of energy conservation and can effectively capture energy-loss-type electricity theft, providing an energy-dimensional basis for electricity theft identification.

[0046] The calculation methods of the three coefficients mentioned above complement each other, constructing a complete electrical feature analysis system from the three dimensions of time, frequency, and energy. Through specific formula calculations, abstract electrical anomalies are transformed into quantifiable indicators, making the identification of electricity theft more accurate and reliable. Its technical effectiveness lies in its ability to comprehensively cover the electrical features of different types of electricity theft, avoiding the limitations of single-dimensional analysis, improving the accuracy and comprehensiveness of electricity theft identification, providing reliable basic data for subsequent weighted voting algorithms, and ensuring that the multi-dimensional electrical feature identification unit can accurately output electricity theft judgment results.

[0047] The core of the weighted voting algorithm in the feature fusion identification module is to dynamically allocate the weight proportions of the three-dimensional coefficients based on the feature differences of different types of electricity theft, ensuring that the voting results more closely reflect the actual characteristics of electricity theft. The weight adjustment is based on the performance intensity of various electricity theft behaviors in the three dimensions of time, frequency, and energy. The greater the contribution of a certain dimension to the identification of a specific electricity theft behavior, the higher its corresponding weight proportion.

[0048] When the system initially detects abnormal harmonic components in the electrical signal, it initiates the weight adjustment logic for harmonic interference-based electricity theft. The core characteristic of harmonic interference-based electricity theft is the introduction of harmonics through external devices, leading to abnormal frequency distribution in the electrical signal. This abnormality is most pronounced in the harmonic distortion feature value of the frequency dimension, while it is relatively weaker in the electrical parameter mutation coefficient of the time dimension and the power balance coefficient of the energy dimension. Therefore, for this type of electricity theft, the algorithm sets the weight of the harmonic distortion feature value to 0.5, making it dominant in the voting results; simultaneously, it sets the weight of the electrical parameter mutation coefficient to 0.3 and the power balance coefficient to 0.2, taking into account auxiliary judgments in both the time and energy dimensions.

[0049] In practice, the parameter acquisition module continuously collects electrical parameters, and the feature calculation component calculates the harmonic distortion characteristic value, electrical parameter mutation coefficient, and power balance coefficient. The system first normalizes the three coefficients, converting them into values ​​between 0 and 1, and then performs weighted calculations according to dynamically adjusted weights. For example, in a certain scenario, harmonic interference electricity theft results in a normalized harmonic distortion characteristic value of 0.9, a normalized electrical parameter mutation coefficient of 0.4, and a normalized power balance coefficient of 0.3. The weighted comprehensive score is 0.9×0.5+0.4×0.3+0.3×0.2. The final comprehensive score is compared with a preset threshold to determine whether it constitutes harmonic interference electricity theft.

[0050] Besides harmonic interference-based electricity theft, the algorithm also pre-sets corresponding weight allocation schemes for other types of electricity theft. For example, the core characteristic of bypass wiring-based electricity theft is energy loss, which is most prominent in the power balance coefficient of the energy dimension. In this case, the algorithm will adjust the weight of the power balance coefficient to the highest level. On the other hand, load shunting-based electricity theft may be accompanied by sudden changes in electrical parameters, so the weight of the electrical parameter mutation coefficient in the time dimension will be increased accordingly. The weight allocation schemes corresponding to different types of electricity theft are pre-stored in the feature fusion and recognition module. The system automatically matches the corresponding weight scheme based on the initially detected electrical anomaly features.

[0051] This dynamically weighted voting algorithm avoids the shortcomings of fixed weights, which cannot adapt to different types of electricity theft. Its technical advantages lie in its ability to optimize weight allocation based on the core characteristics of various electricity theft behaviors, making the identification results more targeted and accurate. This effectively reduces the risk of misjudgment or missed judgment due to the indistinctness of single-dimensional features, further enhancing the multi-dimensional electrical feature recognition unit's ability to identify different types of electricity theft behaviors, and providing a more reliable basis for subsequent alarms and control.

[0052] The dual-mode communication control unit is the core hub connecting the monitoring and identification module and the cloud management platform. Through the redundant design of the fifth-generation mobile communication module and the Beidou short message module, as well as the execution function of the electromagnetic relay, it realizes reliable data transmission and accurate execution of remote control commands.

[0053] The fifth-generation mobile communication module possesses high-speed data transmission capabilities, specifically designed for transmitting large volumes of data. The high-definition images stored in the end-to-end evidence retention unit constitute large-volume data, requiring a stable and high-speed transmission channel to ensure management personnel can promptly view the entire event process. The 12 electrical parameters collected by the multi-dimensional electrical feature recognition unit, although small in individual data points, require continuous real-time transmission to support dynamic monitoring on the cloud platform. The fifth-generation mobile communication module can meet the transmission needs of both types of data, sending high-definition images and electrical parameters to the cloud management platform in real time, allowing management personnel to remotely and intuitively grasp the operating status and abnormal conditions of the electricity metering box. For example, in urban residential communities, where fifth-generation mobile communication signals have comprehensive coverage, the module can stably transmit high-definition video and real-time electrical data for each abnormality trigger, supporting management personnel in quickly determining the nature of the event.

[0054] The BeiDou short message module serves as a backup communication channel, complementing the 5G mobile communication module. The system monitors the signal status of the 5G mobile communication module in real time. When a signal interruption or insufficient signal strength is detected, the BeiDou short message module automatically activates and switches to the primary communication mode. The BeiDou short message module does not rely on ground communication base stations and can operate normally in areas without 5G mobile communication signal coverage, such as underground power distribution rooms in remote mountainous areas. The information transmitted by this module focuses on core alarm content, including device identification codes, electricity theft types, and geographical location information. Device identification codes help managers quickly locate abnormal electricity metering boxes, the electricity theft type provides a reference for subsequent handling plans, and geographical location information facilitates accurate device location for staff. For example, in remote rural areas where 5G mobile communication signals are weak and prone to interruption, the BeiDou short message module can promptly transmit abnormal information to the cloud, ensuring that alarms are not lost.

[0055] The electromagnetic relay is the actuator of the dual-mode communication control unit, directly linked to the on / off control of the incoming power supply. When the dual-mode communication control unit receives a remote power-off command from the cloud management platform via a fifth-generation mobile communication module or a Beidou short message module, it immediately sends a control signal to the electromagnetic relay. Upon receiving the signal, the electromagnetic relay's internal contacts quickly actuate, cutting off the incoming power supply to the electricity metering box and preventing further illegal use of electricity. The power-off operation only affects the incoming power supply and will not affect the power supply to other unrelated lines, ensuring the accuracy and safety of the operation. For example, when the system identifies a clear act of electricity theft and sends a level-two alarm, the administrator confirms the situation through the cloud platform and issues a remote power-off command. After receiving the command, the dual-mode communication control unit controls the electromagnetic relay to quickly cut off the power supply and curb the continued occurrence of electricity theft.

[0056] The dual-mode communication control unit achieves reliable data transmission and effective remote control through automatic switching between two communication modules and efficient execution of electromagnetic relays. Its technical advantages include ensuring smooth communication in different environments, avoiding alarm information loss issues caused by single communication methods, and rapidly responding to remote control commands to promptly cut off power and prevent electricity theft, thus reducing losses for power supply companies and ensuring power supply safety and accurate electricity metering.

[0057] The end-to-end evidence retention unit, through the collaborative work of the image acquisition module, data storage module, and log encryption module, comprehensively records all kinds of evidence related to physical damage and electricity theft, forming a complete and tamper-proof chain of evidence.

[0058] The image acquisition module remains in standby mode, continuously caching the most recent 5 seconds of video data. Upon receiving a monitoring signal from the physical anti-tamper monitoring unit or a theft identification result from the multi-dimensional electrical feature recognition unit, the module immediately initiates formal recording. The recording includes 5 seconds of cached video before the trigger and 5 seconds of real-time video after the trigger. The cached video completely recreates the scene before the abnormal event, while the real-time video records the event's occurrence; the combination of both ensures no event is missed. Simultaneously, the module automatically captures keyframe photos, focusing on the door status, internal wiring, and abnormal areas. Door status photos clearly show whether the door is open, closed, or damaged; internal wiring photos reflect whether wiring is loose, displaced, or has bypassed connections; and abnormal area photos focus on key anomalies such as foreign object intrusion and drilling marks. For example, when someone attempts to pry open the electricity metering box, the image acquisition module immediately records video before and after the trigger, capturing pry marks on the door and photos of the surrounding environment, providing direct visual evidence for determining illegal opening.

[0059] The data storage module is specifically designed to store raw electrical parameter data. When no abnormal signal is triggered, the module stores electrical parameters at a set frequency. Upon receiving an abnormal trigger signal, the module prioritizes storing the raw electrical parameter data for the 30 seconds before and after the trigger. This data includes sampling point data for each of 12 parameters, such as three-phase voltage, three-phase current, active power, reactive power, harmonic content, and power factor, ensuring the continuity and integrity of the electrical parameters. This raw data is crucial for analyzing whether electricity usage is abnormal and can be corroborated by video evidence. For example, when harmonic interference is detected as electricity theft, the harmonic content data stored in the data storage module for the 30 seconds before and after the trigger clearly shows the change process of harmonic components, providing data support for technical analysis and electricity theft determination.

[0060] The log encryption module uses blockchain technology to store operation logs, which cover all key information related to device operation, including power-on time, authorization start records, alarm trigger times, and remote control command execution status. Blockchain technology, through the principle of distributed ledger, synchronously stores each log record across three or more redundant nodes, with each node holding complete log data. Any attempt to tamper with the logs would require modifying the data on all nodes simultaneously, and the distributed storage characteristic makes such tampering extremely difficult. The log encryption module also encrypts the log data during storage, further ensuring data security. For example, the execution log of a remote power-off command is synchronously stored across multiple nodes, ensuring that the log data cannot be illegally tampered with or deleted, providing a reliable basis for subsequent event tracing and accountability.

[0061] The end-to-end evidence retention unit forms a complete chain of evidence that complements and corroborates each other through the comprehensive retention and encrypted storage of three types of evidence: image data and logs. Its technical effectiveness lies in ensuring the authenticity, integrity, and legality of the evidence, meeting the requirements of judicial evidence collection, and providing strong support for holding perpetrators of electricity theft accountable. At the same time, the complete chain of evidence also deters potential electricity thieves, reducing the occurrence of electricity theft and protecting the legitimate rights and interests of power supply companies and the accuracy of electricity metering.

[0062] Specific limitations regarding the intelligent monitoring and control system for preventing electricity theft in electricity metering boxes can be found in the limitations of the intelligent monitoring and control method for preventing electricity theft in electricity metering boxes below, and will not be repeated here. Each module in the aforementioned intelligent monitoring and control system for preventing electricity theft in electricity metering boxes can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of the processor, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0063] In one embodiment, such as Figure 2As shown, an intelligent monitoring and control method for preventing electricity theft in an electricity metering box is provided, which is then applied to... Figure 1 Taking China as an example, the following specific steps will be used:

[0064] S10: After the device completes its self-test, it synchronizes the user's historical electricity consumption data to build a normal electricity consumption feature database.

[0065] S20: The physical anti-tamper monitoring unit collects and processes sensor data, and the multi-dimensional electrical feature recognition unit collects electrical parameters and calculates the electrical parameter mutation coefficient, harmonic distortion characteristic value and power balance coefficient in real time.

[0066] S30: When physical damage is detected, the image acquisition module is activated to record evidence and a first-level alarm is sent through the dual-mode communication control unit. When electricity theft is identified, the image acquisition module is activated to record evidence, a second-level alarm is sent through the dual-mode communication control unit, and the electromagnetic relay is controlled to cut off the incoming power supply.

[0067] S40: After viewing alarm information and evidence information and issuing control commands through the cloud management platform, the administrator can extract encrypted evidence files from the end-to-end evidence retention unit for judicial evidence collection.

[0068] Specifically, after powering on, the device first enters the initialization phase, completing a comprehensive self-test process. The self-test covers the sensors and sealing structure of the physical anti-tamper monitoring unit, the parameter acquisition module and feature fusion recognition module of the multi-dimensional electrical feature recognition unit, the two communication modules and electromagnetic relays of the dual-mode communication control unit, and all modules of the end-to-end evidence retention unit. After all modules are functioning normally, the device automatically synchronizes the user's historical electricity consumption data. This historical data includes changes in 12 electrical parameters, such as three-phase voltage, three-phase current, and active power, over a past period. The device categorizes, organizes, and statistically analyzes this data to construct a user-specific normal electricity consumption feature database. This database provides a benchmark for subsequent electricity theft identification. Different users have different electricity consumption habits and equipment configurations, resulting in different normal electricity consumption feature databases. For example, a residential user's database might reflect parameter fluctuations caused by the start-up and shutdown of household appliances, while an industrial user's database might reflect the characteristics of electrical parameter changes during the operation of production equipment.

[0069] After initialization, the device enters the real-time monitoring phase, with each functional unit operating continuously and stably. The physical anti-tamper monitoring unit's triaxial accelerometer, infrared distance sensor, and Hall sensor continuously collect data. The collected data is transmitted in real-time to the filtering module, where a Kalman filter algorithm removes invalid information caused by environmental interference, ensuring the accuracy of the monitoring data. The parameter acquisition module of the multi-dimensional electrical feature recognition unit collects electrical parameters at a set frequency. The collected parameters are transmitted in real-time to the feature fusion recognition module. Based on benchmark data in the normal power consumption feature database, the module calculates the electrical parameter mutation coefficient, harmonic distortion characteristic value, and power balance coefficient in real-time, continuously comparing and analyzing the differences between the current power consumption state and the normal power consumption state.

[0070] During monitoring, the system continuously assesses for any abnormalities. When the physical anti-tamper monitoring unit detects physical damage such as vibration of the box, intrusion of foreign objects, opening of the box door, or breakage of the conductive circuit, and the dual verification of the authorized opening component fails, the system immediately activates the image acquisition module. The image acquisition module begins recording buffered video for 5 seconds before the trigger and real-time video for 5 seconds after the trigger, while simultaneously capturing key frame photos of the box door status, internal wiring, and abnormal areas. The dual-mode communication control unit simultaneously sends a Level 1 alarm, transmitting the alarm information to the cloud management platform via a fifth-generation mobile communication module or a Beidou short message module, alerting management personnel to the physical security of the electricity metering box. For example, if someone attempts to pry open the electricity metering box and the physical anti-tamper monitoring unit detects a vibration signal, the system immediately initiates evidence recording and a Level 1 alarm process.

[0071] When the multi-dimensional electrical feature identification unit, through comparative analysis, finds that the electrical parameter mutation coefficient, harmonic distortion characteristic value, or power balance coefficient exceeds the benchmark range of the normal electricity consumption feature database, and determines it as electricity theft through a weighted voting algorithm, the system initiates a more stringent handling process. The image acquisition module also records video before and after the trigger and captures keyframe photos, and each module of the end-to-end evidence retention unit synchronously stores relevant evidence. The dual-mode communication control unit sends a secondary alarm, transmitting information such as the type of electricity theft and device identification code to the cloud management platform. Simultaneously, the dual-mode communication control unit receives a remote power-off command from the cloud platform, controlling the electromagnetic relay to quickly cut off the incoming power to the electricity metering box, preventing the continued electricity theft. For example, when the system identifies harmonic interference-related electricity theft, it immediately initiates the evidence recording, secondary alarm, and remote power-off processes.

[0072] Management personnel receive Level 1 or Level 2 alarm information in real time through a cloud-based management platform. The platform intuitively displays key information such as alarm type, device location, and trigger time. Management personnel can view videos and photos recorded by the image acquisition module and raw electrical parameter data stored by the data storage module at any time. Based on this information, management personnel can quickly determine the nature and severity of the incident and issue appropriate control commands promptly. If electricity theft is involved and legal prosecution is required, management personnel can retrieve encrypted video evidence, data evidence, and log evidence from the end-to-end evidence retention unit through the cloud-based management platform. This evidence is encrypted and stored using blockchain technology, ensuring its authenticity, legality, and immutability, and can be directly used in the judicial evidence collection process, providing strong support for pursuing accountability for electricity theft.

[0073] The entire process forms a complete closed loop, from initial database construction and real-time monitoring to anomaly trigger handling and evidence tracing. Its technical effectiveness is reflected in the timely detection, rapid response, and effective handling of physical sabotage and electricity theft, ensuring the accuracy of electricity metering and power supply security. The comprehensive evidence retention and tracing mechanism provides reliable guarantees for judicial accountability, while also serving as a strong deterrent to potential electricity thieves, effectively reducing the occurrence of electricity theft and safeguarding the legitimate rights and interests of power supply companies.

[0074] Optionally, the recovery process after the dual-mode communication control unit sends a secondary alarm and controls the electromagnetic relay to cut off the incoming power is as follows: after dual authorization through device identification code verification of the encryption key and identity recognition by the face recognition module, the dual-mode communication control unit controls the electromagnetic relay to close and restore power supply.

[0075] Specifically, authorized personnel first bring the encryption key close to the sensing area of ​​the metering box. The verification module built into the dual-mode communication control unit automatically reads the unique device identification code stored in the encryption key. The verification module compares the read device identification code with the legitimate device identification codes pre-stored in the system to confirm the legality of the encryption key.

[0076] After successful verification of the device identification code, the facial recognition module automatically activates, and the camera captures the facial image of the current operator. The module extracts real-time facial features using an offline recognition algorithm and accurately compares them with the facial features of authorized personnel stored locally. Simultaneously, a liveness detection function eliminates deception methods such as photos and videos, ensuring the operator's true identity.

[0077] The dual-mode communication control unit will only receive a valid power restoration trigger signal when both conditions are met: the device identification code of the encryption key is verified successfully, and the facial recognition module successfully identifies the user. Subsequently, the dual-mode communication control unit sends a closing command to the electromagnetic relay, causing the internal contacts of the electromagnetic relay to activate, connecting the incoming power supply and restoring normal power supply to the electricity metering box.

[0078] If the device identification code comparison fails, or the facial recognition fails, the dual-mode communication control unit will not send a closing command, the electromagnetic relay will remain open, and the incoming power supply will remain cut off. For example, after electricity theft is stopped, authorized maintenance personnel from the power supply company must arrive on-site to handle the situation. The maintenance personnel must complete dual authorization using their own encrypted key and facial verification before power can be restored, preventing the electricity thief from reconnecting the circuit breaker and continuing to illegally use electricity.

[0079] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A smart monitoring and control system for preventing electricity theft in electricity metering boxes, characterized in that, include: Physical tamper-proof monitoring unit, multi-dimensional electrical feature recognition unit, dual-mode communication control unit, and full-link evidence retention unit; The physical anti-tamper monitoring unit monitors physical damage to the electricity metering box and outputs monitoring signals; the multi-dimensional electrical feature identification unit collects electrical parameters and identifies electricity theft. The dual-mode communication control unit receives monitoring signals and electricity theft identification results, transmits data, and executes remote control commands; the end-to-end evidence retention unit stores monitoring data, image information, and operation logs based on monitoring signals and electricity theft identification results.

2. The intelligent monitoring and control system for preventing electricity theft in electricity metering boxes according to claim 1, characterized in that, include: The physical anti-tamper monitoring unit includes a sealing structure, a conductive circuit assembly, a multi-sensor assembly, and an authorized opening assembly. The sealing structure is a one-piece molded stainless steel enclosure with laser-welded seams and an anti-drill steel plate fixedly installed inside the enclosure wall. The conductive circuit assembly is a flexible conductive sealing gasket that fits the door and the enclosure seam to form a closed conductive circuit. The multi-sensor assembly includes a triaxial accelerometer, an infrared distance sensor, and a Hall sensor. The data collected by these three sensors are processed by a Kalman filter algorithm and then output to the dual-mode communication control unit.

3. The intelligent monitoring and control system for preventing electricity theft in the electricity metering box according to claim 2, characterized in that, The authorization unlocking components include an encryption key and a facial recognition module; the encryption key has a built-in encryption chip that stores a unique device identification code; the facial recognition module performs offline authorization personnel identification, and the electronic lock unlocks only when the device identification code of the encryption key is verified and the facial recognition module is successfully identified.

4. The intelligent monitoring and control system for preventing electricity theft in electricity metering boxes according to claim 1, characterized in that, The multi-dimensional electrical feature identification unit includes a parameter acquisition module and a feature fusion identification module. The parameter acquisition module acquires 12 electrical parameters, including three-phase voltage, three-phase current, active power, reactive power, harmonic content, and power factor. The feature fusion identification module constructs a three-dimensional feature identification model based on time dimension abrupt change, frequency dimension distortion, and energy dimension balance, and outputs the electricity theft judgment result to the dual-mode communication control unit through a weighted voting algorithm.

5. The intelligent monitoring and control system for preventing electricity theft in electricity metering boxes according to claim 4, characterized in that, The time dimension abrupt change is achieved by calculating the abrupt change coefficient of electrical parameters, and the formula for calculating the abrupt change coefficient of electrical parameters is as follows: ,in, These are the electrical parameter values ​​at the current moment. These are the electrical parameter values ​​from the previous moment. The electrical parameter abrupt change coefficient; frequency dimension distortion is achieved by calculating harmonic distortion characteristic values, the formula for calculating the harmonic distortion characteristic values ​​is as follows: ,in, This represents the current total harmonic distortion (THD). The historical average harmonic distortion rate, This is the effective value of the harmonic current. This is the effective value of the fundamental current. The characteristic value is the harmonic distortion value; energy dimensional balance is achieved by calculating the power balance coefficient, and the formula for calculating the power balance coefficient is: ,in This refers to the active power on the incoming line side. For electricity meters to measure active power, B represents the theoretical line loss, and B is the power balance coefficient.

6. The intelligent monitoring and control system for preventing electricity theft in electricity metering boxes according to claim 4, characterized in that, The weighted voting algorithm of the feature fusion identification module dynamically adjusts the weights according to the type of electricity theft; when it is determined to be electricity theft due to harmonic interference, the weight of the harmonic distortion feature value is 0.5, the weight of the electrical parameter mutation coefficient is 0.3, and the weight of the power balance coefficient is 0.

2.

7. The intelligent monitoring and control system for preventing electricity theft in electricity metering boxes according to claim 1, characterized in that, The dual-mode communication control unit includes a fifth-generation mobile communication module, a Beidou short message module, and an electromagnetic relay. The fifth-generation mobile communication module transmits high-definition images and electrical parameters. The Beidou short message module automatically switches when the fifth-generation mobile communication signal is interrupted, transmitting the device identification code, electricity theft type, and geographical location information. After receiving a remote power-off command, the dual-mode communication control unit controls the electromagnetic relay to cut off the incoming power supply.

8. The intelligent monitoring and control system for preventing electricity theft in electricity metering boxes according to claim 1, characterized in that, The end-to-end evidence retention unit includes an image acquisition module, a data storage module, and a log encryption module. The image acquisition module records a 5-second buffered video before triggering and a 5-second real-time video after triggering, and captures key frame photos of the door status, internal wiring, and abnormal areas. The data storage module stores the raw electrical parameter data for 30 seconds before and after triggering. The log encryption module uses blockchain technology to store operation logs, with more than three redundant nodes deployed on the blockchain.

9. A smart monitoring and control method for preventing electricity theft in an electricity metering box, characterized in that, include: After the equipment completes its self-test, it synchronizes the user's historical electricity consumption data to build a normal electricity consumption characteristic database. The physical anti-tamper monitoring unit collects and processes sensor data, while the multi-dimensional electrical feature recognition unit collects electrical parameters and calculates electrical parameter mutation coefficient, harmonic distortion characteristic value and power balance coefficient in real time. When physical damage is detected, the image acquisition module is activated to record evidence and a level one alarm is sent through the dual-mode communication control unit. When electricity theft is detected, the image acquisition module is activated to record evidence, a level two alarm is sent through the dual-mode communication control unit, and the electromagnetic relay is controlled to cut off the incoming power supply. After viewing alarm and evidence information and issuing control commands through the cloud management platform, managers can extract encrypted evidence files from the end-to-end evidence retention unit for judicial evidence collection.

10. The intelligent monitoring and control method for preventing electricity theft in an electricity metering box according to claim 9, characterized in that, The recovery process after the dual-mode communication control unit sends a level 2 alarm and controls the electromagnetic relay to cut off the incoming power is as follows: After dual authorization through device identification code verification of the encryption key and identity recognition by the face recognition module, the dual-mode communication control unit controls the electromagnetic relay to close and restore power supply.

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