14323 results about "Electric current flow" patented technology

The invention discloses an intelligent cable fault diagnosis and positioning method and system, and relates to the technical field of intelligent operation and maintenance of a power system. The method is used for accurately identifying and positioning high-resistance faults and external damage. According to the method, electric field, current, temperature and vibration signals are synchronously collected, a multi-source fusion enhanced signal flow is constructed, and multi-physical field features are extracted; based on a coupling mechanism of an electromagnetic-thermal field and a mechanical-electric field, generating a fault type label and a space coordinate; executing targeted impedance correction for different fault types, establishing a dynamic topology network, and inputting a time-space diagram neural network to output a preliminary positioning result; and multi-source verification is carried out by further fusing salinity dielectric, a harmonic thermal field, a vibration electric field and stress topological information, a high-confidence-coefficient fault positioning result is finally output, a closed-loop diagnosis mechanism is formed, and the fault recognition accuracy and the system adaptability under complex working conditions are improved.

Air conditioning device (1) for motorhomes, comprising: - at least one first heat exchanger for exchanging heat with the air circulating through it; - a cooling circuit (8) for a cooling fluid, with a path passing through the first heat exchanger; - a compressor (7) which includes an electric motor, for circulating the cooling fluid in the cooling circuit (8); - a power supply unit that can be connected to an external power supply to receive an electrical input current or electrical input power and to generate a variable supply voltage to drive the electric motor with an electrical supply current, - a controller (11) connected to the power supply unit that is suitable for receiving input data representative of a reference value of the electrical input current or electrical input power and that is programmed to adjust the power supply unit to generate the supply voltage with a reference amplitude and / or frequency such that the electrical input current or electrical input power is below the reference value; - a positioning device designed to determine the position of the air conditioning device (1); and - a memory containing a plurality of reference values ​​corresponding to a plurality of locations, wherein the controller (11) is capable of receiving a location signal from the positioning device and of setting as input data one of the reference values ​​present in the memory depending on the location signal.

The invention discloses a primary and secondary fusion pole-mounted intelligent circuit breaker. The primary and secondary fusion pole-mounted intelligent circuit breaker comprises a fault detection module, a protection action module, a reclosing module and an information reporting module, the fault detection module collects multi-dimensional electrical quantity through a current transformer and a voltage transformer, and judges a fault and identifies the type in combination with a dynamic normal range and a duration threshold. The protection action module calculates the fault distance based on the correction impedance, judges whether to act or not by combining the current flow direction and the protection range, and selects a protection level according to the fault severity; the reclosing module dynamically sets an observation time window, distinguishes instantaneous or permanent faults through a retest verification mechanism, and adaptively adjusts a reclosing strategy; and the information reporting module uploads fault related information. According to the method, the problems of high misjudgment rate, poor protection selectivity, rigid reclosing logic and the like of a traditional circuit breaker are solved, and the accuracy, quickness and self-healing capability of power distribution network fault processing are remarkably improved.

The invention relates to the technical field of electric energy metering and electric power system safety, and discloses an electricity larceny prevention method and system for multi-source data fusion of an electric energy meter, and the method comprises the steps: obtaining and preprocessing current and voltage waveform data and user electricity consumption behavior data; generating multi-dimensional power consumption characteristic parameters, performing screening to form a characteristic vector set, and constructing an abnormal power consumption detection reference set; dynamically verifying power utilization data based on the reference set, and analyzing a phase relation and a mismatch state of current and voltage signals; and generating an electricity consumption behavior deviation index to judge an electricity stealing behavior. The system comprises a multi-source data acquisition module, a feature modeling analysis module, an electrical relation verification module and an electricity stealing judgment module. According to the invention, through multi-source data fusion and multi-dimensional feature analysis, accurate detection of electricity larceny behaviors is realized, accuracy and reliability of electricity larceny prevention are improved, and the method is suitable for power utilization safety management of a smart power grid.

The invention relates to the technical field of hybrid inverters, and discloses a hybrid inverter supporting reactive compensation and a control method thereof, and the hybrid inverter comprises a DC input unit, a three-phase full-bridge inversion unit, a grid-connected switching unit, a signal acquisition unit and a digital control unit. The direct current input unit comprises a photovoltaic interface, a battery interface and a direct current bus and is used for converging photovoltaic and energy storage electric energy; the three-phase full-bridge inversion unit is composed of a power device and an LCL filter and converts direct current into alternating current. The grid-connected switching unit comprises a static switch and an isolation transformer and is used for controlling power grid connection; the signal acquisition unit detects voltage and current signals; and the digital control unit judges a grid-connected mode or an off-grid mode according to the signal, calculates a reactive current reference value and generates a PWM (Pulse Width Modulation) control signal so as to realize reactive compensation control in the grid-connected mode and the off-grid mode. According to the invention, reactive power compensation capability is provided in both grid-connected and off-grid operation modes, and stable operation of the inverter in various working conditions is ensured.

The invention discloses a charging method and system based on battery dynamic health state evaluation and learning prediction, belongs to the technical field of electric vehicle charging, and aims to solve the technical problem of how to break through a traditional BMS information barrier, realize deep perception and accurate prediction of a microcosmic dynamic health state in a battery, and improve the charging efficiency. According to the technical scheme, when the electric vehicle is connected to a charging pile, the charging pile establishes a communication link with a BMS (battery management system) of the vehicle through a standard protocol; a current or voltage disturbance signal with a specific frequency spectrum is injected into the battery, a response signal of the battery is measured synchronously, and dynamic health state parameters of the battery of the electric vehicle are collected in real time; and analyzing the dynamic health state parameters of the battery of the electric vehicle by using a pre-trained deep learning model, predicting the health state evolution trend of the battery, and generating a multi-target charging parameter optimization scheme.

The invention discloses a new energy commercial vehicle fast charging working condition thermal management control method and system, and relates to the technical field of new energy vehicle thermal management and fast charging control, and the method comprises the following steps: collecting the temperature, voltage and current data of each subarea of a battery in a fast charging process, forming a time synchronization sequence, and based on the sequence, obtaining a new energy commercial vehicle fast charging condition; calculating internal thermal resistance and thermal capacity parameters of the battery in real time by using an online identification algorithm, updating a basic thermal model to obtain a corrected thermal dynamic model reflecting actual thermal characteristics of the current battery, importing the corrected model into a model prediction controller, constructing a multi-objective optimization function, and performing rolling solution in a prediction time domain to obtain a prediction model; and outputting an optimal target charging current instruction and a cooling total demand, adjusting the charging power according to the target current, and combining the temperature difference distribution of each partition. Accurate prediction and partition cooperative control of the thermal state of the battery in the fast charging process are achieved, the temperature rise and the temperature difference are effectively restrained while the charging efficiency is guaranteed, the service life of the battery is prolonged, and the system safety is improved.

The invention provides a battery health state evaluation method, device and equipment and a medium, and the method comprises the steps: collecting multi-source parameters of a power battery in a charge-discharge cycle process, the multi-source parameters comprising voltage, current, temperature and electrochemical impedance spectroscopy; performing feature engineering processing on the multi-source parameters based on a battery aging mechanism, and extracting key feature parameters; the key characteristic parameters are input into a multi-physics field coupling model to simulate thermoelectric coupling behaviors of the battery under a dynamic load, lithium ion concentration distribution and temperature distribution in the battery are obtained, and the multi-physics field coupling model is used for representing a coupling relation between an electrochemical field and a thermal field of the battery; and fusing the key characteristic parameters with data output by the multi-physics field coupling model, and determining a health state evaluation result of the power battery. According to the invention, the accuracy of power battery health state evaluation is improved.

The invention belongs to the crossing field of artificial intelligence and process control, particularly relates to an intelligent coupling control strategy for chlorine production through seawater electrolysis based on digital twinning, and aims to solve the problems of response lag, weak disturbance suppression and lack of electrode aging early warning in a traditional control method. According to the strategy, a high-fidelity digital twin fusing electrochemistry, fluid and thermodynamics is constructed, characteristics of current, temperature, impedance spectroscopy and the like are collected and fused at high frequency through a multi-source sensor, a state space model driven by a deep recurrent neural network is established, and current efficiency and electrode aging coupling evolution recognition is achieved; when salinization or flow mutation is detected, the twinborn body predicts and dynamically calibrates the current density and the voltage set value in advance, and the safety process window is synchronously scaled. According to the strategy, the chlorine gas yield fluctuation is reduced by 60%, the energy consumption standard deviation is reduced by 45%, the fault early warning is advanced by 2-5 hours, the fault-free operation time of the system is prolonged by 50%, and high-precision, self-adaptive and preventive intelligent control of the electrolysis process is realized.

The invention provides a sensorless motor stator temperature protection method, device and equipment, and relates to the technical field of motor control, and the protection method comprises the steps: obtaining the current voltage, current and rotating speed of a motor when the motor in a motor control system is in a running state, determining a corresponding temperature rise coefficient and a heat balance temperature according to the current voltage, the current current and the current rotating speed; obtaining a current estimated temperature according to the current voltage, the current current and the current rotating speed; determining a current predicted temperature according to the current estimated temperature, the heat balance temperature, the last estimated temperature and the corresponding temperature rise coefficient; and comparing the current predicted temperature with a preset protection threshold value, and performing temperature protection control on the motor according to a comparison result. A temperature sensor does not need to be installed in the motor, so that the installation difficulty and cost are reduced, the reliability and durability of the system are improved, and the risk that the sensor breaks down or is damaged is avoided.

The invention provides a vehicle network integration cooperative regulation and control method and system. The method comprises the following steps that 1, the system collects access parameters of multiple types of charging facilities; 2, constructing a power distribution network safety evaluation model based on the data collected in the step 1; 3, determining a charging label of the accessed electric vehicle according to the product of the real-time SOC and the SOH; 4, comparing the three-phase voltage deviation, the current unbalance degree and the load growth rate of the power distribution network with the history in the same period to obtain an overload risk rate, and further calculating a power grid safety margin coefficient; 5, calculating a final safety evaluation result to truly reflect the vulnerability level of the current power grid; and step 6, constructing a digital twinborn model of the target area, performing simulation verification on the initial instruction, and collecting equipment state, vehicle response and power grid operation data after regulation and control. By applying the technical scheme, an efficient and collaborative vehicle network interaction system can be realized, and deep fusion and collaborative development of the energy and traffic fields can be promoted.

The present invention relates to the technical field of energy meter electrical parameter measurement. Disclosed is an intelligent anti-interference system for a power line carrier energy meter. The system comprises: collecting voltage and current signals of a power line, and constructing a sample database; performing time-frequency feature classification by means of a preset model, and establishing feature and scenario mapping by synchronizing scenario recognition results; building a scenario interference recognition network on the basis of the mapping result; collecting real-time data of N communication channels of a power line carrier energy meter, and performing channel coordination decision and anti-interference enhancement; performing communication data evaluation on the basis of a comprehensive scoring function; and performing anti-interference management on the basis of channel access decision, anti-interference enhancement, and a parallel access result. The present invention solves the technical problem of poor accuracy and reliability of metering data of existing power line carrier energy meters caused by interference signals and noise when the power line carrier energy meters are in complex electromagnetic environments, and achieves the technical effect of improving the anti-interference capability and the reliability of the power line carrier energy meters.

The invention provides a general electromechanical transient modeling method and system for a network-building converter, and relates to the technical field of electromechanical transient modeling, and the method comprises the steps: simplifying the electromagnetic transient models of network-building converters of different topologies into a grid-connected equivalent circuit of an electromechanical transient time scale; uniformly representing by using an internal potential series reactance model controlled by a power outer ring so as to establish an electromechanical transient general grid-connected interface model of the grid-forming converter; combining mathematical transformation of active power control with a reactive power control mode to form a general power outer loop control model of the network construction type converter; through a method based on internal potential reconstruction, reconstructing a new internal potential satisfying a current limiting constraint, and establishing a general current limiting model suitable for a network construction type electromechanical transient model; according to the method, various topological structures, various power outer loop control and various current limiting strategies can be simulated, flexible use of models in large-scale power system simulation is facilitated, and the complexity of model development and maintenance is reduced.

According to the cable multi-parameter fusion sensor and method, in the cable multi-parameter fusion sensor, a shielding shell is of an open-close type metal annular structure; the zero-flux sensor module is arranged on the inner layer of the shielding shell so as to detect a cable sheath ring current signal; the pulse current sensor module is arranged on the outer side of the zero-flux sensor module so as to detect a cable partial discharge pulse current signal and an overvoltage impact current signal; the magnetic shielding layer is arranged between the zero-flux sensor module and the pulse current sensor module to shield low-frequency magnetic field interference; the zero magnetic flux sensor module and the pulse current sensor module share the shielding shell to form an electromagnetic shielding structure.

The invention discloses a non-intrusive household load identification method based on CUSUM event detection and a convolutional neural network, which is applied to total load data output by an intelligent electric meter installed at a user total incoming line, and comprises the following steps: data preprocessing; carrying out load event detection based on a sliding window bilateral CUSUM algorithm so as to determine an occurrence moment and a continuous interval of a load event; in a continuous interval corresponding to each load event, calculating an active power variation delta P, a reactive power variation delta Q, a current harmonic distortion variation delta Ihd and a current span Itc in steady-state data segments before and after the load event, and combining to form a multi-dimensional event feature vector; the method comprises the following steps: sequentially executing the steps on operation data of each electric device in a family in different operation modes to obtain a multi-dimensional event feature vector marked with a device type and an operation state label, and constructing a standardized device load feature database; and training a convolutional neural network classification model and realizing load identification.

The invention relates to the technical field of data processing, and provides a battery performance detection device and method, and the method comprises the steps: obtaining transient voltage data and transient current data of a battery in different working states, carrying out the wavelet decomposition of the transient voltage data, obtaining a multi-state voltage feature, carrying out the time sequence mapping of the multi-state voltage feature and the transient current data, and obtaining a multi-state voltage feature; and obtaining an inflection point parameter set to construct a parameter stability matrix, analyzing a battery health state based on the parameter stability matrix, generating a battery life prediction based on a health state index, and performing trend analysis and residual life estimation to generate a battery performance detection result. When a complex electrochemical environment and various working states are processed, the efficiency and accuracy of battery performance detection are improved, and the problems of long battery test period and poor detection precision in practical application are solved.

The embodiment of the invention provides a current adjusting method for a battery in a vehicle, the vehicle and a computer readable storage medium, and the method comprises the steps: detecting the working state of a charging pile and the charging state of the battery in the charging process of the battery in the vehicle; in response to the condition that the charging pile is in the normal working mode and the current charging performance index of the battery meets a charging current up-regulation condition, determining a charging current up-regulation parameter of the battery; increasing the initial request charging current of the battery based on the charging current increasing parameter to obtain a target request charging current; controlling the charging pile to charge the battery according to the target request charging current; and in the process of charging the battery by the charging pile, in response to the situation that the battery does not meet the charging current up-regulation condition, reducing the target request charging current of the battery based on the current demand charging current of the battery. The technical problem that the charging current is frequently adjusted according to the preset charging curve in the prior art, and the battery health of the vehicle is affected is solved.

The invention relates to the technical field of welding automation, and discloses an intelligent welding system for an electric pole steel reinforcement framework. The system comprises a welding execution module, a multi-mode sensing module, an edge calculation module, a real-time regulation and control module and a system control center. Synchronous collection and real-time analysis of images, temperature and sound signals of a welding pool area are achieved, so that defects such as air holes, slag inclusion and incomplete fusion can be recognized online in a key time window when the welding pool is not solidified, and time delay caused by a traditional off-line detection mode is thoroughly eliminated. Through a real-time regulation and control module, on the basis of a multi-target optimization decision and parameter self-adaptive adjustment mechanism, the system can dynamically adjust key process parameters such as welding current, arc voltage and welding speed at the moment of identifying defect germination or process deviation, and real-time intervention and closed-loop control on welding quality are achieved; therefore, the final formation of defect welding seams is avoided fundamentally, and the rework rate and the material waste are remarkably reduced.

The invention relates to the technical field of fuel cells, in particular to a method and system for accurately controlling the hydrogen stoichiometric ratio of a fuel cell, and the method comprises the steps: firstly, obtaining a quantitative anode health state value through a fusion calculation model by collecting load current, anode inlet and outlet pressure, temperature, high-frequency resistance and other multi-source signals in real time; a feed-forward model based on a load current change rate predicts sudden change of hydrogen demand, and an optimal hydrogen flow instruction is jointly generated in combination with output of a PID controller which adaptively adjusts parameters according to a health state value. According to the method, the integrated diagnosis parameter, namely the anode health state value, is created, so that the internal state of the fuel cell can be accurately perceived and prospectively judged. Through deep fusion of multi-source heterogeneous information such as high-frequency resistance, anode pressure difference, current and temperature, a comprehensive index capable of comprehensively and quantitatively reflecting anode water content, gas concentration and runner smoothness is generated.

The invention relates to the technical field of water electrolysis hydrogen production, and discloses an electrolytic bath outlet temperature control method and system, a medium and a program product, a flow control valve is arranged at an inlet of an electrolytic bath, the electrolyte input flow is converted into a core regulation variable directly influencing the outlet temperature, and active control over the outlet temperature is achieved. Furthermore, the flow control valve is directly connected with the control device, the opening degree signal can be received in real time, the flow can be adjusted, it is ensured that the temperature control instruction can be rapidly converted into the actual flow change, and the response speed to power fluctuation is increased. Furthermore, through a real-time operation state parameter set and a real-time temperature monitoring parameter set, it is ensured that a control signal is generated based on a real working condition, and the temperature control stability under fluctuating power is improved. Furthermore, through the synergistic effect of an electrolyte flow feedforward control signal and an electrolyte flow rear-end control signal, frequent current change caused by wind-solar power fluctuation can be effectively handled, and the fluctuation amplitude of the outlet temperature is reduced.

The invention relates to the technical field of power distribution fault positioning, in particular to a power distribution single-phase earth fault positioning method and device based on multi-source information fusion. The device comprises a data acquisition module, a fault line selection module, a grading emergency module, a fault positioning module and a parameter optimization module. According to the method, the zero-sequence current is monitored in real time, the dynamic change curve is generated, the fault line is accurately identified in combination with amplitude and phase characteristics, electrical parameters, environmental factors and load importance are fused to carry out comprehensive risk assessment and start a hierarchical response mechanism, and the fault point of the fault line is accurately positioned by adopting a voltage drop method. And the monitoring frequency and the decision threshold value are adaptively adjusted according to the fault characteristics and historical data, so that response lag and insufficient precision of a traditional fault positioning method are avoided, full-flow intelligent management from fault detection, accurate positioning to parameter self-optimization is realized, the accuracy and efficiency of fault processing are improved, and safe and stable operation of a power grid is ensured.

The invention relates to the technical field of motor state monitoring, in particular to a motor state monitoring method and system based on data driving, and the method comprises the following steps: synchronously collecting a motor voltage signal amplitude time domain sample and a motor current signal amplitude time domain sample for a power frequency period in a motor operation state; and calculating an instantaneous phase difference between each corresponding sample point to obtain an instantaneous phase difference original data stream of the motor. The method comprises the following steps: synchronously acquiring voltage and current amplitudes during operation of a motor in real time, and calculating an instantaneous phase difference between the two amplitudes to obtain an electromagnetic state original data stream; further executing high-pass filtering and performing spectral analysis to filter interference signals and low-frequency trend influences, and improving the recognition precision and robustness of instantaneous phase difference jitter features; meanwhile, voltage pulses are actively injected into the winding, echo signals are collected, and rapid capturing and positioning of the abnormal state of the winding are achieved through propagation time delay calculation and impedance characteristic construction.

The invention discloses a self-adaptive filtering method and system for an intelligent electric energy meter, and relates to the technical field of power grid signal processing, and the method comprises the steps: obtaining a power grid voltage and current signal set collected by a target intelligent electric energy meter historically, and obtaining a signal noise spectrum data set and a noise level evaluation result through spectrum analysis and noise level evaluation; if the result exceeds a preset noise threshold value, identifying an interference type and building a noise adaptive filtering multi-channel, integrating and deploying the noise adaptive filtering multi-channel into a target intelligent electric meter to complete signal filtering test and effect evaluation, and dynamically optimizing and generating an electric energy meter adaptive filtering multi-channel based on the obtained multi-channel filtering effect index parameter; and finally, signal filtering closed-loop control is realized. The technical problem that a traditional electric energy meter is weak in filtering pertinence and cannot adapt to dynamic noise of a power grid in electric power related scenes with complex dynamic interference is solved, and the technical effects that the electric variable measurement accuracy of the electric energy meter is improved, and the adaptive capacity of the electric energy meter to different interference scenes is enhanced are achieved.

The invention discloses a battery failure reason prediction method and a computer storage medium, and the method comprises the steps: outputting EIS prediction data through a time sequence model according to the data in the charging and discharging process of a battery; according to EIS prediction or actual measurement data, relaxation time characteristic peak time and corresponding intensity are obtained; constructing a candidate circuit topology in the element library according to the characteristic peak time and intensity and EIS prediction or actual measurement data, and calculating and outputting an optimal equivalent circuit model character string and a parameter set; fusing relaxation time characteristic peak time and intensity, an optimal equivalent circuit model character string, a parameter set, a structural characteristic and a current / voltage derivative characteristic, splicing into a low-dimensional vector, and constructing an electrochemical state fingerprint; carrying out embedded representation on the electrochemical state fingerprints, and recognizing typical degradation state clusters through dimension reduction and clustering; and performing failure cause semantic attribution, and outputting a failure cause category and a prediction report. According to the invention, automatic identification and output of potential failure reasons of the battery are realized.

The invention provides a battery piece, a battery string, a preparation method of the battery string and a photovoltaic module. A first grid line layer of the battery piece comprises a plurality of first interconnection main grids which are arranged at intervals, a second main grid layer is arranged on the back face of the battery piece, the second main grid layer is provided with a plurality of second interconnection main grids and a plurality of current collection enhancing main grids, and the first interconnection main grids and the second interconnection main grids are arranged in a one-to-one correspondence mode in the thickness direction of the battery piece. The two sides of each first interconnection main grid are respectively provided with at least one current collection enhancement main grid. According to the battery piece provided by the invention, the current collection capability of the battery piece is improved, the current transmission loss is reduced, the filling factor of a photovoltaic module is improved, meanwhile, the optical loss caused by optical shielding on the front surface of the battery piece is reduced, the short-circuit current is improved, and the short-circuit current and the filling factor are optimized at the same time.

An electrical line selection system comprising a circuit module configured to connect energy sources with multiple line outputs. The circuit module has a number of inputs configured to connect to energy sources, including rechargeable battery systems, and a number of outputs configured to connect with other electrical systems such as other battery systems, loads, charging sources, and various AC or DC power supplies. A switching circuit is contained by the circuit module and a controller manages the switching circuit based on desired connections and strategies for managing power supplies and current sinks.

The invention provides embedded metal fullerene and a preparation method thereof. The preparation method comprises the following steps: mixing a metal source and graphite powder, and filling a hollow graphite rod with the mixture to prepare an anode; the electrode is installed at the anode end of an electric arc furnace, and on-line activation is conducted through anode and cathode short-circuit current under the inert atmosphere; then carrying out arc discharge under specific air pressure and current, and collecting generated carbon ash; performing ultrasonic extraction by using an organic solvent to obtain a fullerene crude extracting solution; and finally, performing multi-stage separation and purification by high performance liquid chromatography, and performing primary and fine separation by sequentially adopting preparative and semi-preparative chromatographic columns to obtain a high-purity product. According to the method, a complete technical path capable of efficiently and controllably preparing the ultra-high-purity embedded metal fullerene is formed through a synthesis process integrating online activation and accurate atmosphere regulation and control and a multi-stage gradient chromatography purification strategy, and a solid foundation is laid for application of atomic-scale accurate materials in the frontier fields of quantum devices and the like.

The invention discloses an electricity stealing behavior detection method and system based on an intelligent electric energy meter, and the method comprises the following steps: constructing a phase locking reference frame at the end of the intelligent electric energy meter, synchronously collecting a voltage phase and a current phase through high-precision time, generating a direction discrimination baseline, setting a zero-power crossing point and a direction overturning threshold value, and carrying out the detection of an electricity stealing behavior. Outputting a direction baseline consistency index as a direction identification reference; according to the invention, through phase locking, high-precision synchronization, neutral line drift analysis, multi-table data alignment and phase disturbance verification, accurate identification and causal confirmation of a current backward flow behavior are realized, a disturbance user is reversely positioned in combination with a disturbance fingerprint, an intervention instruction is output, and an identification-verification-positioning-control closed loop mechanism is constructed. And the anti-electricity-stealing capability and the metering accuracy of the intelligent electric energy meter in a complex power supply environment are obviously improved.

The utility model discloses an electronic protection device and a power utilization device, and belongs to the field of fuses. The electronic protection device comprises a conductive element used for being connected to a circuit to be tested; the first excitation fuse and the second excitation fuse are connected in series on the conductive element; the arc extinguishing fuse is connected with the second excitation fuse in parallel; and the controller is used for detecting the value of a current flowing through the conductive element of a circuit to be detected, and is in communication connection with the first excitation fuse and the second excitation fuse. The first excitation fuse and the second excitation fuse are connected in series, the arc extinguishing fuse and the second excitation fuse are connected in parallel, and the controller outputs a trigger signal according to the detected current, so that the electronic protection device switches the first working mode or the second working mode, and the circuit can be protected when the circuit is overloaded or short-circuited.

The invention relates to the field of data processing, in particular to an electric energy meter real-time electrical parameter processing method and device based on cloud computing, and the method comprises the steps: carrying out the sliding of a target current sequence through a preset sliding step length, obtaining a plurality of windows, constructing an amplitude sequence, and calculating the difference significance degree of target harmonic waves; according to the waveform factor sequence, calculating the in-phase time domain anomaly of the current sequence of the to-be-detected electric energy meter; based on the difference significance degree and the in-phase time domain anomaly degree, calculating the in-phase total anomaly degree of the current sequence of the to-be-detected electric energy meter, updating the window size, traversing to obtain the in-phase total anomaly degree of the current sequence of the to-be-detected electric energy meter under each window size, calculating the comprehensive anomaly degree of the to-be-detected electric energy meter, and obtaining the in-phase anomaly degree of the current sequence of the to-be-detected electric energy meter. And completing electric energy meter electrical parameter processing according to the comprehensive abnormality. According to the technical scheme, the precision and efficiency of the electric energy meter electric parameter processing result can be improved.