1674 results about "Electricity meter" patented technology

The invention provides a multi-source ammeter data intelligent fusion and abnormity identification method. According to the method, original electric parameter data of a plurality of intelligent electric meters are collected under a unified time reference, a cross-equipment measurement data set indexed according to electric meter numbers is constructed, and electric parameter classification and associated information generation are completed in combination with electric wiring information and functional parameters; an electric parameter change curve is extracted through a continuous time window, a value change consistency index is calculated, a response offset feature vector is further introduced for joint judgment, and accurate recognition of an abnormal electric meter and an abnormal time period is achieved; for the intelligent electric meter which is identified as abnormal, constructing an estimated value through data of other electric meters, and calculating residual errors between the estimated value and an original value and between the estimated value and an adjacent estimated value according to a main conductive parameter so as to realize dual residual error verification; judging an anomaly type according to the consistency index and the residual result, and outputting an anomaly recognition result; according to the method, the anomaly detection precision in a multi-table collaboration scene is improved.

The invention relates to the technical field of electricity meter metering, and discloses an electricity meter adaptive error compensation method and system, and the method comprises the steps: calibrating an electricity meter, collecting baseline data under different environment conditions, and recording a measurement error; environment data and ammeter data are collected in real time through an ammeter, and key features are extracted; constructing an error model, and predicting the error of the current ammeter data; and performing real-time correction and parameter adjustment according to the prediction error, and outputting the corrected measurement data. By introducing a real-time error prediction and dynamic compensation mechanism based on environmental data and combining a particle swarm optimization algorithm to optimize regularization parameters in a ridge regression model, the measurement precision of the electric meter under a complex environmental condition is effectively improved. The method can adaptively adjust the measurement data of the electric meter, reduces errors caused by environmental factors, improves the accuracy and stability of electric power measurement, and provides more reliable data support for an electric power management and monitoring system.

The invention discloses an intelligent diagnosis system of a power distribution network fault self-judgment switch device, and relates to the technical field of power system automation and intelligent power grids, and the intelligent diagnosis system comprises an intelligent diagnosis system interconnection hub which is in communication connection with a power parameter monitoring module, an intelligent fault detection module and a visual decision support module; the electric power parameter monitoring module monitors the state of a power distribution network in real time through a mutual inductor, voltage, current, power factors and harmonic data are collected through an intelligent electric meter, the intelligent fault detection module achieves fault recognition, trend prediction and anomaly detection through an LSTM neural network, and the decision support module provides a graphical interface and automatically generates a fault response strategy. According to the method, autonomous judgment and quick response of the power distribution network fault are achieved, the accuracy and efficiency of fault detection are remarkably improved, the false alarm rate and the missing report rate are reduced, meanwhile, the decision support module of the graphical interface simplifies the fault processing flow, and the stability and safety of power grid operation are improved.

An air conditioner load monitoring and anomaly detection method and system. The method comprises: acquiring user power consumption data and meteorological data, the user power consumption data and the meteorological data comprising the total power of an electricity meter, the power of an air conditioner, and the outdoor temperature, preprocessing the data, and computing electrical characteristics of the user power consumption data; on the basis of the electrical characteristics, learning by using a two-tower neural network so as to obtain operating rules of the air conditioner, and extracting an air conditioner operation curve; on the basis of the air conditioner operation curve, computing electrical characteristics and energy consumption characteristics of the air conditioner, and performing cluster analysis by using a K-means clustering algorithm; and, on the basis of clustering results, comparing the clustering results with clustering results of collected electrical data of the air conditioner under normal and abnormal operating conditions to determine whether the air conditioner is in an abnormal state, so as to implement detection of anomalies in the operation of the air conditioner, thereby improving the precision of load decomposition of the air conditioner, reducing application costs, providing a decision-making reference for equipment maintenance personnel, and prolonging the service life of the equipment.

The invention discloses an electric energy meter error real-time monitoring and intelligent calibration system and method, and relates to the technical field of electric energy meter calibration, and the system comprises a target power data calculation module which is used for collecting voltage and current signals in real time, and carrying out the calculation to obtain target power data; the reference power data calculation module is used for performing real-time calculation to obtain reference power data; the error vector acquisition module is used for acquiring an error vector; the error prediction result generation module is used for carrying out modeling analysis on the error vector and generating an error prediction result; and the target electric energy value output module is used for outputting the target electric energy value. The technical problem that the metering accuracy is insufficient due to the fact that the electric energy meter lacks an effective error analysis and prediction means and a dynamic calibration mechanism in a bidirectional power flow scene in the prior art is solved, and the purposes of real-time monitoring, error analysis and prediction and dynamic calibration of the forward and reverse power data of the electric energy meter are achieved. And the metering accuracy of the electric energy meter in a bidirectional power flow scene is improved.

The invention discloses an intelligent electric meter fault early warning method and system based on multi-parameter synchronous measurement. The method comprises the step of synchronously collecting operation videos, reading data and environmental parameters of the electricity meter. Firstly, illumination compensation optimization is performed on a video, image features are extracted through a convolutional layer and a full connection layer, a comprehensive visual feature vector is constructed in combination with a cross attention mechanism and environmental parameters, and the overall shape of an electric meter is extracted to detail features in a layered manner; the change trend and fluctuation characteristics are extracted from the reading data by using time sequence analysis, and the influence of environmental factors is considered. Then, fusing multi-source features to generate a feature map reflecting the state of the electric meter; normal and fault state features are compared through similarity calculation, and a fault risk is identified and early warning is carried out; and evaluating a result by using ID matching and a machine learning algorithm, and optimizing fault early warning in combination with historical data. By implementing the method, multi-source information can be fused, the speed and accuracy of fault diagnosis can be remarkably improved, and continuous and stable operation of a power system is ensured.

The invention relates to the technical field of intelligent power grids, and discloses an abnormal power consumption behavior real-time monitoring and positioning method and system, and the method comprises the steps: carrying out the transformation of an existing collection device at an edge end, achieving the serial communication with the edge collection device, and carrying out the dynamic adjustment according to the collection condition and business demands of a transformer area, and forming a new collection strategy; clustering the electricity meters by using a Pearson's correlation coefficient and a DBSCAN clustering algorithm, dividing electricity meter clusters, and calculating the load condition of each cluster; according to the load condition and the acquisition weight of the electric meter cluster, the acquisition sequence and the acquisition frequency are adjusted, and the acquisition strategy is iterated and optimized periodically; and monitoring ammeter data in real time, identifying an abnormal electricity consumption behavior, and outputting an abnormal prompt. According to the invention, the algorithm is built in the edge computing platform through the big data algorithm analysis of the historical power consumption behaviors of the user, so that the dependence on manual judgment is effectively reduced, and the automation degree in the abnormal power consumption behavior monitoring, analyzing and processing process is 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 provides a field data verification device based on a money-free clamp buckle type single-phase electric energy meter, and the device comprises a host which is used for starting a measurement process through the contact of a probe with a signal contact of the electric energy meter, receiving current data transmitted by a wireless clamp-shaped current transformer, and carrying out the filtering, calibration and error analysis of the measurement data; and the wireless split core type current transformer is used for being clamped on a current loop of the measured electric energy meter, starting to measure current data and sending the current data to the host in a wireless mode. According to the invention, a wireless communication technology, a field data processing algorithm and a verification function are integrated, and field real-time data acquisition, processing, analysis and verification can be realized, so that the efficiency and accuracy of verification work are improved.

The invention relates to a relay and an electric meter. The relay comprises an electromagnetic pushing system, the electromagnetic pushing system comprises a coil and an armature assembly, the armature assembly is located on one side of the coil in the first direction, and the axis direction of the coil is in the third direction; the contact system is located on the third direction side of the electromagnetic pushing system and comprises a static contact unit and a movable contact unit which are arranged in the third direction, the movable contact unit is connected with the armature assembly, one end of the movable contact unit is fixed to the relative position of the static contact unit, and the other end of the movable contact unit is suitable for being driven by the armature assembly to be close to or away from the static contact unit; the terminal group is positioned on one side, deviating from the electromagnetic pushing system, of the contact system and is connected with the static contact unit and the movable contact unit; wherein the first direction is perpendicular to the third direction. According to the invention, the space layout of the relay is more reasonable, the structure is more compact, the occupied space is effectively reduced, the relay can be better matched with other parts, and the applicability is good.

The invention discloses an electricity consumption information acquisition terminal concurrent meter reading method, device and equipment and a storage medium, and relates to the field of electricity consumption information acquisition. The method comprises the following steps: acquiring a communication routing path and a communication routing hop count from an acquisition terminal to each to-be-acquired electric energy meter in an electric energy meter network topology structure; according to the communication routing path and the hop count of each to-be-collected electric energy meter, the to-be-collected electric energy meters are classified to obtain N concurrent meter reading task groups, and N is larger than or equal to 2; communication routing paths among the to-be-collected electric energy meters in each concurrent meter reading task group are not intersected and communication routing hops are different; and performing concurrent meter reading on the to-be-acquired electric energy meter according to the concurrent meter reading task group to acquire the electricity utilization information. According to the invention, the problems of overweight communication network load and frequent conflicts caused by mutual interference between a downlink reading instruction and an uplink response instruction due to communication channel overlapping and routing conflicts when an existing power utilization information acquisition terminal executes a multi-meter simultaneous reading task are solved.

The invention relates to a relay and an electric meter. The relay comprises a contact system, wherein the contact system comprises a movable contact unit and a static contact unit; a pushing system; the connecting structure is connected with the pushing system and the moving contact unit, and the connecting position of the connecting structure and the pushing system is located on the side, away from the static contact unit, of the moving contact unit. According to the application, the pushing system is connected with the moving contact unit through the connecting structure, and the connecting position of the connecting structure and the pushing system is located on the side, away from the static contact unit, of the moving contact unit, so that when the moving contact and the static contact are closed to generate an arc, the moving contact unit can block the arc to prevent ablation of the pushing system; and the overall reliability and service life of the relay are effectively improved.

The invention provides an electric energy meter PCB function test method and device, a medium and equipment, and the method comprises the steps: obtaining a multi-channel signal source, automatically adjusting the characteristics of an input signal based on a feedback signal of an electric energy meter through a self-adaptive algorithm, and determining the consistency of the working characteristics of the input signal and the working characteristics of the electric energy meter; a virtual power grid environment simulation model is constructed, through integrated power simulation software and dynamic interference simulation, simulation signal source automatic adjustment signal characteristics are input into the virtual power grid environment simulation model based on the integrated power simulation software to synthesize a composite signal, and load fluctuation of an electric energy meter in actual operation is simulated based on the composite signal. Determining an electric energy meter test data set; according to the invention, the fault mode of the electric energy meter can be automatically identified, the test data can be analyzed in real time, and fault diagnosis and optimization suggestions can be automatically given. The intelligent diagnosis mode is far better than a traditional manual detection method, and the speed and accuracy of fault diagnosis can be remarkably improved.

The invention discloses an electricity meter adaptive error compensation method, system and device based on multi-physical coupling and hidden variable modeling and a storage medium, and relates to the technical field of electric energy metering and detection, and the method comprises the steps: constructing a multi-physical coupling basis vector containing a single variable and a cross variable based on a sensing output signal; hidden variable joint modeling is carried out based on the multi-physical coupling basis vector and parasitic capacitance change, magnetic conductivity drift and shunt resistance offset, and a compensation mapping relation of electromagnetic, thermal and stress coupling is formed; generating a compensation coefficient by adopting the compensation mapping relation, and applying the compensation coefficient in an ammeter metering link to complete an error compensation process; according to the method, voltage, current and phase compensation coefficients are generated through multi-physical coupling basis vector and hidden variable modeling, dynamic description and self-adaptive correction of error sources are achieved, dynamic accurate correction of voltage, current and phase is achieved, and it is ensured that the ammeter keeps high-precision metering for a long time under the complex environment and the device drift condition.

The invention relates to a relay and an electric meter. The relay comprises a pushing system; the contact system comprises a static contact unit and a movable contact unit, the static contact unit comprises a static magnetizer, the movable contact unit comprises a movable spring and a movable magnetizer, the movable magnetizer and the movable spring are separately formed and fixedly connected, the movable magnetizer and the static magnetizer are oppositely arranged, and the movable magnetizer is connected with the pushing system; wherein the movable magnetizer is suitable for getting close to or getting away from the static magnetizer under the driving of the pushing system, the first end of the movable spring is suitable for getting close to or getting away from the static contact unit under the driving of the movable magnetizer, and the second end of the movable spring is fixed relative to the static contact unit. According to the invention, the movable magnetizer and the static magnetizer are adopted to realize an anti-short-circuit function, different from an anti-short-circuit structure formed by bending the reed body in the prior art, the production process is simpler and more convenient, and the material cost is lower.

The invention relates to an electricity meter fault prediction method, system and device based on deep learning. The electric meter fault prediction method based on deep learning comprises the following steps: periodically collecting various data of an electric meter; preprocessing the collected data, and then performing clustering processing to obtain a plurality of clusters; the data in the multiple clusters are input into the deep learning model, each different cluster corresponds to different gate structure weights of the deep learning model, and finally a result value with time sequence features corresponding to the data is obtained. According to the invention, the data collected by the electricity meter is input into the deep learning network for fault prediction, features and modes can be automatically learned from the data, and prediction and classification are carried out. In the field of electric meter fault prediction, deep learning can learn the power utilization habit of a user and the operation mode of an electric meter by analyzing historical data of the electric meter so as to predict possible faults of the electric meter.

The invention discloses a single-phase charge-control intelligent electric energy meter and an intelligent metering system thereof, relates to the technical field of electric variable measurement, and aims to solve the technical problem of inaccurate metering of the existing intelligent electric energy meter, and the single-phase charge-control intelligent electric energy meter comprises a working electric quantity calculation module which is connected to a power grid and is used for counting the electric quantity when the electric energy meter works and storing the electric quantity in a memory; the non-working electric quantity calculation module is used for calculating the electric quantity when the electric meter does not work; the working electric quantity calculation module further comprises a first processing unit which is used for calculating the working electric quantity consumed when the electric meter works according to the working duration of the electric meter; the first calculation unit is used for receiving the working electric quantity from the first processing unit, calculating corrected electric quantity according to the working electric quantity and historical electric quantity data stored in the memory, and transmitting the corrected electric quantity to the correction unit; and the correction unit is used for receiving the correction electric quantity transmitted by the first calculation unit and correcting the working electric quantity. The method has the advantage of improving the electricity metering accuracy of the electricity meter.

The invention relates to the technical field of electric meter online monitoring, in particular to an electric energy data intelligent acquisition terminal based on federal learning. The data acquisition and preprocessing module is used for acquiring electric energy data in a power grid in real time and carrying out de-noising and normalization preprocessing on the electric energy data; the model training module based on federated learning is used for training a neural network model for the preprocessed electric energy data by using local data so as to obtain a local model; the homomorphic encryption algorithm application module is used for encrypting and updating data and model parameters in a local data training process by adopting a homomorphic encryption algorithm; and the global model updating module is used for sending the neural network model subjected to multiple times of local data training and encryption updating to a central server, and optimizing and updating the neural network model through a weighted federated average aggregation algorithm. According to the invention, distributed data processing and machine learning technologies are combined to realize intelligent data analysis of electric power data, so that the intelligent level of electric power monitoring and fault early warning is improved.

The invention relates to the technical field of intelligent electric energy meters, in particular to an intelligent electric energy meter system based on an RF net-shaped ad hoc network and a communication method of the intelligent electric energy meter system. The system adopts an intelligent electric energy meter with an integrated gateway function as a gateway node in an RF network and uploads power utilization data and state information to a head end system; independent gateway equipment does not need to be additionally deployed, so that the hardware procurement cost, the installation and debugging cost and the long-term operation and maintenance cost are remarkably reduced; meanwhile, according to the intelligent electric energy meter system communication method based on the RF net-shaped ad hoc network, the optimal main path and the optimal standby path are selected for data transmission by dynamically calculating the comprehensive routing metric value, the reliability of the network is greatly improved through the multi-path redundancy design, and the system has the higher fault self-healing capacity; in addition, the intelligent electric energy meter integrated with the gateway function can monitor and optimize the network topology structure, the data flow distribution and the node resource utilization rate in real time through a built-in network management system, and the data transmission efficiency and the network stability are further improved.

The invention relates to the technical field of electricity meters, and particularly discloses a relay and an electricity meter thereof, comprising a mounting plate: a clamping frame is fixedly mounted on the front surface of the mounting plate, sliding grooves are formed in the upper and lower ends of the clamping frame, sliding plates are slidably connected to the inner sides of the sliding grooves, and heat dissipation fins of a heat conduction aluminum plate are attached to electronic components in the electricity meter. The n-pentane heat-conducting medium in the liquid storage box is heated and vaporized, the heat is absorbed, the heat dissipation capability is improved, the heat pushes the air cylinder to open the heat dissipation window, the air velocity in the electric meter is improved, the heat dissipation is enhanced, the temperature is continuously increased, and the heat-conducting medium is further vaporized, so that the inner current-conducting plate and the outer current-conducting plate are attached; and after the temperature is reduced, the heat-conducting medium is condensed, the air cylinder shrinks to block the heat dissipation window, the heat dissipation fan does not need to be automatically triggered by a temperature sensor, the consumption is reduced, the stability is improved, the cost is reduced, and the protection and moisture-proof performance is improved by the blocking window when the heat dissipation device is not used.

The invention relates to a single-phase load identification intelligent ammeter, which relates to the technical field of ammeters, and comprises an ammeter body, a terminal cover and a fixing piece, the ammeter body is provided with a wiring area, a display area and a drainage channel penetrating through two sides of the ammeter body, and the terminal cover is hinged on the ammeter body and covers the wiring area and the drainage channel. The fixing member is used for detachably fixing the terminal cover on the ammeter body. The plugging part is arranged on the terminal cover, the plugging groove is arranged in the wiring area, the fixing piece is taken down from the plugging part to form an air guide flow channel between the plugging part and the wiring area, and the air guide flow channel is communicated with the drainage channel. Air is supplied to the plugging part through external air supply equipment, dust removal air can be blown into the wiring area along the air guide flow channel and is discharged through the drainage channel, dust in the wiring area can be cleaned under the condition that the terminal cover is not opened, the dust removal efficiency is improved, and the maintenance risk is reduced.

The invention provides an intelligent electric energy meter service life prediction method and device and a readable storage medium, and belongs to the technical field of device service life prediction.The method comprises the steps that multi-dimensional input is constructed by fusing key environment data and an operation time sequence, and the microcosmic, periodic and long-term characteristics of the input are extracted through multi-scale convolution support; the feature combination is dynamically optimized through an adaptive fusion module; constructing a time sequence prediction model, embedding a convolution attention mechanism in an encoder, and compressing redundant information of key features by combining sparse self-attention distillation through key features of feature combination of channel-space double attention dynamic enhancement optimization; the decoder adopts a mask probability sparse attention and iterative prediction strategy to generate an error prediction sequence based on the global features of the encoder to avoid future information interference; and calculating the residual life according to the intersection point of the error prediction sequence and the failure threshold. According to the method, the long sequence prediction precision, the key feature utilization rate and the calculation efficiency are improved, and reliable support is provided for preventive maintenance of the intelligent electric meter.

The invention discloses a distributed single-mode small model data synchronization method applied to an intelligent electric energy meter, and the method comprises the steps: S1, building a high-fidelity training environment based on a programmable power supply, dynamically optimizing simulation parameters in combination with end-side feedback, and training an initial power utilization anomaly detection model; s2, modeling the trained model according to an equipment portrait, and generating a lightweight model through bidirectional adaptive compression; s3, deploying a lightweight model at an electric energy meter end and monitoring performance attenuation characteristics; s4, the environment offset is reversely fed back to the cloud through a block gradient return mechanism, and the model parameters are iteratively corrected at the cloud; and S5, triggering cloud secondary training by using feedback data, and circularly updating the model until the precision and power consumption dual-index convergence is achieved. According to the method, a closed-loop optimization link is formed through the end cloud bidirectional data flow, the static defect of traditional one-way deployment is broken through, and continuous self-adaption of the model to the dynamic environment is achieved.

The invention discloses an electricity meter data acquisition method and system based on a DLT698.45-2017 protocol. A dual-mode acquisition mechanism is constructed by expanding an active query communication protocol and a passive monitoring communication protocol in a gateway machine dictionary table, presetting an electricity meter model and data point parameters and developing a message encapsulation and analysis interface. According to the method, data points are grouped and framed according to serial ports and electricity meters, a message sending period is managed through a fixed / temporary sending queue, and PIID automatic self-increasing and FCS dynamic calculation are achieved through a serial port processing thread. The system can generate query messages according to a reading period in an active mode, and can monitor serial port data and filter cross-platform messages in a passive mode. The method can effectively improve the ammeter data acquisition efficiency and accuracy, reduces the system resource consumption, guarantees the data integrity and safety, is suitable for the ammeter data real-time acquisition of a smart power grid and a new energy scene, and is of great significance for the construction and development of the smart power grid.

The invention belongs to the field of waste electric energy meter disassembly, and provides a waste electric energy meter disassembly system and method. The waste electric energy meter disassembling system comprises an automatic feeding device, an automatic sorting and grabbing device, an automatic disassembling device and a smashing and screening device which are sequentially arranged along a main conveying line. The automatic feeding device is used for automatically conveying waste electricity meters to the inlet end of the automatic sorting and grabbing device. The automatic sorting and grabbing device is used for automatically sorting single waste electricity meters and conveying the single waste electricity meters to a station where the automatic disassembling device is located; the automatic disassembling device is used for automatically disassembling the waste electricity meters on the stations into set parts; and the crushing and screening device is used for crushing each disassembled part, separating and screening according to the properties of recyclable materials, and classifying and storing the recyclable materials into corresponding material receiving boxes.

The invention belongs to the field of non-intrusive load monitoring, and discloses a household electricity consumption analysis method based on non-intrusive load monitoring and related equipment, firstly, non-intrusive monitoring is realized by using household total electricity meter data instead of a single equipment electricity meter, and the complexity and cost of household electricity consumption data collection are reduced; secondly, an unsupervised learning method is adopted to cluster the power load state data, data does not need to be marked in advance, and different load events are automatically identified and classified, so that the problems of load type diversity and high identification difficulty are effectively solved, and the accuracy and efficiency of load event detection are improved; in combination with a depth-first search algorithm and load event constraint conditions, fine search is carried out on load event labels, an undetermined event sequence set is generated, the logicality and continuity of event sequences are enhanced, electricity utilization behavior analysis of the electric equipment is deeper and finer, home users can better understand and optimize own electricity utilization modes, and the user experience is improved. And energy conservation, emission reduction and efficient utilization of energy are promoted.

According to the electric meter intelligent dynamic complementary reading method and device based on big data analysis, the method comprises the steps that historical data are analyzed, the reading data items and the reading priority of an electric meter are intelligently adjusted, task data sets needing complementary reading are combined into a composite task according to requirements, automatic execution is executed in the non-busy time period, and the intelligent dynamic complementary reading efficiency of the electric meter is improved. And the data acquisition efficiency and accuracy are improved. A master station system is used for issuing a configuration scheme and a task to terminal equipment, data items of different electricity meters are sorted, and deep mining and analysis are carried out based on collected data within a past set time (flexible adjustment can be carried out according to specific field requirements); and a set of personalized complementary reading configuration strategy suitable for various ammeters is deeply combed and constructed, so that intelligent dynamic complementary reading is realized. The measure not only effectively guarantees the basic data support of big data processing, but also assists a decision application level to obtain more accurate and effective results.

The invention relates to the technical field of electricity meter scrap treatment, and discloses an electricity meter scrap crushing and sorting treatment device which comprises a machine body, a motor is fixedly connected to one side of the machine body, two crushing rollers are rotatably connected to the top in the machine body, and a first circular gear is fixedly connected to the side, away from the motor, of each crushing roller; the output end of the motor is connected with one of the crushing rollers, the two first circular gears are meshed, a rolling assembly, a separating assembly and a screening assembly are sequentially arranged in the machine body from top to bottom, a transmission assembly and a reciprocating assembly are arranged on the outer wall of the machine body, the rolling assembly comprises a rotating shaft, a rolling box and a fixing plate, and the rotating shaft is connected with the rolling box. And the rotating shaft is rotationally connected to the inner wall of the machine body. And through cooperation of the rotating shaft, the first bevel gear and the second bevel gear, the rolling rollers generate periodic left-right rolling action in the rolling box, the crushed materials are subjected to secondary rolling, and the particle size of the materials is refined.

A meter socket adapter (MSA) for connecting a battery energy storage system (BESS) to a household microgrid through a meter combo load center. The MSA includes: a housing matching an electricity meter and a meter socket in the meter combo load center; a plurality of power conductors that connect among the electricity meter, the meter socket, and BESS; a meter interconnection device (MID) switch for connecting a utility grid or one or more distribution energy resource (DER) devices to supply power to household loads in the household microgrid; a MID driving circuit for driving the MID switch to close or open; and a thermal management circuit couple with a plurality of temperature sensors disposed at each high current connection point to prevent overheat.

The invention relates to the technical field of electric meter data transmission, in particular to an intelligent electric meter multi-mode communication low-power-consumption control and data compression combined processing method. If the ammeter temperature is greater than the temperature threshold, calculating the heat dissipation coefficient of the ammeter according to the heat dissipation parameter; determining the maximum operation power of the ammeter according to the heat dissipation coefficient; judging whether the state of the electricity meter is abnormal or not according to the operation parameters, if the electricity meter works normally, selecting an LPWAN technology for data transmission and selecting a data compression mode according to a data change period, responding to the abnormal work of the electricity meter, adjusting the emission frequency according to the accumulation amount of key data, and after the adjustment of the emission frequency is completed, performing data compression. And determining a data compression and communication mode according to the maximum operation power. By calculating the heat dissipation coefficient and determining the maximum operation power according to the heat dissipation coefficient, the electric meter can operate in a safe power range, so that the operation stability of the electric meter is improved.