4319results about "Measurement using digital techniques" patented technology

The invention discloses a high-precision voltage measurement method and system based on multi-parameter adaptive compensation, and relates to the technical field of intelligent voltage measurement. The high-precision voltage measurement method and system based on multi-parameter adaptive compensation comprises the steps that S1, voltage signal data and disturbance source characteristic data are collected, preprocessing is completed, and an analysis basis is constructed; s2, analyzing voltage excursion in combination with disturbance current characteristics, and dynamically adjusting a compensation path; s3, evaluating a compensation correction effect, and driving a compensation output strategy in real time; and S4, comprehensively analyzing the offset characteristics and the correction result, judging an abnormal section and triggering adaptive adjustment. The problems that disturbance components cannot be comprehensively extracted from multiple parameters such as PWM modulation frequency, wire harness impedance and working condition load change and a compensation function cannot be reversely constructed in an existing method, and a measured value does not have stability are solved.

The invention discloses a DC-DC power supply dynamic response optimization system based on digital PID, which relates to the technical field of DC-DC power supply dynamic response optimization, and comprises a voltage and current sampling module, a reference signal generation module, an output signal generation module, a digital signal generation module, a control module and an output signal generation module, the digital PID controller calculates control output according to errors, the PWM signal generation module generates corresponding PWM signals according to the control output, the power switch driving module amplifies the signals to drive a switch tube, the load monitoring module monitors load changes in real time, output of the load monitoring module can be fed back to other modules, and power supply dynamic response optimization is achieved. According to the invention, the dynamic response performance of the DC-DC power supply is remarkably improved, the output fluctuation is reduced, the recovery time is shortened, the power supply efficiency is improved, the stability is guaranteed by adopting multiple anti-interference design, peripheral elements are reduced, miniaturization is realized, the cost is reduced, fault diagnosis is realized, and the service life is prolonged.

The invention discloses an electrical fire monitoring method based on inherent residual current automatic compensation, and relates to the technical field of electrical safety monitoring, and the method comprises the following steps: S100, collecting a residual current signal, executing multi-component time-frequency deconstruction processing, extracting an energy distribution characteristic through wavelet packet transformation, and extracting a mutability index in combination with short-time spectrum entropy analysis, and constructing a preliminary distribution map of higher harmonic interference, and determining boundary features of interference signals in a time domain and a frequency domain. According to the method, high-frequency interference signals are accurately positioned through time-frequency deconstruction, wavelet packet analysis and spectral entropy indexes, non-fault harmonic components are effectively eliminated in combination with amplitude-frequency coupling recognition and a recursive rejection strategy, closed-loop control is constructed by introducing an adaptive compensation and stability backtracking mechanism, accurate recognition and dynamic correction of real electric leakage risks are achieved, and the method is suitable for large-scale popularization and application. The identification precision and the safety reliability of the monitoring system in a complex industrial environment are obviously improved, and the method has good engineering adaptability.

The invention provides a high-voltage cable partial discharge identification and positioning method, and relates to the technical field of high-voltage cable diagnosis, and the method comprises the steps: collecting partial discharge pulse signals through high-frequency current transformers disposed at two ends of a high-voltage cable; carrying out noise reduction processing on the acquired partial discharge pulse signal by using an adaptive multi-scale wavelet decomposition and reconstruction method to obtain a partial discharge characteristic signal after noise reduction; inputting the partial discharge characteristic signal into a pre-trained lightweight residual attention network for identification and classification, and outputting a discharge type discrimination result, discharge intensity and characteristic parameters; and based on the discharge type discrimination result, the discharge intensity and the characteristic parameters, a self-correction double-end positioning algorithm is adopted to position the discharge source, and the position of the discharge source is calculated. According to the invention, the technical problems of unsatisfactory signal noise reduction effect, low discharge type identification accuracy, unstable positioning precision and the like in the prior art can be solved, so that high-precision identification and positioning of partial discharge of the high-voltage cable are realized.

The invention discloses a sampling implementation method and system suitable for motor protection quick response, belongs to the technical field of motor protection, and can increase the sampling frequency and improve the quick response of motor fault protection. Comprising the steps that motor phase current and bus voltage are collected, after anti-aliasing filtering is conducted, parallel sampling is conducted through a main ADC module and a redundant ADC module which are independently configured, and the following operations are synchronously executed based on a double-buffer-area framework: in a first buffer area, a compensation coefficient updating period is dynamically adjusted, and convergence is restrained; in the second buffer area, generating a voltage gradient prediction sequence, and compensating data abrupt change; when the harmonic frequency spectrum amplitude or the voltage gradient prediction sequence exceeds the limit, an oversampling mode is triggered, a redundant ADC module is allocated to load a multi-order digital filter, and an independent hardware acceleration unit is started to process harmonic compensation and gradient prediction in parallel; and generating a dynamic safety envelope, and if the gradient extreme value in the preset continuous window breaks through the safety envelope, generating an overvoltage fault signal.

The invention relates to the technical field of power supply detection, and discloses a fire-fighting equipment power supply detection method and system.The detection method comprises the following steps that voltage fluctuation, current phase and ripple coefficients are collected through a multi-channel sensor group, a feature sequence is generated through sliding window noise reduction, the Euclidean distance is calculated through Z-score standardization, and a calibration instruction is generated when a threshold value is exceeded; kalman filtering adjusts frequency output detection parameters, fast Fourier transform is executed to extract harmonic amplitude to generate a suppression vector, and a least square reconstruction model outputs a state identifier; according to the method, voltage, current and ripples are collected through multiple channels, anti-interference performance and data integrity are enhanced through sliding window noise reduction, a threshold value is adjusted through Z-score and Euclidean distance self-matching, sampling frequency and detection parameters are optimized through Kalman filtering, harmonic characteristics are extracted through FFT, and the state is evaluated through a least square reconstruction model. And a multi-dimensional classification system is constructed by fusing the distortion rate and the phase deviation, so that the detection precision, the sensitivity and the response real-time performance are improved.

The invention discloses a DC voltage divider parameter anomaly detection method based on harmonic characteristics, and the method comprises the steps: deploying an isolation type voltage sensor at a bus of a DC power transmission system, carrying out the voltage sampling through combining with an ADC, carrying out the data buffering and preprocessing, extracting a fundamental wave component and a target harmonic component through the fast Fourier transform, and calculating the harmonic distortion rate. And constructing a low-voltage arm capacitance and harmonic distortion rate model based on a voltage divider secondary circuit equivalent circuit and an energy distribution principle, and calibrating the low-voltage arm capacitance and harmonic distortion rate model. And designing a multi-objective optimization scheduling algorithm based on energy storage capacity and capacitance characteristics, and realizing dynamic power distribution and harmonic suppression of the system. And after abnormal triggering, the system automatically loads a capacitance compensation coefficient, adaptively adjusts algorithm parameters in combination with a measurement loop PI control link, reduces a harmonic amplification effect, and ensures that a measurement error is within an acceptable range. Harmonic monitoring precision and capacitance compensation optimization capability of the direct-current power transmission system are effectively improved, and stable operation of the system is guaranteed.

The invention relates to the technical field of circuit control, in particular to a control method and system of a bidirectional charging and discharging circuit. The method comprises the following steps: collecting current monitoring data and voltage monitoring data of a bidirectional charging and discharging circuit in real time; performing arc characteristic analysis on the current monitoring data and the voltage monitoring data to obtain arc characteristic data; analyzing a high-frequency harmonic component and a current ripple fluctuation amplitude of the bidirectional charging and discharging circuit based on the arc characteristic data; performing direct-current arc detection on the bidirectional charging and discharging circuit according to the high-frequency harmonic component and the current ripple fluctuation amplitude to generate a direct-current arc fault judgment result; and calculating the instantaneous current change rate of the current monitoring data, and carrying out short-circuit detection on the bidirectional charging and discharging circuit through the instantaneous current change rate. By monitoring current and voltage data in real time, arc and short circuit characteristics are accurately analyzed, relay control is optimized, an accurate control instruction is generated, and the safety and reliability of the two-way charging and discharging circuit are improved.

The invention relates to the technical field of power equipment state monitoring, in particular to a transformer iron core alternating current and direct current mixed current on-line monitoring method and system based on a magnetoelectric coupling sensor, and the method comprises the steps: monitoring the change of magnetic flux generated by the vibration of an iron core in a transformer in real time through a magnetoelectric coupling sensor array; the magnetic flux change is converted into an original electric signal, the original electric signal is processed, an alternating current signal component and a direct current signal component in the mixed current are extracted, and historical operation data and real-time environment parameters of the alternating current signal component and the direct current signal component are input into a deep recurrent neural network to be trained; and the deep recurrent neural network outputs the enhanced stray current and the direct current signal after the environmental influence is eliminated after iterative training. According to the invention, high-precision prediction of the temperature of the iron core is realized by using a method of combining a deep recurrent neural network and adaptive decomposition; and the neural network is trained by using the dynamic data, so that the dynamic processing capability of the network is enhanced and the operation reliability of the transformer can be effectively improved.

The invention discloses a power grid multi-range intelligent sensing method and system based on MEMS integration, and relates to the technical field of intelligent sensing, and the method comprises the steps: connecting an MEMS sensing unit to three parallel measurement channels, and connecting the MEMS sensing unit to a controllable signal routing module in parallel; after gating, the signals are sent to a successive approximation analog-to-digital converter for digitalization through nonlinear gain amplification and anti-aliasing filtering; determining a measuring range based on a sampling sequence and a sliding window ratio, and automatically switching channels through a threshold value and a hysteresis mechanism; performing baseline correction on the switching data and performing weighted fusion according to sensitivity and bandwidth; and after the laboratory performs segmented calibration and consistency verification on the three channels, calibration parameters are written and stored, and are transmitted to an upper system through an isolation power supply according to a preset protocol. Automatic range switching is achieved through a sliding window and a hysteresis mechanism, baseline drift correction and weighting fusion according to the proportion of sensitivity and bandwidth are adopted after channel switching, and measurement continuity and precision consistency are ensured.

The invention discloses a self-adaptive adjustment method and system for electric energy meter measurement, and relates to the technical field of electric power metering, and the method comprises the steps: building a first measurement mode and a second measurement mode for a target electric energy meter; carrying out load fluctuation monitoring on the target electric energy meter through a load monitoring module, and generating a load fluctuation index; if the load fluctuation index is greater than the preset fluctuation index, activating a first measurement correction module to perform measurement precision adjustment on the target electric energy meter according to a first measurement mode; and if the load fluctuation index is smaller than or equal to the preset fluctuation index, activating a second measurement correction module to perform measurement precision adjustment on the target electric energy meter according to a second measurement mode. The technical problem that the measurement mode cannot be adaptively adjusted according to different loads during measurement of the electric energy meter in the prior art is solved, adaptive adjustment of the measurement of the electric energy meter is realized, and the technical effect of balancing the power consumption and precision of the measurement of the electric energy meter is achieved.

The invention belongs to the field of power equipment monitoring, and discloses an electrical signal acquisition system based on intelligent dynamic sampling, which comprises a signal acquisition module, a signal conditioning module, an abrupt change detection module, an impedance calculation module and an upper computer, and is characterized in that the signal acquisition module comprises a first ADC module, a second ADC module, a first MCU module and a second MCU module. Short-circuit impedance real-time calculation and waveform abrupt change detection are adopted for cooperative judgment, and when equipment operates stably, the sampling rate of the system is kept low; when impedance changes or waveform changes suddenly, the sampling rate is improved automatically, important signal changes are recorded accurately, and waveform abrupt change detection is carried out by adopting an edge detection algorithm improved based on an FIR (Finite Impulse Response) filter. The system ensures the time sequence consistency of data under different sampling frequencies through multi-channel data synchronization and timestamp management, and meanwhile, smooth transition is performed by applying an interpolation algorithm during sampling switching, so that the continuity of a data sequence is ensured. The data redundancy is reduced; and the integrity of key information is ensured.

A chip includes a power grid, power switches coupled between the power grid and a circuit, and current sensors configured to generate sense currents based on load currents passing through the power switches. The chip also includes a readout circuit having an input and an output, and signal routing coupling the current sensors to the input of the readout circuit.

The invention relates to the technical field of voltage acquisition, in particular to a battery string voltage acquisition system with a calibration system and a voltage acquisition method. Which comprises a multi-path voltage input end, a voltage signal adjusting end, a voltage follower, an analog-to-digital converter, a main control center and a communication circuit, and is characterized in that the voltage signal adjusting end comprises a dynamic voltage division network, consists of a digital potentiometer and a high-voltage operational amplifier, and dynamically adjusts the voltage division ratio to suppress common-mode voltage; the main control center is integrated with a multi-channel synchronous sampling calibration module and generates a global synchronous signal through the main MCU to control the ADC to perform synchronous acquisition; a temperature compensation module is arranged between the voltage follower and the ADC, and a digital temperature sensor is adopted to correct the gain drift of the operational amplifier in real time; the voltage division ratio of the dynamic voltage division network is dynamically adjusted according to the real-time common-mode voltage and a preset safety threshold value. According to the scheme, dynamic partial pressure adjustment, multi-channel self-calibration, nonlinear temperature compensation and a rapid protection mechanism can be integrated.

The invention provides a coal mine underground 3DR electric leakage detection protection method, which comprises the following steps of: constructing an auxiliary star point connected with a system by using three-phase half-waves of a power supply system of a converter substation through a common cathode or common anode connecting wire; a residual current Hall sensor is used for detecting electric leakage residual current of different harmonic waves, and a 3DR electric leakage insulation resistance measurement technology is discriminated based on a Fourier algorithm; according to the harmonic component, the electric leakage resistance, the electric leakage value and the area of the frequency converter of the power supply system of the coal mine mobile converter substation can be judged, and alarm protection is judged; and the harmonic current is dynamically detected, so that selective leakage protection can be realized. According to the invention, through a 3DR electric leakage technology, electric leakage detection and instantaneous protection of the frequency converter are realized; selective earth leakage protection is realized according to the detection of the fundamental component and the harmonic wave; through harmonic leakage current and fundamental wave detection system distributed capacitance, electric leakage protection and capacitive current accurate judgment of power supply equipment in a coal mine power supply system are realized.

The invention discloses a voltage acquisition circuit and power supply equipment, the circuit comprises a voltage acquisition end, a near-end sampling unit, a far-end sampling unit, a voltage selection unit and an anomaly detection unit, and the voltage acquisition end is used for acquiring voltage signals. The near-end sampling unit is connected with an output port of the power supply equipment, and the near-end sampling unit is used for collecting the voltage of the output port of the power supply equipment to obtain a first voltage. The far-end sampling unit is connected with the power port of the load and is used for collecting the voltage of the power port of the load to obtain a second voltage. The voltage selection unit is connected with the near-end sampling unit, the voltage selection unit is connected with the far-end sampling unit, the voltage selection unit is connected with a voltage acquisition end, and the voltage selection unit is used for transmitting a target voltage to the voltage acquisition end. The abnormity detection unit is connected with the far-end sampling unit, and the abnormity detection unit is used for detecting a reverse connection fault or a disconnection fault of the far-end sampling unit.

The invention relates to the technical field of sensors, in particular to a transformer dynamic magnetic bias current detection method and device based on magnetoelectric coupling sensing, and the detection device composed of a magnetoelectric coupling sensing element, an exciting coil and a rear-end processing circuit is used for measuring direct current magnetic bias current. The working principle of the magnetoelectric coupling sensing element is based on stress coupling between the magnetostrictive material and the piezoelectric material, then an output signal is generated on the piezoelectric material, and the sensitivity is remarkably improved by using the resonance amplification effect of the magnetoelectric coupling sensing element. Non-contact current detection can be realized by detecting the magnetic field generated by the magnetic bias current of the neutral point grounding wire of the transformer, and direct physical contact with power equipment is not needed, so that the safety of the system is improved, and the problem of high installation difficulty of a contact sensor is avoided; high-sensitivity, high-precision, anti-interference and real-time transformer direct-current magnetic bias current monitoring is achieved, and the transformer direct-current magnetic bias current monitoring device has the advantages of being easy to install and deploy and small in size.

The invention relates to the technical field of traveling wave positioning, and discloses a traveling wave positioning method, system and device based on an intelligent fuse, and a medium. The method comprises the following steps: installing an intelligent fuse high-frequency sampling signal to obtain digital data; the data is transmitted to a master control fuse to synthesize a zero sequence quantity to obtain a fault judgment result; constructing a feature matrix by applying adaptive threshold wavelet transform based on the zero sequence quantity; combining zero-sequence current and traveling wave characteristics and adopting an improved algorithm to carry out distance measurement and fault positioning; and executing hierarchical protection according to a judgment result and a positioning result to obtain maintenance information. According to the intelligent device, the position of a fault point can be accurately positioned, and differential protection actions can be automatically executed according to the severity of the fault, so that the fault searching and processing time is greatly shortened, and the operation reliability and the maintenance efficiency of the power distribution network are improved.

The invention relates to the technical field of automobile electronic testing, and discloses an integrated ECU power-on burning test monitoring system and method. The system comprises a power supply intelligent regulation and control module, a burning verification module, a test diagnosis module, an abnormity monitoring module and a feedback optimization module. The power supply intelligent regulation and control module realizes stable power supply output through a dynamic voltage frequency regulation algorithm and a temperature self-adaptive algorithm; the burning verification module is used for ensuring the burning integrity by using a block redundancy check and increment verification algorithm; the test diagnosis module diagnoses faults based on the multi-dimensional test data and the decision tree model; the abnormity monitoring module monitors abnormity in real time by using real-time streaming data processing and an isolated forest algorithm; and the feedback optimization module optimizes test diagnosis through incremental learning and a Bayesian optimization algorithm. According to the system and the method, comprehensive and accurate monitoring and optimization of the ECU are realized, and the performance and the reliability of the ECU are effectively improved.

The invention discloses a current inversion method based on a magnetic sensor array, and the method comprises the steps: S1, setting a plurality of measurement points, uniformly dividing a conductor layout region in a to-be-measured part of a to-be-measured multi-conductor system into grids with M * N nodes, and numbering each grid node as (i, j); constructing a coordinate system and recording coordinates of all grid nodes; s2, establishing a finite element simulation calculation model, calculating a reference position coefficient matrix of all measurement points, and constructing a reference position coefficient matrix database; s3, calculating a conductor position coefficient matrix, and constructing a position coefficient matrix; s4, according to the magnetic field measurement value acquired by the magnetic sensor array, the conductor current is calculated through inversion; and S5, after resampling the magnetic field measurement value, substituting the updated measurement value and the position coefficient matrix stored in the step S4 into the linear equation set constructed in the step S4 to solve the current of each conductor. The method has the characteristics of rapid calculation and low operand while the accuracy is ensured, and the inversion calculation efficiency can be improved.

The invention provides a power grid cable real-time current detection method and system, and the method comprises the steps: carrying out the multi-frequency-band synchronous collection of the current of a cable shielding layer for a high-voltage DC power transmission system with multiple loops laid in parallel, and obtaining the time-space information data; an electromagnetic coupling transfer function is calculated based on the data, and an electromagnetic coupling coefficient matrix is constructed, so that near-end cross induction current is separated to obtain a real current signal; establishing a cable dispersion model by using a real current signal, and performing fault feature recognition by combining a time domain criterion, a frequency domain criterion and time-frequency joint entropy analysis; and finally, calculating a credibility index by combining the temperature gradient and the electromagnetic environment parameters, correcting a preliminary judgment result and generating a protection control signal. According to the method, the near-end cross induction current and the real fault current can be effectively distinguished, the problem that the protection system of the multi-end high-voltage direct current system operates by mistake or does not operate in the power-on transient period is solved, and the reliability of the system is improved.

The invention provides an isolation switch control device with a fault monitoring function, and relates to the technical field of electric power automation, and the device comprises an information collection module which collects the current information in real time during the operation of an opening and closing drive motor, and transmits the current information to a circuit protection module; the circuit protection module performs feature extraction on the current information in a mode of solving a signal waveform envelope line; whether the disconnecting switch has a fault is determined according to the current signal characteristics, and a control instruction is issued to the variable frequency driving module according to a fault result, or a key monitoring prompt is sent to the key monitoring module; the variable frequency driving module controls the operation state of the opening and closing driving motor according to the issued control instruction; and when the key monitoring module receives the key monitoring prompt sent by the circuit protection module, the monitoring frequency of the isolation switch is increased. According to the scheme, the abnormal state of the isolating switch can be monitored in the opening and closing process, so that serious accidents caused by faults of the isolating switch are reduced.

The invention relates to the field of switching power supply high-side current detection, in particular to a switching power supply high-side current detection method, which comprises the following steps of: acquiring current signals to form a sequence, acquiring an intrinsic mode by using empirical mode decomposition, analyzing each mode to construct a difference amplitude-frequency index, and calculating a noise index in combination with a similarity index and heterogeneity. According to the method, the de-noising window is intelligently adjusted, and the local outlier factor is utilized to detect the anomaly, so that accurate current anomaly identification is finally realized, the detection precision and the system intelligence level are remarkably improved, the resource utilization is optimized, and a powerful guarantee is provided for stable operation of a power system.

The invention provides a transformer substation residual current intelligent monitoring method and device based on multi-parameter fusion, and relates to the technical field of power system monitoring, and the method comprises the steps: collecting the residual current value of each loop through a residual current sensor, and collecting environment parameters at the same time; performing dynamic confidence fusion on the residual current values of the plurality of residual current sensors through a confidence function and the consistency factor to obtain a fused residual current value; calculating self-adaptive weights of the environmental parameters, and calculating a dynamic threshold value through the nonlinear mapping function of the environmental parameters and the self-adaptive weights; calculating a multi-parameter fusion evaluation index, combining the fusion residual current value, the dynamic threshold value and the multi-parameter fusion evaluation index, calculating a comprehensive fault risk index through a fault membership function, and obtaining a fault diagnosis result according to the risk index value; and outputting early warning information according to the fault diagnosis result. According to the invention, intelligent monitoring and fault early warning of the residual current of the transformer substation can be realized, and the monitoring precision and the reliability of fault diagnosis are improved.

The invention relates to the technical field of state monitoring, in particular to an intelligent fuse comprising a monitoring module, and the fuse comprises a data analysis module, a steady state recognition module, a temperature analysis module, a coupling calculation module and a state calibration module. According to the method, time consistency verification and corresponding matching are carried out on temperature and current sampling, abnormal interference is eliminated in a stable current-carrying interval, a continuous sequence is formed, and a definite time relation is established between thermal response and a current-carrying state by combining analysis of accumulated deviation and change turning of the temperature along with time; the abnormal trend of slow evolution is amplified and presented, correction is carried out according to the direction consistency of multi-segment time difference change, progressive features before fusing are recognized in advance, early warning continuity and operation decision reliability are improved, misjudgment is reduced, continuous updating of state evaluation is supported, and stability of a control closed loop is improved.

The utility model relates to the technical field of circuits capable of automatically changing measuring ranges, in particular to a multi-measuring-range automatic switching circuit, which comprises measuring range control circuits with a plurality of measuring ranges, and is characterized in that each measuring range control circuit is used for carrying out current measurement in a corresponding measuring range so as to be displayed on an ampere meter; the current detection circuit is connected with each range control circuit and is used for detecting the current of each range control circuit; and the MCU main controller is respectively connected with the current detection circuit and each range control circuit and is used for comparing the current of each range control circuit with the corresponding set current and controlling whether each range control circuit is conducted or not according to the result. The situation that ampere meters with different measuring ranges are manually replaced can be reduced.

The invention provides a self-detection signal acquisition circuit based on analog quantity current and voltage mixed input, which comprises a surge protection circuit, a switch selection circuit, a clamping protection circuit, a follower circuit, an impedance matching circuit and an ADC acquisition chip which are connected in sequence, and also comprises a microcontroller, the microcontroller is connected with the ADC acquisition chip and the switch selection circuit, and the ADC acquisition chip is connected with the switch selection circuit. The microcontroller is used for acquiring the output voltage of the impedance matching circuit through the ADC acquisition chip, performing periodic detection on the output voltage of the impedance matching circuit, and periodically outputting a high level or a low level to the switch selection circuit based on the periodic detection result of the output voltage of the impedance matching circuit. Therefore, the switch selection circuit is controlled to switch gears. The technical problems that in the prior art, due to the fact that only a plurality of analog quantity signal input collecting modules of different types can be used for collecting a plurality of sensors with different output signals, the workload of sensor wiring work is large, the work efficiency is low, and the error rate is high are solved.

The invention discloses a lightning arrester data monitoring method and system for optimizing LoRa networking. The lightning arrester data monitoring method and system are used for effectively monitoring a lightning arrester. The method is applied to a lightning arrester data monitoring system. The system comprises a LoRa lightning arrester detection node module, a LoRa-GPRS concentrator gateway module, a remote control platform module, a field lightning arrester control terminal module and a circuit switch remote controller. The method comprises the steps that a LoRa lightning arrester detection node module monitors operation data of a lightning arrester and sends the operation data to a LoRa-GPRS concentrator gateway module through LoRa; the LoRa-GPRS concentrator gateway module receives the operation data and sends the operation data to the remote control platform module through a GPRS network; the remote control platform module performs data analysis on the operation data so as to judge the operation state of the lightning arrester; and the LoRa-GPRS concentrator gateway module performs information interaction with the field lightning arrester control terminal module through a CAN network, so that the field lightning arrester control terminal module processes the lightning arrester by using the circuit switch remote controller according to the operation state.

An energy storage control system includes a plurality of energy storage modules and a plurality of control apparatuses in one-to-one correspondence with the plurality of energy storage modules, where each control apparatus is connected to the corresponding energy storage module, and the energy storage module includes a battery unit and a power unit, the battery unit including at least one battery group. The control apparatus includes a sub-module controller and at least one battery management system in one-to-one correspondence with the at least one battery group, where each battery management system is connected to the corresponding battery group and the sub-module controller, and the sub-module controller is connected to the power unit.

The invention discloses a dual-polarization multi-layer optical current sensor and a multi-physical field disturbance resisting method thereof, and belongs to the technical field of current sensors of power systems. The sensor comprises a dual-polarization multi-layer sensor system and a dual-polarization multi-layer optical current sensor real-time signal processing system which are connected with each other, the output end of a double-layer diamagnetic photoelectric sensing signal processing unit and the output end of a temperature-resistant signal photoelectric sensing signal processing unit in the real-time signal processing system of the dual-polarization multi-layer optical current sensor are connected to the input end of a dual-polarization multi-layer signal processing unit; and the output end of the dual-polarization multi-layer signal processing unit is connected to the multi-physical field anti-interference signal output unit. According to the invention, the resistance of the straight-through optical path type MOCT to ambient temperature field fluctuation can be effectively improved, and the influence of external magnetic interference at any position and the influence of ambient temperature fluctuation interference can be resisted.