3112results about "Power supply testing" patented technology

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 a power supply fault rapid detection system and method based on an intelligent diagnosis engine, and belongs to the technical field of power electronic equipment fault diagnosis, and the system comprises a function region division module which is mainly used for dividing a plurality of function regions according to a power supply topological structure; the real-time data acquisition module is mainly used for acquiring parameter data of each functional area in a power supply operation stage; the current model building module is mainly used for building a current time sequence prediction model; the trend prediction module is mainly used for generating a future current change trend; the abnormity judgment module is mainly used for identifying an abnormal condition by performing similarity matching with real-time data; the fault positioning module is mainly used for matching with a fault mode based on an abnormal current waveform and constructing a directed graph to position a fault position; the method has the advantages that early warning and accurate positioning of the power supply fault are realized through multi-modal data fusion and a deep learning model, and the operation and maintenance efficiency and reliability of the power electronic equipment are remarkably improved.

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 an energy storage power supply residual life prediction method and system based on dynamic weight distribution, and belongs to the technical field of energy storage power supply health management. The method comprises the following steps: acquiring voltage, current and temperature time sequence signals of energy storage power supply operation through a multi-source sensor, and constructing a degradation characteristic sequence by adopting a sliding window method; a degradation inflection point division stage is detected and identified by using a curvature extreme value, a historical degradation mode is matched based on a dynamic time warping algorithm, and an optimal model group is selected; respectively carrying out dynamic weight distribution on the time step length and the feature dimension by adopting a dual-channel attention network, and fusing a learnable coefficient with space-time attention output to generate a life prediction result; residual errors and feature drift are monitored and predicted in combination with an incremental learning mechanism, and model parameters are updated and a degradation knowledge base is expanded by adopting an elastic weight consolidation algorithm. According to the method, the key information capturing capability is enhanced through a space-time attention mechanism, the model adaptability is optimized in combination with incremental learning, and the energy storage power supply life prediction precision and the working condition generalization performance are remarkably improved.

The invention provides a multi-dimensional grid-connected test system for a photovoltaic string inverter, and the system comprises a power grid simulation module which is used for constructing a power grid simulation environment based on a multi-dimensional coupling mechanism of voltage fluctuation, frequency deviation and harmonic distortion; the photovoltaic array simulation module is used for constructing IV characteristic dynamic deduction models of different irradiance and temperature gradient effects based on a photovoltaic array equivalent circuit physical model to realize a natural simulation environment; the loading module is used for loading the power grid simulation environment and the natural simulation environment to the photovoltaic string inverter to be tested; the data acquisition module is used for monitoring running state data of the photovoltaic string type inverter in real time and constructing a running state data set containing multi-physical-quantity coupling characteristics; and the diagnosis module is used for inputting the running state data set into the trained LSTM neural network model to obtain a test result of the photovoltaic string inverter. According to the invention, the efficiency and convenience of the grid-connected test of the inverter can be improved, and the accuracy and reliability of the grid-connected performance of the inverter are ensured.

The invention discloses an intelligent operation and maintenance fault early warning method for a rail transit variable-frequency power supply, and relates to the technical field of power electronics and intelligent operation and maintenance, and the method comprises the following steps: setting a multi-point synchronous collection device to carry out the high-precision real-time collection of voltage and current signals of a variable-frequency power supply system, and carrying out the digital coding processing of data; and performing frequency domain analysis on the acquired voltage and current signals by using a preset spectrum analysis algorithm, and extracting harmonic amplitudes and phase characteristic parameters of different orders. According to the invention, through high-precision synchronous acquisition and spectrum analysis, rapid and accurate identification of harmonic abnormity is realized; a machine learning model and dynamic threshold adjustment are fused, and the adaptability and intelligent recognition capability of the system to fault modes under multiple working conditions are enhanced; and a trend prediction and graphical early warning platform is introduced, so that the fault risk is pre-judged in advance and visually responded, and the operation and maintenance efficiency and the operation safety of the rail transit power supply system are remarkably improved.

The invention relates to the technical field of power electronic equipment testing, and discloses a special intelligent testing device and method for a power UPS, and the device comprises a multi-source power supply system which comprises a three-phase program-controlled variable-frequency power supply, a single-phase program-controlled variable-frequency power supply and a DC program-controlled power supply, the output voltage of the three-phase program-controlled variable-frequency power supply is 0-480V and is adjustable, and the output voltage of the single-phase program-controlled variable-frequency power supply is 0-480V; the output voltage of the single-phase programmable variable-frequency power supply is 0-280V and the frequency of the single-phase programmable variable-frequency power supply is 45-64Hz and adjustable; the output voltage of the direct-current programmable power supply is 50-1000V and adjustable; an electronic load system; a signal acquisition system; an embedded control system; and an upper computer software system. A three-phase program-controlled variable-frequency power supply, a single-phase program-controlled variable-frequency power supply and a direct-current program-controlled power supply are integrated to form a multi-source power supply system, a resistive and rectifying dual-mode electronic load is combined, millisecond-level synchronous switching of a voltage level and a load state is realized through an embedded control system, a closed-loop test capability of multi-dimensional performance of the power UPS is formed, and the test efficiency is improved.

The invention relates to the technical field of electrical fault detection, in particular to a mobile power supply fault detection method and system based on intelligent diagnosis, and the method comprises the following steps: collecting voltage and current data of a mobile power supply in a normal operation state, and generating an electrical performance baseline data set through recording the timestamp of the data and a corresponding electrical performance index; and based on the electrical performance baseline data set, extracting time sequence features of voltage and current to obtain electrical performance feature data. According to the invention, based on voltage and current data acquisition in a normal state of the mobile power supply, a baseline data set covering timestamps and electrical performance indexes is established, and detail information of electrical performance changes is captured by extracting time sequence features such as peak values, mean values and standard deviations; meanwhile, frequency spectrum features are accurately extracted by means of fast Fourier transform, the intensity and phase information of frequency components is mastered, then signals are decomposed through wavelet transform, and richer electrical performance anomaly information under multiple scales is obtained.

The invention provides a shelter rapid power supply recovery method and system suitable for an emergency rescue task. The method comprises the following steps: collecting a power interruption signal, analyzing the power interruption signal, and generating an emergency response instruction; fault points are automatically identified and accurately positioned, the importance level of each electric device in the shelter is evaluated, and a dynamic priority list and a device demand report are generated; intelligently selecting a stand-by power supply combination scheme, starting a stand-by power supply switching process, and generating a stand-by power supply activation instruction; after a standby power supply activation instruction is received, the power supply sequence and power distribution of all devices are dynamically adjusted, normal operation of key facilities is preferentially guaranteed, and a device power supply plan is generated; and continuously monitoring the working state of the standby power supply and the influence of the standby power supply on the overall power system of the cabin, dynamically optimizing the power supply strategy, and generating an optimized power supply scheme. According to the technical scheme provided by the invention, the response speed and the power supply reliability of the shelter hospital or the temporary emergency facility during power interruption are improved.

The invention relates to the technical field of inverter open-circuit fault diagnosis, and provides a PMSM inverter open-circuit fault diagnosis method based on SMO-MLD, and the method comprises the following steps: building an inverter hybrid logic dynamic model and a novel super-spiral sliding-mode observer, constructing a first fault detection variable and a self-adaptive threshold value, and constructing a second fault detection variable and a self-adaptive threshold value; meanwhile, constructing a second fault detection variable and a fixed threshold value, defining a first logic variable, a second logic variable and a fault indication variable, dividing fault types into a single-tube fault, a cross double-tube fault, a different-phase double-tube fault and an in-phase double-tube fault, and positioning the faults; according to the method, a traditional sliding-mode observer is replaced by self-adaption in the novel super-spiral sliding-mode observer, the sliding-mode surface approaching time is shortened, buffeting of sliding-mode motion is reduced, a traditional fixed threshold value is replaced by a self-adaption threshold value, the fault diagnosis time is shortened, and the fault diagnosis robustness is improved.

The invention relates to a remote fault diagnosis method and system for an intelligent energy storage power supply, and the method comprises the following steps: carrying out the real-time monitoring of electrical parameters of the energy storage power supply, capturing abnormal fluctuation, and transmitting the abnormal fluctuation to a remote intelligent diagnosis center; and extracting a fault feature vector group through a deep learning algorithm, analyzing a fault propagation path, and generating a fault propagation link diagram. Causal relationship reasoning is carried out based on the graph, and a fault source and a fault type are positioned. And according to the fault source and the type evaluation influence range, obtaining a fault influence degree evaluation report. Finally, an intelligent fault processing suggestion scheme is generated according to the report, rapid and accurate fault diagnosis and processing are realized, and safe and stable operation of the energy storage system is ensured. The technical problems that a traditional fault diagnosis method often depends on the experience of field technicians and simple fault detection equipment, time and labor are consumed, and in the face of complex or hidden faults, the traditional fault diagnosis method is often out of effort are solved.

The invention relates to the technical field of DC / DC power supplies, and discloses a DC / DC power supply function parameter testing method and system and computer equipment, and the method comprises the steps: injecting a preset disturbance signal into an input end of a tested DC / DC power supply through a signal conditioning circuit, and obtaining output voltage response data and output current response data; adopting a dynamic multi-parameter test system and collecting target test parameter data; calculating a characteristic parameter set, and executing voltage-temperature control model predictive control analysis to obtain a control parameter sequence; and controlling the power output value of the electric heating wire, the rotating speed value of the heat dissipation fan and the position value of the electric push rod in the test box body to obtain an intelligent adjustment test environment and generate an aging test result and a test strategy adjustment instruction, thereby overcoming the problem of parameter detection blind areas in a traditional test method, and improving the test accuracy even under the condition that the output voltage is accurately matched with the set value. And the power supply performance abnormity can be effectively identified, and the reliability and accuracy of the test are obviously improved.

The invention discloses an integrated power supply test method and system integrating fault prediction, and relates to the technical field of power supply test. A comprehensive power supply test system integrating fault prediction comprises a test parameter acquisition module, a reference state updating module, a data fusion module, a fault prediction module and a retest recording module. According to the method, the first prediction channel and the second prediction channel are arranged, and the model path is flexibly selected in combination with the initial anomaly judgment result, so that the prediction accuracy is improved while the prediction efficiency is ensured, and operation requirements in different complexity scenes are met; by setting a circulation analysis mechanism and a dynamic circulation limit value and based on weight increasing operation of a maximum influence data item, intelligent verification and self-adaptive adjustment of model result consistency are realized, and the stability and robustness of a fault judgment process are enhanced.

The invention relates to the technical field of power supply system health assessment, in particular to a health assessment method and system of a power supply system based on artificial intelligence. The method comprises the following steps: acquiring data of a power supply system, estimating initial performance parameters of the power supply system, evaluating an initial running state of the power supply system, and acquiring initial state data of the power supply system; performing power supply equipment load operation simulation based on the initial state data, and predicting a fault evolution trajectory; the transmission quality attenuation degree of the power supply system is estimated by analyzing the fault evolution trajectory of the power supply system, the loss increase trend of a transmission line is detected, and the performance decrease trend is evaluated in combination with the attenuation degree; evaluating health attenuation data of the power supply system according to the performance reduction trend; transmitting the data to an artificial intelligence model for deep learning training to obtain accurate power supply system health state evaluation data; according to the invention, health analysis is carried out on the power supply system, so that the power supply system is safer and more stable.

The invention relates to the technical field of energy storage management, and particularly discloses a UPS energy storage system and method based on power management, and the system comprises the steps: collecting the electrical state parameters of each UPS node in a cluster in real time through a parallel monitoring module, collecting the state parameters of a power grid end through a power grid analyzer, carrying out the load characteristic fluctuation phase analysis of a de-noised UPS node characteristic data set, and carrying out the calculation of the uninterrupted power supply (UPS). Extracting a time domain load change gradient of each UPS node; predicting a load demand interval of each UPS node in the future 15 minutes through an LSTM sequential network; generating a dynamic energy efficiency MAP graph of each UPS node based on historical energy efficiency curve data, and calibrating an optimal energy efficiency working interval of each UPS node in combination with a real-time SOC; generating a cluster-level load distribution feasibility matrix according to cross comparison of the load demand interval and the optimal energy efficiency working interval; and on the basis of the generated cluster load distribution control instruction set, the stable transition of each UPS node during load switching is ensured, the impact caused by switching is reduced, and the overall efficiency and safety of the system are improved.

The invention relates to the technical field of unit power failure detection, in particular to an AC power supply input power failure detection method and system. The AC power supply input power failure detection method comprises the following steps: comparing a characteristic voltage value with a preset threshold value; triggering a sampling frequency adjustment mechanism according to the preliminary detection signal, increasing the sampling rate according to the voltage fluctuation frequency by adopting an adaptive algorithm, and obtaining high-precision sampling data through real-time calculation; for the optimized power consumption control scheme, acquiring current system state data, coordinating quick response capability and low power consumption optimization through a state machine algorithm, and outputting a multi-stage interaction strategy signal; adjusting a dynamic threshold value of capacitance voltage division design according to the multi-stage interaction strategy signal, and predicting voltage fluctuation by adopting a Kalman filtering algorithm to obtain smoothed detection sensitivity data; and analyzing the misjudgment rate reduction degree through a threshold fine tuning algorithm in combination with the abnormal fluctuation characteristics and the partial pressure state, and outputting a final power failure detection result.

The invention discloses an output voltage detection method and system based on an aviation power supply, and relates to the technical field of aviation power supply voltage detection. A differential voltage sensor is connected to the output end of an aviation power supply, a high-frequency suppression capacitor is connected in parallel, the sampling rate of 20-50 times of the working frequency is set according to the type of the power supply, and the signals are collected and converted into analog voltage signals; the analog signal is subjected to two-stage filtering, is amplified to 0-5V through an instrument amplifier, and is converted into a digital voltage sequence through a 16-bit ADC (Analog to Digital Converter); calculating AC power supply effective value, peak value and other parameters, DC power supply average value, ripple coefficient and other parameters; comparing the characteristic parameters with a preset threshold value, determining that the characteristic parameters exceed the threshold value and recording related information; and a detection result is transmitted to a monitoring terminal through an RS485, data is locally stored, and a switching value is output to an alarm device when the data is abnormal. The method adapts to aviation power supply load fluctuation and environment temperature change, detection precision is high, data transmission and storage are safe, abnormity is accurately identified and early warning is carried out in advance, and aviation power supply operation and maintenance reliability and efficiency are improved.

The invention discloses a remote real-time monitoring and fault early warning method for a power supply operation state, and relates to the technical field of power electronics and energy management, and the method comprises the steps: collecting the temperature data of a key part of a power supply through an optical fiber Bragg grating sensor array, and analyzing the wavelength offset; electrical parameters are collected through a differential MEMS current / voltage sensor, and a permalloy / ferrite composite shielding layer is arranged in the sensor; collecting a mechanical vibration signal through a piezoelectric ceramic vibration sensor; for device data from different manufacturers, Modbus and CAN heterogeneous protocols are matched and analyzed through a regular expression, and the Modbus and CAN heterogeneous protocols are converted into a unified RDF triple format; inputting temperature, current and vibration data into a space-time alignment module, and constructing a semantic mapping relation by adopting an ontology; calculating a sensor confidence coefficient weight, and performing weighted fusion to generate an equipment health index; operating a lightweight LSTM model at an edge node, and detecting current harmonic and vibration resonance frequency band abnormity in real time; cOMSOL multi-physical field simulation is combined at the cloud end, and the evaporation rate of the capacitor electrolyte is predicted.

The invention relates to the technical field of aircraft power supply systems, and discloses an intelligent power distribution and fault diagnosis method for an aircraft power supply system, which comprises the following steps: acquiring a real-time current signal and load working condition information of an aircraft power supply bus, a double-domain composite entropy feature is constructed by extracting a time domain entropy transition index representing the energy domain stability of a current signal and a phase synchronization index representing the time structural domain stability; according to the method, dual inspection of the energy domain and the time structure domain is carried out on the current signals, and cooperative judgment is carried out in combination with the load working condition, so that sensitive capture of real fault forebodes is realized; and meanwhile, tolerance is dynamically shown on normal loads in the airplane operation process, the restriction between safety and usability in the prior art is effectively avoided, and predictive health management is made possible.

A load connection state detection method for an energy storage power supply. The energy storage power supply comprises an inverter power supply. The method comprises the following steps: sampling an output voltage and an output current of the inverter power supply, and calculating output apparent power (S1); and determining whether the apparent power is less than a preset power threshold; if the apparent power is greater than the preset power threshold, a detection result being that a load is connected to the energy storage power supply; and if the apparent power is less than the preset power threshold, executing an active load online detection algorithm for secondary detection, and according to the secondary detection result, determining whether a load is connected (S2).

The invention provides an abnormal power failure diagnosis method and device, and relates to the technical field of power failure diagnosis, the device comprises an MCU, the MCU is connected with a selection switch through a line, and one end of the selection switch is provided with a capacitor. Hardware hidden dangers can be eliminated at the beginning of power-on through hardware self-inspection in the system pre-starting stage, and it is guaranteed that operation baselines of the whole delay power supply module and the MCU are correct; according to the following capacitor energy charging function, a super capacitor is connected in parallel to the 12V low-voltage power supply side, and the charging current and voltage slope are monitored in real time, so that even if the capacitor stably and safely stores enough energy, overcharge damage is prevented, and monitoring is interrupted by data heartbeat of an MCU and a BMS master controller and power-down cmd, it is ensured that the system can sense a power-off instruction in time at any time, and the power-off state of the system is ensured to be stable and reliable. And persistent storage of the key operation parameters is completed in an atomicity write-in mode, so that the data loss risk caused by communication timeout or software faults is greatly reduced.

The invention discloses a power supply integrity automatic test system based on multi-parameter intelligent cooperation, and belongs to the technical field of power supply test. Automatically identifying a power supply type through a power supply type identification and configuration module, and calling preset test parameters from a database to generate a test scheme; the method comprises the following steps: synchronously acquiring multi-modal data output by a power supply through a multi-parameter acquisition module, wherein the multi-modal data comprises test parameters of various power supplies; performing standardized scoring on each test parameter of the power supply through an intelligent scoring module; constructing a three-dimensional incidence matrix through an automatic evaluation module, dynamically adjusting the weight of each graded test parameter, and calculating an evaluation index of the power supply integrity; feedback information is generated through a feedback module, and a visual report of the power supply integrity test is generated according to the visual template; through mutual cooperation of the modules, automation of power supply integrity testing is realized, manpower is saved, and evaluation objectivity is improved.

The invention provides a mainboard power supply output voltage stability test method and system, and the method comprises the steps: generating a dynamic stepped load current based on a load demand parameter and a limit working condition defined by a hardware specification when a mainboard operates in a preset multi-mode switching state, and setting a first synchronization window before each step switching moment, setting a second synchronization window after the step switching time, collecting voltage waveform data, inputting the voltage waveform data into a preset filtering algorithm, extracting an overshoot amplitude and recovery time, constructing an asymmetric coupling model, and taking a difference value between the overshoot amplitude and a preset fluctuation range as a first stability index; the ratio of the recovery time to the response time threshold value is used as a second stability index, nonlinear weight distribution of the two indexes in multiple step intervals is calculated, a stability grade judgment result is generated in combination with a circuit board wiring impedance characteristic library, and the test compatibility of high-density mainboard multi-phase power supply and high-frequency devices is improved.

The invention relates to the technical field of photovoltaic inverter regulation and control, in particular to a device capable of adjusting, controlling and monitoring a photovoltaic inverter. Comprising an intelligent adjusting unit which adopts a multi-parameter dynamic matching algorithm based on power grid situation awareness; an adaptive protocol unit; a state monitoring unit; and a safety control unit. According to the method, a multi-parameter dynamic matching algorithm based on power grid situation awareness is adopted, power, current and voltage parameters output by the photovoltaic inverter and voltage, frequency real-time parameters and fluctuation trend parameters of the power grid are collected, and the power grid situation dynamic matching logic is combined, so that accurate dynamic adaptation between the output of the inverter and the state of the power grid can be realized; the problem of insufficient adaptability caused by the fact that the power grid situation is not considered in traditional single-parameter adjustment is solved; and PWM adjusting signals are generated through the parameter acquisition module, the power grid situation analysis module and the adjustment decision module to drive an IGBT switch tube, so that the accuracy and stability of output adjustment are guaranteed.

The invention discloses a state monitoring method and system for an outdoor emergency power supply. Firstly, original data such as battery internal resistance, charging efficiency, temperature fluctuation and load abrupt change are collected to form an initial data set; and then noise suppression and fusion processing are carried out on the data set to obtain a smoothed battery parameter sequence. And constructing a dynamic trend vector by analyzing the differential change of the sequence, judging a potential anomaly level according to the slope of the dynamic trend vector, and outputting an anomaly probability score. And identifying an inter-parameter interaction cluster based on clustering analysis, and performing causal reasoning on a dominant cluster to determine a fault dominant factor. And finally, in combination with the real-time state, the environmental parameters and historical defect information, constructing a modeling matrix, and executing multi-dimensional clustering to identify specific fault types such as bearing wear, insulation aging and the like. If the fault is caused by internal resistance abnormity, an interference source is further positioned, and an accurate fault position is output. According to the invention, the battery fault monitoring accuracy and positioning capability in a complex environment can be effectively improved.

The invention relates to the technical field of power electronics, in particular to a direct-current charging pile insulation monitoring method and system, and the method comprises the following steps: monitoring the voltage deviation between a branch and a bus in real time, adjusting a measurement compensation parameter, correcting a branch insulation resistance measurement value, recognizing leakage current drift, positioning a leakage branch, triggering relay control, and sending alarm information. And generating a charging pile monitoring record. According to the method, the branch voltage deviation trend and the voltage compensation parameters are combined, the branch voltage measurement consistency is improved, the insulation resistance fluctuation is utilized to compare and correct the observation error, the measurement precision is optimized, the current deviation compensation in the no-load state is adopted to eliminate the zero drift interference of the sensor, and the measurement accuracy is improved. A current jump amplitude and a voltage direction are combined to identify an electric leakage branch, positioning accuracy is enhanced, a relay control and event information linkage mode is used, alarm response and equipment state records form a closed loop, and real-time performance and integrity of system monitoring are improved.

The invention discloses a gas meter power supply abnormity monitoring system and method based on a signal acquisition technology, and relates to the technical field of gas meter power supplies, the system comprises a multi-dimensional sensing module, a dynamic adaptive module, a multi-dimensional fusion analysis module, an intelligent judgment module and a verification execution module; according to the invention, the multi-dimensional fusion analysis module accurately calculates key parameters such as a power supply ripple coefficient and load transient response time in a corresponding mode, the electromagnetic interference intensity is calculated through professional algorithms such as discrete Fourier transform in combination with an environment electric field and a magnetic field sequence, a threshold value is dynamically adjusted based on a working mode, and a comprehensive score is calculated through multi-parameter deviation weighted fusion. The power supply state is deeply and comprehensively evaluated; the intelligent judgment module scientifically divides anomaly levels according to comprehensive scores, quantifies and distinguishes real anomaly and environmental interference by means of an environmental interference contribution degree formula, solves the problem that traditional monitoring cannot accurately recognize power anomaly under complex working conditions, and improves anomaly judgment accuracy.

The invention discloses a sampling current calibration method and device of a power supply, electronic equipment and a storage medium, and relates to the technical field of computers, and the method comprises the steps: collecting a current current value of the power supply; if the current value meets a preset calibration condition, obtaining a plurality of current sampling values under each load point in the power supply, obtaining a current average value based on the plurality of current sampling values, and comparing the current average value with a preset current theoretical value to obtain a linear relation between the current average value and the preset current theoretical value; and determining a current correction coefficient based on the linear relationship, and correcting the current value by using the current correction coefficient to obtain a calibrated current sampling value. The technical problem that the sampling current value of a traditional voltage calibration method has deviation and the accuracy of power supply control is reduced is solved, and the technical effect of improving the accuracy of power supply monitoring is achieved by correcting the sampling current value of the power supply.

The invention relates to an energy storage converter performance evaluation method and device, equipment, a medium and a program product. The method comprises the following steps: acquiring performance index parameters of the energy storage converter under a plurality of evaluation dimensions; the evaluation dimensions at least comprise electrical performance, thermal performance, mechanical performance, environmental adaptability and control performance; performing correlation analysis processing on correlation degrees among the evaluation dimensions based on the performance index parameters to generate a correlation matrix; vectors in the incidence matrix are used for representing the correlation degree between every two evaluation dimensions; and performing statistical analysis and quantitative evaluation processing on the incidence matrix to obtain a performance evaluation result for the energy storage converter. By adopting the method, the accuracy of energy storage converter performance evaluation can be improved.