2100 results about "Current transducer" patented technology

The invention relates to the technical field of motor fault diagnosis, in particular to a motor fault diagnosis algorithm based on multi-sensor fusion, and the algorithm comprises the steps: injecting a step excitation signal into a motor, synchronously collecting the original response waveforms of vibration and current sensors, and calculating the inherent response delay. Establishing a mapping relation library of delay values and current sensor filtering parameters, calling the delay values in real time according to the filtering parameters, performing reverse time offset compensation on a current harmonic signal time sequence, performing time alignment on the two types of data, finally performing cross-domain coupling analysis on the aligned data, extracting vibration pulse peak frequency and current harmonic fluctuation quantity, and determining the vibration pulse peak frequency and the current harmonic fluctuation quantity. Early faults are judged by combining the bearing outer ring fault characteristic frequency band and the load rate dynamic threshold value, graded alarm is generated by tracking characteristics, the problem of fault false judgment and missed judgment caused by sensor data space-time dislocation is solved, and the early fault diagnosis accuracy of the motor is improved.

The invention relates to a multi-sensor fault feature fusion diagnosis method for electrical equipment, which comprises the following steps: synchronously acquiring operation data of the electrical equipment through a vibration sensor, a temperature sensor, a current sensor and an ultrasonic sensor, dynamically adjusting the sampling frequency according to the physical characteristics of each sensor, and the sampling rate of the temperature signal is not lower than 1Hz. Through a multi-source sensor data synchronous acquisition and time sequence alignment technology and a signal alignment method combining a dynamic time warping (DTW) algorithm and Hilbert-Huang transformation, the problem of time asynchronization of heterogeneous sensor data such as vibration and temperature is solved, so that the time alignment precision of multi-source data is improved, the feature extraction accuracy is improved, and the accuracy of feature extraction is improved. Through hierarchical feature extraction and graph convolutional network fusion, a feature incidence matrix based on mutual information is constructed, deep correlation between vibration signal TKEO features and cross-modal features such as current harmonics is mined by using GCN, the feature dimension is reduced, and the fault feature separability index is improved.

The invention provides a split type direct current charging multi-split group charging and group control control system, and belongs to the technical field of split type direct current charging piles. The split type direct current charging system comprising a main control cabinet, a power distribution unit, a charging pile terminal and other hardware architectures is constructed; a voltage monitoring unit, a current sensor module, a harmonic filter and other multi-dimensional sensor networks are integrated to acquire power grid state data in real time, and a sliding time window method is used to carry out segmented analysis on the data to extract power grid characteristic parameters; establishing a multi-objective optimization model comprising a power balance equation and a power grid stability equation to calculate an optimal power distribution matrix, adopting a neural network to realize intelligent distribution and dynamic balance adjustment of the power of each charging pile terminal, and starting an emergency power redistribution mechanism to ensure stable operation of the system when the power grid is detected to be abnormal. The technical problem of unbalanced power distribution of the multi-pile charging system caused by power grid voltage fluctuation and harmonic pollution is solved.

The invention discloses an intelligent operation and maintenance method. The method comprises the steps of deploying a vibration sensor, a temperature sensor, a current sensor and a pressure sensor at key operation parts of building equipment; receiving an original data flow of each sensor through an edge computing node; performing space-time alignment on the processed sensor data and the equipment operation state parameters; establishing a digital twin model library on the cloud server; and performing mode comparison on the real-time sensor data stream and the fault features in the digital twin model library through a fuzzy matching algorithm, and when the vibration frequency domain features have amplitude sudden change exceeding a baseline value in a preset frequency band, the temperature change rate exceeding a preset threshold and the current harmonic distortion rate exceeding a set proportion, triggering a grading early warning signal. According to the invention, the accuracy, the real-time performance and the intelligent level of operation and maintenance of the building equipment can be obviously improved.

The invention discloses a cable partial discharge detection method and system, and the method comprises the steps: installing sampling sensor groups on a detected cable at a preset interval, and each group at least comprises a current sensor and an ultrasonic sensor; synchronously sampling and preprocessing the high-frequency current signal and the ultrasonic signal; extracting current waveform characteristics and a first time stamp of arrival of the first pulse, and extracting sound wave pulses in the ultrasonic signals and a second time stamp of arrival of the sound wave pulses; and calculating a time difference, if the time difference is smaller than a preset threshold value and the waveform amplitude similarity is within a preset range, determining that no failure partial discharge exists, otherwise, positioning a failure position. According to the method, the acoustoelectric signals are acquired cooperatively through multiple sensors, interference is eliminated in combination with time difference and waveform similarity criteria, the detection reliability and the positioning precision are effectively improved, and the method is suitable for cable insulation state monitoring and fault early warning.

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

The invention relates to the technical field of energy consumption management, and particularly discloses a 12-axis PCB drilling machine energy consumption management system based on resource dynamic scheduling, which collects input and output differential current data and power factor change rate data in real time by deploying a current sensor and a power monitoring module on each motion axis driver; a current anomaly characteristic value and a power stability characteristic value are extracted through a Bayesian point-of-change detection algorithm and a Hilbert-Huang transform method, and a composite energy consumption anomaly characteristic vector is constructed; the random forest model is combined to intelligently score the energy consumption state of each shaft, the working mode of the abnormal shaft is dynamically adjusted according to the scoring result, and self-adaptive scheduling and optimization of energy consumption are achieved; the system continuously optimizes operation parameters through a closed-loop feedback mechanism, the energy consumption of the whole machine is effectively reduced on the premise of guaranteeing the processing efficiency, the intelligence, refinement and greenization levels of equipment operation are improved, and the system has good engineering application value and popularization prospects.

A fastener driver includes a motor, a trigger, and a lifting assembly operable to be moved by the motor. The fastener driver includes a speed sensor, a voltage sensor, and a current sensor. A controller is configured to provide, in response to actuation of the trigger, power to the motor, receive speed signals from the speed sensor indicative of the speed of the motor, receive voltage signals from the voltage sensor indicative of the voltage of a battery pack, and receive current signals from the current sensor indicative of the current of the motor. The controller determines a torque of the motor based on the signals, determines whether the torque of the motor is less than or equal to a torque threshold, and activate an electronic clutch, in response to the torque of the motor being less than or equal to the torque threshold, to electronically brake the motor.

The invention relates to a current sensor chip packaging structure and a packaging method. The current sensor chip packaging structure comprises a bus frame and a chip which are packaged through a plastic package body, the side, provided with the chip bonding pad, of the chip is defined as the front face of the chip, only one side of the front face is configured to be opposite to the back face of the bus frame, the chip bonding pad is arranged on the other side, extending out of the bus frame, of the front face, and a sensor element is arranged on the side, right opposite to the bus frame, of the front face of the chip. A gap between the chip and the bus frame is provided with an isolation layer, and the front surface is connected to the back surface of the bus frame through the isolation layer. According to the current sensor chip packaging structure and the packaging method, the front surface of the chip is connected to the back surface of the bus frame through the isolation layer, and the sensor element is arranged at the position opposite to the front surface of the chip, so that the distance between the sensor element and the bus frame is minimized, and the reliability of the current sensor chip is improved by minimizing the distance between the sensor element and the bus frame. Sensitivity and measurement precision of the sensor are remarkably improved, and the problems of reduction of isolation voltage endurance capability and process fluctuation are avoided.

An adaptive IoT power plug system for intelligent load management and remote control, consisting of: a power plug housing configured to be inserted between a power outlet and an electrical appliance; an embedded sensor array comprising at least one voltage sensor, at least one current sensor, and at least one power sensor and configured to continuously monitor the electrical parameters of the connected device; a microcontroller unit (MCU) operatively coupled to the sensor array and configured to execute a load prioritization technique that dynamically determines power allocation based on real-time consumption data and user-defined priority levels for one or more connected loads; a semiconductor switching module electrically connected to the MCU and configured to selectively interrupt or modulate the power supply to the connected device based on commands from the load prioritization technology; a wireless communication module integrated into the MCU for bidirectional data exchange via at least one wireless protocol selected from Wi-Fi, Zigbee or Bluetooth Low Energy; a user interface that can be accessed remotely via a mobile or web application and enables the configuration of load priorities, real-time monitoring of power consumption, scheduling of device operation, and manual override of switching commands; and a power management subsystem including a power harvesting module configured to provide supplemental power to the system's electronic components, thereby reducing dependence on the main power source; The system autonomously adjusts the power distribution between multiple connected devices to load fluctuations and predefined user priorities in order to optimize energy efficiency and prevent overloading of the circuit.

The invention discloses an electric meter data storage method of a single-phase cost-control electric energy meter, and relates to the technical field of intelligent electric meter data processing, and the storage method comprises the following specific steps: S100, data acquisition and characteristic pro-analysis: acquiring voltage, current and power data of the single-phase cost-control electric energy meter through a voltage sensor and a current sensor, by integrating the voltage sensor and the current sensor, real-time and accurate acquisition of key power utilization data of voltage, current and power of the single-phase charge-control electric energy meter is realized, and by introducing a dynamic time window setting mechanism, the length of a time window is automatically adjusted according to the fluctuation amplitude of the data, so that the accuracy of power utilization is improved. It is ensured that a window is shortened to capture transient changes when data fluctuates violently, the window is prolonged to reduce redundant collection when the data is stable, the flexibility and accuracy of data collection are improved through intelligent adjustment, subsequent data processing can be conducted based on richer and more detailed feature information, and the data collection efficiency is improved. And the intelligent level of the whole data storage system is obviously improved.

A power system includes a central unit, a zone unit capable of communicating with the central unit, and a downstream electric wire configured to electrically connect a predetermined downstream unit to the zone unit. A central processor of the central unit executes processing including transmitting electric wire characteristic data stored in a central storage device to the zone unit at a predetermined timing. A zone processor of the zone unit executes processing including writing the electric wire characteristic data transmitted from the central unit into a zone storage device in response to reception of the electric wire characteristic data, and determining whether to turn a semiconductor switch coupled to the downstream electric wire to an OFF state, based on the electric wire characteristic data written into the zone storage device and the current detected by a current sensor.

The invention relates to the field of current sensor testing, in particular to a calibration test system for a three-phase TMR current sensor, which is provided with a calibration test mode switching device and organically integrates a calibration mode and a test mode into the same equipment. The current sensors with different compatibility can be calibrated and tested, the accuracy of the calibration and test results of the current sensors is ensured, the research and development efficiency is improved, and the equipment investment is reduced.

The utility model relates to a speed-adjustable vacuum circuit breaker, which comprises a controller, a driving mechanism, a current sensor, a supporting insulator, an insulating pull rod, a moving end conductor, a vacuum arc-extinguishing chamber, a static end conductor and a main cable, and is characterized in that when the current of a main loop of the circuit breaker flows through the main cable, the current sensor transmits the detected current value of the main loop to the controller; the controller analyzes and judges the input main loop current value, when the main loop current value is smaller than a set value, the controller inputs a small-value opening control current to a driving mechanism of the circuit breaker, and at the moment, the driving mechanism drives the circuit breaker to do slow opening motion, so that mechanical shock is reduced; and when the current value of the main loop is greater than or equal to the set value N, the controller inputs a large-value opening control current to the driving mechanism of the circuit breaker, and the driving mechanism drives the circuit breaker to perform rapid opening motion at the moment. According to the utility model, the problems of short service life and high failure rate of the traditional circuit breaker are solved, the operation power consumption of the circuit breaker is reduced, and the purpose of energy conservation is realized.

Provided is an electric drum brake system, including: an electric drum brake configured to be driven by an electric motor; a current sensor configured to detect a current input to the electric motor; and a controller configured to, when parking is released, determine a parking release time based on a temperature of the electric drum brake, and when a maintenance time reaches the determined parking release time, end a parking release operation by stopping the electric motor, the maintenance time being a period of time while a state where a motor current detected by the current sensor reaches a target current is maintained.

A magnetic field sensor is provided for sensing a current flowing in a first direction divided in at least two conductor portions separated in a second direction perpendicular to the first direction. It includes at least a first sensing element and second sensing element and at least one integrated magnetic concentrator for sensing the magnetic field at respectively first and second positions in a region between the two conductor portions. The sensing elements are adapted in combination with the concentrator to sense the field with a highest sensitivity in a sensing direction perpendicular to the first direction, wherein the two positions are separated by a predetermined distance in a spacing direction perpendicular to the sensing direction.

The invention provides an on-line monitoring system and method for the grounding current of a transformer iron core, and belongs to the field of data processing, and the system comprises a magnetic adsorption type dual-channel current sensor which is used for synchronously collecting a transformer iron core grounding current channel signal and a transformer clamp grounding current channel signal; the self-adaptive signal preprocessing module is used for carrying out self-adaptive differential processing through a self-adaptive differential coefficient and carrying out variable gain adjustment and self-adaptive filtering; the multi-dimensional feature extraction module is used for performing multi-dimensional signal feature extraction on the purified grounding current signal to obtain a multi-dimensional feature parameter set; the feature fusion module is used for performing constraint fusion on the multi-dimensional feature parameter set based on the corrected iron core eddy current loss physical model, and generating a comprehensive health evaluation index through an adaptive weight adjustment mechanism; and the intelligent diagnosis module is used for carrying out transformer iron core fault type identification, health state evaluation and trend prediction according to the comprehensive health evaluation index and the multi-dimensional characteristic parameter set to obtain a transformer iron core state monitoring result.

The invention discloses a predictive control method and system for a network-building type inverter, and belongs to the technical field of power electronics, and the method comprises the steps: building an output voltage prediction model according to the output voltage data and historical control input signals of the network-building type inverter at the current moment; obtaining a current output voltage prediction value through the output voltage prediction model; obtaining a reference voltage vector of the inverter at the next moment according to a preset optimization criterion function and the current output voltage predicted value, and obtaining an optimal control input signal at the next moment; and according to the optimal control input signal at the next moment, regulating and controlling a switch element of the grid-forming inverter. Therefore, by implementing the method and the device, the problems that a traditional output voltage prediction model is easy to generate model mismatch for an actual inverter, and the reliability of a prediction result is greatly reduced when the data of the current sensor is changed due to the fact that a traditional grid-forming inverter model excessively depends on the data of the current sensor in the prior art can be solved.

An apparatus for detecting disconnection of a power cable of a motor may include a computing device including a processor and a storage medium on which one or more programs configured to be executable by the processor are recorded, wherein the one or more programs may include: obtaining a plurality of sensing current values from a plurality of current sensors respectively sensing currents flowing in a plurality of windings of the motor corresponding to a plurality of phases of the motor; determining a plurality of correction current values by removing a common mode current from each of the sensing current values; and detecting disconnection in each of the phases based on a cable disconnection index based on the plurality of correction current values.

The invention discloses an intelligent furniture anti-pinch control method, and particularly relates to the technical field of intelligent furniture, an intelligent furniture overall frame composed of all movable modules is driven through a push rod, so that stretching and folding actions of the intelligent furniture are completed, pressure sensors are arranged at all the movable modules of the intelligent furniture, and the intelligent furniture anti-pinch control method is achieved. Acquiring a pressure value of each activity module of the intelligent furniture; a current sensor is arranged on a power supply or a manual operator of the intelligent furniture to obtain the current current of a motor; a position detection sensor is arranged in the push rod to obtain the mechanical angular displacement of the motor or the stroke of the push rod; the total load torque of the push rod in the stretching and folding process of the intelligent furniture is obtained according to the load torque applied to the push rod by each movable module of the current intelligent furniture; and calculating a normal current value of the motor according to the obtained total load torque and the mechanical angular displacement of the motor, comparing the current current value of the motor with the calculated normal current value of the motor, and judging whether a person or an object is clamped according to an error.

The invention provides a power storage device and a current interruption method. A power storage device is provided with a power storage device module, a voltage sensor, a current sensor, an explosion fuse, and a controller. The voltage sensor detects a voltage value of the power storage device module. The current sensor detects a value of a current flowing through the power storage device module. The explosion fuse is connected in series with the power storage device module. In the controller, a voltage condition and a current condition are set. The voltage condition is predetermined according to a voltage value detected by the voltage sensor. The current condition is predetermined according to the current value detected by the current sensor. The controller operates the explosion fuse when both a voltage condition and a current condition are satisfied.

The invention relates to a battery health state estimation method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a plurality of charging and discharging total capacities of a to-be-estimated battery under a preset condition, a state-of-charge difference value corresponding to each charging and discharging total capacity and a current battery cell cycle index of the to-be-estimated battery; obtaining a first health state of the to-be-estimated battery according to the plurality of charge-discharge total capacities and the charge state difference value corresponding to each charge-discharge total capacity, and obtaining a second health state of the to-be-estimated battery according to the current cell cycle index; and weighting according to the first health state and the second health state to obtain a final health state of the to-be-estimated battery. Therefore, weighted calculation is carried out on the health states of the to-be-estimated battery in different scenes to obtain the final health state, the problems of SOH value deviation caused by insufficient acquisition precision of a current sensor, insufficient SOH estimation adaptability in different use scenes and the like in related technologies are solved, and the precision and reliability of SOH estimation of the battery are improved.

A self-triggering, bidirectional control electronics component for an electronic switch (50), for the detection and rapid shutdown of currents at a selected threshold value for both current flow directions, includes a threshold switch having a plurality of selectable shutdown threshold values for both current flow directions, the threshold switch coupled to a bidirectional current sensor system (65), arranged in the electronic switch, based on sensing of sensors on an input side of the threshold switch; and a high-speed de-energizing circuit (53) on an output side of the threshold switch including a high non-load circuit voltage for rapid removal of current from a magnetic drive coil (45), the high-speed de-energizing circuit being configured to rapidly remove the current from the magnetic drive coil when the bidirectional current sensor system senses a current greater than or equal to the selected threshold value among the plurality of selectable shutdown threshold values.

The invention discloses an electric arc positioning circuit and an inverter, the electric arc positioning circuit comprises a maximum power point tracking module, a current sensor, an electric arc detection module and a control module, the current sensor is used for detecting real-time current values between a plurality of photovoltaic arrays and a plurality of maximum power point tracking units; the electric arc detection module determines the electric arc fault information by analyzing the real-time current value, the control module obtains the positioning information of the electric arc fault according to the electric arc positioning instruction and the electric arc fault information, the positioning of the electric arc fault can be realized only by using one current sensor, the number of used current sensors is reduced, and the product cost is reduced.

The invention provides a DC Buck converter voltage and current sensor fault-tolerant control system, which comprises the following steps: establishing a time-varying state space model of a DC Buck converter, and dynamically reconstructing a parameter matrix by the time-varying state space model according to the real-time change of a duty ratio; the time-varying augmentation fault estimator is used for monitoring faults of a voltage sensor and a current sensor in real time, the fault estimator is implemented through a model reference adaptive filter, a Buck converter is adopted to construct a reference model in a healthy state, and efficient real-time diagnosis and correction can be achieved through the faults of the voltage sensor and the current sensor of the Buck converter. And various types of sensor faults such as a jump fault, an offset fault, a stuck fault, a high-frequency fault and a gap fault can be effectively estimated. For measurement distortion of the voltage sensor and the current sensor, the fault estimator can provide comprehensive evaluation information of fault types and fault severity.

The invention relates to the technical field of driving control of symmetrical vacuum pressure control valves, in particular to a zero-point-free zero returning method of a double-position synchronous motor for a symmetrical vacuum pressure control valve, which is suitable for scenes needing high-precision pressure control, such as semiconductor manufacturing, vacuum coating, precision vacuum detection and the like. The problems that in the prior art, the vacuum sealing performance is damaged by depending on a special sensor, cost is high, abrasion of a sealing ring is aggravated due to zero point fixation, and double-shaft synchronization precision and load distribution are disjointed are solved. According to the method, the position where the sealing ring reaches the sealing pre-tightening force serves as a dynamic non-fixed zero point, an additional zero point sensor or a collision sensor or a horizontal sensor is not needed, the current-torque coupling characteristic of a motor is utilized, and full-process automatic control is achieved through a high-precision Hall current sensor and an incremental encoder. The method comprises the following specific steps: initializing motor parameters, establishing a T = K * I mapping relation, calibrating a current overload threshold value, calibrating a current detection module, synchronously starting and operating double motor shafts, identifying a collision state based on current detection, locking and verifying a zero returning position, and judging zero point uniqueness based on torque uniformity. The double-shaft zero returning repetition precision is high, zero point uniqueness judgment fits the actual working condition, uneven abrasion of the sealing ring can be reduced, the service life of the sealing ring and the maintenance period of the valve are prolonged, meanwhile, the equipment manufacturing cost and the maintenance difficulty are reduced, and the vacuum sealing stability and the pressure control precision of the symmetric vacuum pressure control valve are effectively improved.

The invention provides a valve fault self-checking method and system based on current detection and a storage medium, and the method comprises the steps: firstly, collecting the working current of a valve driving chip in real time through a non-contact current sensor, and reducing the interference of an external signal on a measurement signal through a non-intrusive design; secondly, analyzing the current curve, the current operation amplitude and the current instantaneous change rate to obtain real-time model matching data; then, dynamic characteristic model reference data is established based on historical current data in the valve state switching process, and the adaptability of an alarm threshold value and the valve working state is improved; and finally, comparing real-time model matching data with theoretical characteristic model reference data, analyzing and identifying abnormal conditions, and triggering graded early warning response or redundancy control operation according to the abnormal conditions. Wherein invalid warning is reduced and the equipment maintenance efficiency is improved by adopting a multi-stage early warning mechanism; in addition, the fault-tolerant rate of the working of the instrument / meter valve is improved through redundancy control operation.

The invention discloses a transducer screening method and device, equipment, a storage medium and a product, and the method comprises the steps: obtaining a head wave of an ultrasonic signal, determining the amplitude of the head wave, and enabling the head wave to be a signal wave of a first ultrasonic signal detected under an initial threshold voltage; judging whether the amplitude of the head wave is in a preset amplitude interval or not, if not, eliminating the transducer, and if yes, determining the pulse width ratio of the head wave; adjusting the initial threshold voltage according to the pulse width ratio of the head wave to obtain a head wave threshold voltage; under the head wave threshold voltage, signal waves of the detected ultrasonic signals are obtained, and the pulse width ratio and the amplitude of each signal wave are determined; determining an evaluation coefficient by using the pulse width ratio variance, the pulse width ratio mean value, the amplitude variance and the amplitude mean value; if the evaluation coefficient is smaller than the preset value, the current transducer is reserved.

The invention relates to a non-current sensor model prediction control method and system based on an LC filtering type voltage source inverter, and belongs to the field of inverter control. The designed sliding mode observer only needs capacitance parameters, and inductance and voltage observation errors have no influence on current observation errors. A capacitor current predicted value and a capacitor voltage predicted value are predicted by using the sliding mode observer, and the three-phase switching state of the inverter is regulated and controlled according to the predicted values. Therefore, the parameter robustness of the sliding-mode observer is high, and when the sliding-mode observer is used for controlling the inverter, the control precision is high.

The invention provides an online inspection method and system for a photovoltaic module, and the method comprises the steps: generating an optimal inspection path through a path planning algorithm P = f (L, A) based on a photovoltaic array topological structure; the unmanned aerial vehicle carries a multispectral camera, an infrared thermal imager and a current sensor to fly, and a visible light image, an infrared thermal image and electrical parameters are synchronously obtained; an improved YOLOv5 algorithm is adopted to analyze the collected data in real time to identify a fault component; performing correlation analysis F (T (x, y), I) on the temperature field distribution characteristic T (x, y) and the current characteristic I to distinguish fault types; and generating a fault map containing GPS coordinates and a maintenance suggestion according to an analysis result, and relates to the technical field of photovoltaic power station operation and maintenance, the unmanned aerial vehicle automatically performs routing inspection according to a planned path, the routing inspection time is greatly shortened, the routing inspection efficiency is improved, and the application of multi-source data acquisition and a deep learning algorithm can more accurately detect and classify faults, so that the fault detection efficiency is improved. The false detection rate is reduced, and the fault detection accuracy is enhanced.