492 results about "Current wave" patented technology

The invention discloses an electric power utilization anomaly detection and early warning method based on the Internet of Things, which relates to the technical field of electric power utilization and comprises the following steps of: performing fitting comparison on identified inductive current fluctuation and a behavior residual error template generated based on a real load behavior; analyzing a response time window, a fluctuation amplitude track and a behavior continuity characteristic, and judging whether the inductive current fluctuation generated by a non-target loop belongs to a real load change behavior or not under the condition that a plurality of loops are grounded together according to the response time window, the fluctuation amplitude track and the behavior continuity characteristic; and combining the behavior residual error fitting score, the phase consistency value and the frequency response stability value to generate a signal credibility judgment sequence, and carrying out credibility grade division on the inductive current fluctuation. According to the method, the problem of false fluctuation misjudgment caused by inductive signal interference under the condition that multiple loops share the grounding condition is solved, accurate identification and dynamic regulation and control on the authenticity of inductive current fluctuation are achieved, and therefore the accuracy and reliability of power utilization anomaly detection and early warning are improved.

The invention discloses a variable frequency driving device energy recovery control system based on direct power supply of a high-voltage power grid, and relates to the technical field of electrical transmission and energy recovery control. Updating the power grid impedance model in real time by using a complex impedance calculation method; load operation state parameters are dynamically adjusted in combination with motor end output power, rotating speed change and torque calculation; according to the method, regenerative energy is accurately calculated, a feedback path is adjusted according to voltage fluctuation and frequency deviation of a power grid, a feedback current fluctuation ratio and a power factor are monitored, a feedback path conduction proportion is optimized in real time, when the current is unstable or the power factor is abnormal, a suboptimal path is automatically switched, and continuous and stable operation of a system is guaranteed; according to the invention, the energy feedback efficiency and the power grid compatibility of the high-voltage power grid variable-frequency driving device are effectively improved, and the method is suitable for energy feedback application of a high-power motor driving system.

The invention discloses a rectifier bridge arm fault identification method and system circuit based on multi-characteristic current waveform analysis, and relates to the technical field of rectifier bridge arm fault identification, and the method comprises the steps: collecting a current signal of an AC input side of a rectifier bridge through a current sensor, and obtaining an original current time domain waveform after filtering conditioning; performing period division on the original current time domain waveform based on a voltage synchronization signal, and outputting a positive half-cycle conduction interval and a negative half-cycle conduction interval in each power frequency period; in each power frequency period, performing square integral operation on the current waveforms of the positive half-cycle conduction interval and the negative half-cycle conduction interval to obtain a positive half-cycle energy value and a negative half-cycle energy value, and calculating an energy unbalance degree; and windowing fast Fourier transform is carried out on the original current time domain waveform, amplitudes and phases of third, fifth and seventh characteristic harmonics are extracted to form a harmonic characteristic vector, the vector is matched with a pre-stored bridge arm fault harmonic fingerprint template, and the matching degree of each fault type is obtained.

The invention discloses a transient-time varying-based transformer anti-short circuit capability dynamic checking method and system. According to the method, a high-fidelity digital twinborn model is established by constructing a four-layer database comprising a foundation, a material, a structure and operation parameters. And performing transient electromagnetic-structure coupling simulation by using the reconstructed real short-circuit current waveform driving model to obtain transient electromagnetic force, dynamic deformation and stress distribution prediction results under short-circuit impact. Meanwhile, a multi-axis degradation model covering mechanical, electrical and thermal dimensions is constructed, long-term evolution of equipment is quantified, conventional working conditions are converted into equivalent short-circuit impact times, and a comprehensive capability index is calculated. Finally, the transient impact risk and the long-term degradation degree are coupled, a four-quadrant risk assessment matrix is constructed, a comprehensive risk quantitative index is calculated, and dynamic grading and accurate positioning of the overall risk state of the transformer are achieved. According to the method, the problems of isolated island and single risk dimension of traditional static check information are solved.

Disclosed in the present invention are a feeder automation test method and apparatus, a device, and a storage medium. The method comprises: calculating a voltage effective value and a current effective value of each node in a distribution network framework under different fault handling section conditions of a feeder automation system; sending the voltage effective values and the current effective values to a corresponding tester, such that after receiving the voltage effective values and the current effective values, the tester converts the voltage effective values into an analog voltage waveform, converts the current effective values into an analog current waveform, outputs the analog voltage waveform and the analog current waveform to a corresponding field power distribution terminal, and returns switch position change information of the field power distribution terminal; and comparing the switch position change information with preset standard feeder automation action logic in a corresponding fault handling section condition and then, on the basis of a comparison result, obtaining a feeder automation test result. The present invention can improve the reliability of feeder automation tests.

The invention relates to the technical field of constant-temperature stirring equipment control, in particular to a temperature control method of a constant-temperature stirrer, which comprises the following steps of: calculating an instantaneous deviation array between real-time temperatures of multiple monitoring points in a heating container and a target temperature by acquiring the real-time temperatures; and a maximum value, a minimum value and a mean value are extracted to construct a divergence characteristic triple representing the temperature distribution state. Meanwhile, the running current waveform and the real-time rotating speed of the stirring motor are associated, and a load disturbance characteristic curve is generated. And synchronously inputting the instantaneous temperature deviation array, the divergence characteristic triple and the load disturbance characteristic curve into a temperature compensation depth prediction network, and outputting a heater duty ratio sequence and a stirring motor speed regulation instruction sequence in a plurality of control periods in the future by the network. The method can actively sense the uniformity of the internal temperature field and quantify the dynamic disturbance of the stirring load, thereby improving the temperature control uniformity and the anti-interference capability of the system.

The invention specifically relates to a method and a system for detecting a high-resistance grounding fault of a power distribution network, and belongs to the technical field of power distribution network fault detection. According to the method, the amplitude difference of the zero-sequence current is converted into the angle difference through the Grubby angle field coding, so that weak current distortion is amplified into a remarkable spatial stripe in the Grubby angle field image, and the abrupt change characteristic in the fault transient process can be effectively represented. Meanwhile, due to the symmetry and translation invariance of the Grubrum angle field matrix, the time domain dependency relationship of the zero-sequence current waveform of the high-resistance grounding fault is completely reserved, and the fault feature extraction capability can be effectively improved. According to the method, a traditional standard convolution kernel is improved according to polar coordinate characteristics of the Grubrum angle field image, time evolution characteristics are extracted by using radial branches of the multi-axis variable neural network, amplitude distortion characteristics are extracted by using angular branches of the multi-axis variable neural network, diagonal characteristics are extracted by using deformable convolution in a self-adaptive manner, and the expression ability of the extracted characteristics is effectively improved.

The invention relates to the technical field of motor performance evaluation, in particular to a permanent magnet direct current pump motor performance evaluation method and system based on cloud computing. Comprising the steps of obtaining current waveform data and vibration waveform data, and obtaining a first criterion based on the current waveform data and the vibration waveform data; obtaining a second criterion according to the vibration waveform data; obtaining a third criterion according to the vibration waveform data; obtaining a fourth criterion according to the current waveform data and the vibration waveform data; judging the causal correspondence between the current step and the output change of the control loop to obtain a fifth criterion; continuously observing the change trend of high-frequency components in the vibration waveform data to obtain a sixth criterion; based on the first criterion, the second criterion, the third criterion, the fourth criterion, the fifth criterion and the sixth criterion, obtaining a classification result; and confirming measures according to a classification result. The problems of repeated false alarm, invalid maintenance and system reliability evaluation deviation caused by the fact that a permanent magnet direct current pump motor performance evaluation system cannot distinguish real mechanical faults under a low-speed cruise working condition in the prior art are solved.

The invention relates to the technical field of thunder and lightning monitoring and protection, in particular to a thunderbolt positioning and energy analysis method and system based on a lightning rod monitoring network. The method comprises the following steps: collecting and verifying a lightning current waveform and a microsecond timestamp in real time, and measuring grounding resistance regularly; the terminal carries out filtering analog-to-digital conversion on the signal and extracts characteristic parameters, after packaging, the priority is set according to the current amplitude, and the priority is uploaded to the cloud platform; the cloud platform is associated with multi-terminal synchronous data, when the number of effective terminals is not less than three, coordinates of a thunderbolt point are calculated, integral operation is performed on a lightning current waveform in combination with actually measured grounding resistance to quantify single-time lightning stroke energy, and historical data are analyzed by using a long-short-term memory network model to realize equipment health diagnosis and life prediction. And displaying the thunderbolt point distribution thermodynamic diagram and the state evaluation report through a visual interface. According to the invention, the whole process management from data acquisition to intelligent decision making is realized, and the accuracy and predictability of lightning monitoring and protection are improved.

The invention discloses a deadbeat predictive current control method based on a composite disturbance observer, and belongs to the technical field of dual three-phase permanent magnet motor control. The dual three-phase permanent magnet motor is composed of two sets of stator three-phase windings, and the space phase shift angle is 30 degrees. The method comprises the following steps: establishing a discretized motor model containing total disturbance under a double-dq coordinate system; a composite disturbance observer is designed, and direct current disturbance and alternating current disturbance are synchronously estimated through a second-order disturbance expansion state observer embedded into a generalized integrator; and performing feed-forward compensation by using the disturbance estimation value, and calculating a voltage control quantity in combination with deadbeat prediction. By introducing the second-order disturbance expansion state observer and the generalized integrator, synchronous compensation of direct current disturbance and alternating current disturbance is realized, so that current harmonics are effectively reduced, and the current waveform quality is improved. Meanwhile, complete decoupling of the current control loop and the disturbance suppression loop is realized. In addition, the method still shows high robustness under the condition of motor parameter mismatch.

The invention relates to the technical field of semiconductor device testing, in particular to a GaN device dynamic on-resistance measurement error suppression method and system. The method comprises the following steps: acquiring a break-over voltage waveform, a gate voltage waveform and a drain current waveform of a switching period of the GaN device based on a predetermined test loop; respectively calculating a grid feed-through theoretical error waveform and a parasitic parameter theoretical error waveform based on the grid voltage waveform and the drain current waveform; subtracting the grid feed-through theoretical error waveform and the parasitic parameter theoretical error waveform from the conduction voltage waveform to obtain a preliminary compensation waveform; constructing a voltage waveform hybrid compensation model, and calculating a compensated voltage waveform by using the voltage waveform hybrid compensation model based on the preliminary compensation waveform, the gate voltage waveform, the drain current waveform and the break-over voltage waveform; and calculating on resistance according to the compensated voltage waveform and the drain current waveform. The problem that in the prior art, dynamic on-resistance measurement of a GaN device is not accurate enough is solved.

The invention relates to the technical field of data center computing power and electric power resource cooperative control, in particular to an electric power dynamic monitoring system based on a knowledge graph. Comprising a heterogeneous data spin mapping unit used for collecting current waveform data and voltage data of an intelligent power distribution unit; the topological coupling force field construction unit is used for acquiring physical topological data and logical topological data of the data center and generating a coupling strength matrix defining association weights among nodes; the dynamic potential energy evolution and gradient analysis unit is used for generating a potential energy gradient vector for indicating a regulation and control direction; the potential energy guiding regulation and control decoding unit is used for receiving the potential energy gradient vector; monitoring the modulus length of the potential energy gradient vector; and after the closed loop feedback logic and the hardware control signal are executed, the physical operation states of the intelligent power supply distribution unit and the server calculation unit are changed. According to the method, the mathematical abstraction ability and the quantization accuracy of the stability monitoring of the complex data center system are remarkably improved.

The invention relates to the technical field of power system monitoring and anomaly analysis, and discloses a museum power distribution loop abnormal power consumption mode identification method and system. The method comprises the following steps: acquiring millisecond-level current and voltage original waveforms of each level of power distribution loop of a museum, and extracting a time sequence current sequence containing harmonic distortion rate mutation and leakage current high-frequency pulses; performing exhibition area portrait classification based on the sequence, and determining dominant load type labels of each loop; fusing the load label and the time sequence, and predicting a normal current track of each loop; collecting a latest current waveform in real time, comparing the latest current waveform with the predicted trajectory, and identifying and marking a potential abnormal loop; abnormal source equipment combination judgment and abnormal millisecond-level evolution characteristic analysis are carried out on the abnormal loop; and judging whether to trigger instant early warning or not according to the abnormal evolution characteristics and the equipment combination type. According to the invention, accurate identification and source positioning of abnormal power utilization of the distribution loop of the museum are realized, the false alarm rate is reduced, and the timeliness and reliability of abnormal response are improved.

The invention relates to the technical field of relay protection, in particular to a method for identifying excitation surge current of a transformer sent out by a wind power plant based on differential current waveform characteristics and application of the method. Compared with a traditional second harmonic braking method, the method has the advantages that the time window is short, the magnetizing inrush current of the transformer can be quickly identified, and the protection reliability of the sending-out transformer of the wind power plant is improved. The objective of the invention is to solve the problem of how to reliably identify the magnetizing inrush current fault of the wind power plant transformer.

The invention relates to the technical field of material processing, and discloses a nitrogen content dynamic regulation and control process for variable polarity argon arc welding of high-nitrogen steel, which comprises the following steps: adjusting the proportion of nitrogen in shielding gas in real time based on a detection result of a flowing state of a molten pool; dynamically regulating and controlling the variable polarity switching frequency based on the arc stability detection signal; the gas supply delay time is adjusted based on the welding heat input change condition; and current waveform modulation parameters are synchronously optimized based on the penetration change so as to realize uniform distribution of nitrogen elements. According to the nitrogen content dynamic regulation and control process for variable-polarity argon arc welding of the high-nitrogen steel, the nitrogen element requirements of different areas of a molten pool can be accurately matched, and the problem that the local nitrogen content is too high or too low due to uneven convection of the molten pool is solved; meanwhile, current waveform modulation parameters are optimized in combination with fusion depth changes, the solubility stability of nitrogen elements in key areas such as the root of the weld joint can be ensured, the problems that the nitrogen content distribution is not uniform and the solubility of the root fluctuates are solved on the whole, and the nitrogen content of each area of the weld joint is closer to a design value.

The invention relates to the technical field of industrial safety control, in particular to a dual-system redundancy safety circuit and a self-diagnosis method, the dual-system redundancy safety circuit is composed of a first safety system, a second safety system, a test load and a switching unit, and the first safety system and the second safety system realize information interaction through an optical coupling isolation communication interface. According to the self-diagnosis method, an encrypted diagnosis trigger pulse sequence is generated through the second safety system, a test contactor of the first safety system is driven to be connected to a test load, and a main safety loop generates simulated real safety action current; the second safety system performs high-speed sampling, filtering, correlation analysis and response delay extraction on the current waveform to obtain a diagnosis result of the contact performance and the load capacity; and when an abnormity is detected, the second safety system controls the switching unit to execute safety switching through the solid-state switching output point, so that control right taking-over is realized, and the reliability and the online diagnosis capability of the safety loop are improved.

The application discloses a method and system for optimizing and controlling energy consumption in automobile fastener production, and relates to the technical field of fastener production. The method comprises the following steps: obtaining real-time current waveform signals and power grid fundamental voltage signals of an inverter unit in an energy feedback link, establishing a phase dynamic drift model by using a time difference analysis algorithm, and forming a continuous mapping of energy flow direction changes on a time axis; extracting a continuous change section of an offset rate between the current waveform and the power grid fundamental based on the established phase dynamic drift model, constructing a phase trend prediction function by using a sliding window algorithm, and converting the time characteristics of energy flow direction changes into a phase prediction signal trajectory. The application realizes the synchronization of feedback current and power grid voltage by phase dynamic drift modeling and advance compensation control, reduces ripple current and component stress, extracts energy density change rate and dynamically filters and regulates, makes energy flow smooth and continuous, and realizes efficient and energy-saving control of fastener production.

The application provides a circuit breaker operating coil current characteristic diagnosis and analysis system and method. It belongs to the technical field of power system automation and substation state monitoring. The method comprises the following steps: synchronously recording the current of a plurality of circuit breaker operating coils on the DC feeder line screen side to generate multi-channel synchronous recording wave data; collecting SOE message information at the same time, using the time stamp and action identification information in the SOE message to automatically match and locate the specific action circuit breaker, and generating action circuit breaker positioning data; through real-time collection of the current waveform data of the circuit breaker operating coil and the use of high-precision algorithms for feature extraction and analysis, abnormal fluctuations in current changes can be accurately captured, such as excessive starting current and unstable maintenance current, thereby reducing the risk of circuit breaker misoperation or refusal caused by abnormal current characteristics, avoiding power system accidents caused by equipment failure, and improving the reliability of circuit breaker operation.

A system (100) for identifying electrical load types for a variety of different electrical loads (102, 103, 104), wherein the system comprises: a hierarchical load attribute database (108) comprising a plurality of layers (110), wherein a (112) of the layers contains a plurality of different load categories, wherein a first layer (112, L1) of the plurality of layers contains the different load categories; wherein a second layer (L2) of the plurality of layers contains a plurality of different load subcategories for each of the different load categories; and wherein a third layer (L3) of the plurality of layers contains the different electrical load types for the different load subcategories; and a processor (114) which is constructed (116) to: Acquiring a voltage waveform and a current waveform for a corresponding one of the different electrical loads; Mapping a voltage-current trajectory onto a grid containing a plurality of cells, each of which has a binary value of zero or One is assigned based on whether the voltage-current trajectory passes through each of the cells; Extracting a variety of different properties from the depicted grid of cells as a graphical signature of the corresponding one of the different electrical loads; Deriving a category of the corresponding one of the different electrical loads from the hierarchical load attribute database; and Identifying one of a variety of different electrical load types for the corresponding one of the different electrical loads, where the voltage waveform and the current waveform each represent a total number of K data points of the form (v k , i k ) contained, where: k = 1,...,K; where v k and i k correspondingly, a voltage and a current value of a sampled data point k; where maximum and minimum values ​​of the voltage waveform and the current waveform are calculated from: v max = max v k , V min = min v k , i max = max i k , i min = min i k , v 0 = 1 2 ( v max + v min ) , and i 0 = 1 2 ( i max + i min ) ; where v0 and i0 are both averages of the corresponding maximum and minimum values ​​that form the central points of the grid of cells, where Δ defines a size of the grid; where dv = v max − v 0 Δ di = i max − i 0 Δ ; the processor is further configured to generate two sequences from the voltage waveform and the current waveform as: { v 0 − dv ⋅ Δ , v 0 − dv ⋅ ( Δ − 1 ) , … , v 0 , … , v 0 + dv ⋅ ( Δ − 1 ) , v 0 + dv ⋅ Δ} and { i 0 − di ⋅ Δ , i 0 − di ⋅ ( Δ − 1 ) , … , i 0 , … , i 0 + di ⋅ ( Δ − 1 ) , i 0 + di ⋅ Δ} where each of the two sequences has N = 2Δ+1 elements; where the grid of cells includes a first axis having N cells and a second axis having N cells; and where each of the cells has a position value (v0 + dv · x,i0 + di · y) and a binary model value B x,y is assigned, which is initialized to 0.

The invention relates to the technical field of mining machinery intelligent monitoring, and discloses a remote monitoring system and method based on a crusher. According to the system, an original current waveform and a bearing voiceprint signal in a starting stage are collected through an initial state sensing unit, a current waveform deviation spectrum is generated, sound energy of a specific frequency band is extracted, and an initial state data set is formed through fusion; the dynamic operation analysis unit monitors a power fluctuation period, a torque change slope and a material flow noise spectrum in a steady state, and generates a real-time operation state flow; the self-adaptive regulation and control unit identifies an abnormal correlation mode of power and torque, starts fine adjustment of the feeding speed when the torque slope exceeds a threshold, and dynamically adjusts an instruction according to real-time feedback of noise characteristic frequency band energy. According to the scheme, early diagnosis of hidden faults of the equipment and predictive smooth control of the material blocking risk are realized, and the equipment reliability and the production continuity are improved.

This invention provides a fault early warning method for low-voltage power distribution systems in smart factories, belonging to the field of low-voltage power distribution fault early warning technology. Based on the low-voltage power distribution system topology, it deploys synchronous current and voltage acquisition terminals and ambient temperature sensors to acquire real-time current waveforms, voltage sag events, neutral current values, and ambient temperature for each circuit. The real-time current waveforms are decomposed into harmonic sequences using Fourier transform, generating a harmonic spectrum distribution matrix. A joint probability table of voltage sag and neutral overcurrent events is constructed by correlating timestamps. Combining the harmonic amplitude growth trend with the characteristics of coupled events whose joint occurrence probability exceeds a set threshold, a candidate circuit set for insulation degradation risk is screened, and temperature field inversion calculation is performed to generate a conductor surface temperature rise distribution map. This method can quantify the temporal coupling relationship between the two types of events, narrowing the fault investigation scope, reducing false alarms and missed detections, accurately reflecting the insulation degradation state of the circuits, and achieving accurate fault early warning for low-voltage power distribution systems.

The application discloses an electromagnetic detection optimized bipolar SHMPWM transmitting method, which comprises the following steps: S1, by analyzing the influence of the resistive and inductive load on the transmitting current waveform distortion and the transmitting spectrum energy loss, extending the current waveform based on the equal-area principle, compensating for the lost transmitting current spectrum energy, and calculating the current waveform extension time; S2, considering the inductive load and the dead zone effect, establishing a bipolar SHMPWM nonlinear equation set; S3, using the particle swarm algorithm to iteratively operate the bipolar SHMPWM nonlinear equation set, and obtaining the solving result of the switching angle of the half-cycle symmetric SHMPWM. The application adopts the optimized particle swarm algorithm to solve the equation set to obtain the switching angle, and realizes that the frequency domain information of the half-cycle symmetric SHMPWM frequency focusing waveform conforms to the specific harmonic amplitude set by the expectation.

The invention relates to the technical field of intelligent home regulation and control, and discloses a home equipment regulation and control method combined with whole house intelligent perception. According to the method, multi-mode environment sensing data such as sound waveforms, thermal imaging, illumination intensity distribution and current waveforms are collected in real time through heterogeneous sensor arrays in functional areas of a house; a standardized perception data stream is generated through timestamp alignment and abnormal value identification and replacement; on the basis, a real-time energy consumption portrait containing an equipment operation state matrix, an environment comfort vector and an energy consumption distribution histogram is constructed; comparing the image with a historical reference image, and generating an image deviation matrix containing equipment operation deviation, environment fluctuation and energy efficiency difference characteristics; and optimizing searching in an energy consumption strategy space, and outputting a dynamic regulation and control instruction set comprising equipment start and stop, power regulation and mode switching. According to the method, precise dynamic regulation and control of the home equipment are realized, and the living comfort and the energy utilization efficiency are improved.

The application discloses a PFC circuit and an electric flame stove suitable for direct current and alternating current, comprising a voltage switching control module, a filter module, an inverter voltage boosting module, a full-bridge rectifying module and a power factor correction module. The voltage switching control module detects input voltage and controls the on-off of the filter module and the inverter voltage boosting module respectively, realizing the adaptation of 48V direct current and 220V alternating current voltage input. The power factor correction module adopts a Boost (voltage boosting) type active PFC topology, the high-frequency on-off control of the switching tube Q7 / Q8 is realized through the control chip U2 / U3, the input current waveform follows the input voltage waveform, the power factor is improved to above 0.95, the switching tube Q8 is adopted to replace the diode in the prior art, there is no voltage and current loss when the switching tube is turned on, the stable current and voltage output are ensured, the voltage / current waveform is consistent, and the power factor is improved.

This technology provides a mechanism for monitoring power systems and outputting a predetermined value if an abnormality occurs within the power system. [Solution] The monitoring device 2 includes, as its function, an acquisition unit 231 that acquires waveform data from an oscilloscope device 3 that acquires and outputs waveform data of voltage and current of the power system; an inference unit 232 that uses the waveform data acquired by the acquisition unit 231 as input and makes inferences as to whether the operation within the power system is normal, based on a learning model 223 that uses past waveform data and operation status data at the date and time indicated by the time axis of the past waveform data as training data; a determination result output unit 233 that outputs result data indicating that an abnormality has occurred in the power system if the inference result is that an abnormality has occurred in the power system; and a related data output unit 234 that outputs predetermined related data related to the power system based on the inference result.

The invention provides a non-contact power supply-based magnetic suspension rotor wireless energy transmission method and system, and relates to the technical field of non-contact power supply, and the method comprises the steps: carrying out the motion state vector reconstruction of a magnetic suspension rotor, and outputting a pose priority weight vector; setting a data acquisition scheduling strategy; receiving a six-degree-of-freedom native state set; after load impedance transient response data are received, the real-time pose of the rotor is reconstructed and output; fitting the instantaneous optimal frequency and the current waveform phase compensation amount of the resonant cavity; loading to an adaptive power mapping model, and predicting a power demand change trend; and dynamically tuning output parameters of the high-frequency inverter, and performing coupling efficiency offset compensation. The technical problem that the performance of a whole magnetic suspension system is affected due to the fact that a wireless energy transmission method in the prior art depends on static frequency and current waveform setting and is difficult to adapt to the rapidly changing motion state and load requirement of a magnetic suspension rotor in real time is solved.

The invention discloses a driving circuit and a driving device of a transistor. The driving circuit of the transistor at least comprises a first driving unit and a first voltage holding unit, the first driving unit comprises a first end and a second end; the first end is electrically connected with a driving signal end, and the second end is electrically connected with one end of the first voltage holding unit; the other end of the first voltage holding unit is electrically connected with the control electrode of the transistor; wherein the first driving unit provides a first driving signal for the control electrode through the first voltage holding unit for the first time, so that the transistor is in a conducting state; after the transistor is switched from the on state to the off state, the first voltage holding unit is used for controlling the second end to be maintained at the first holding voltage. According to the technical scheme, the current waveform of the control electrode of the transistor can be optimized, and current and voltage oscillation generated in the conduction process of the transistor is reduced.

This invention discloses an AC circuit breaker control method and device, relating to the field of circuit breaker control technology. The method includes the following steps: acquiring the target waveform sequence of the target AC circuit and obtaining the fundamental and higher harmonic components through frequency domain decomposition to extract current waveform features; constructing a zero-crossing prediction model based on the current waveform features, and dynamically correcting the prediction model by combining the higher harmonic components and load asymmetry characteristics to generate a candidate interval for the initial breaking time; determining the final breaking time by combining the instantaneous power direction reversal point and the arc sustaining energy threshold; triggering the circuit breaker operation at the final breaking time, and dynamically adjusting the contact separation speed based on the residual arc energy until the arc energy decays to a safe value. This invention solves the problems of arc extension and equipment damage in traditional circuit breakers under harmonic distortion or sudden disturbances by extracting current waveform features to construct a zero-crossing prediction model and dynamically correcting the contact separation strategy.

The invention discloses a non-contact real-time current monitoring device, which comprises a magnetic field induction sub-device and an analog signal processing sub-device, and is characterized in that the signal output end of the magnetic field induction sub-device is electrically connected with the signal input end of the analog signal processing sub-device; the analog signal processing sub-device comprises an impedance matching sub-module, a passive RC pre-compensation sub-module and an active integration sub-module which are cascaded in sequence; the impedance matching sub-module comprises an input matching resistor and an output matching resistor; the passive RC pre-compensation sub-module comprises a resistor and a capacitor, the resistor and the capacitor form an RC loop, and the passive RC pre-compensation sub-module is cascaded between the impedance matching sub-module and the active integration sub-module; the active integration sub-module comprises an operational amplifier, an input resistor, an integration capacitor and a feedback resistor. The device provided by the invention can directly output an analog voltage signal which is homologous with a measured current waveform through an exquisite collaborative design.

The invention relates to the technical field of motor control, and discloses an anti-locked-rotor starting control system. The system comprises a main control module, a dynamic rule base generation module, a phase compensation module, a pre-triggering module and a feedback correction module. The main control module monitors a three-phase current waveform and a rotor position signal of the motor and generates an instantaneous locked-rotor feature vector; the dynamic rule base generation module extracts a current waveform distortion mode of a historical locked-rotor event, and combines a rotor inertia parameter to construct a fuzzy rule set so as to initialize a dynamic rule base; the phase compensation module dynamically compensates the phase current waveform and constructs a stability evaluation function; the pre-triggering module triggers pre-access of the standby power supply according to the phase offset and verifies compatibility; and the feedback correction module generates a feedback parameter according to the locked-rotor risk index and the power supply verification result, and corrects the mapping relationship between the feature vector and the rule base. The system can accurately identify locked-rotor characteristics, dynamically adapt to operation parameters, actively prevent and control locked-rotor risks, and improve the starting stability of the motor.