98104 results about "Electric machine" patented technology

The invention relates to an intelligent monitoring alarm method and system for a motor controller, and the method comprises the steps: obtaining an internal circuit signal and a body vibration signal of the motor controller, carrying out the combined noise analysis, and generating a dynamic noise baseline; performing component fault identification based on the dynamic noise baseline and the internal circuit signal to obtain a fault precursor current feature; performing component impact response separation based on the dynamic noise baseline and the body vibration signal to obtain hidden fault vibration characteristics; performing component association mapping on the fault precursor current feature and the hidden fault vibration feature to obtain an internal fault component identifier; and performing alarm analysis based on the fault component identifier, the fault precursor current feature and the hidden fault vibration feature to obtain a graded alarm decision. According to the invention, early fault features can be captured more sensitively, and false alarms and missing alarms are reduced.

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

The invention discloses an inverter intelligent control method based on a self-adaptive algorithm, and relates to the technical field of inverter intelligent control, and the method comprises the steps: multi-source temperature collection and environment recognition, machine learning-based electric-thermal coupling prediction, self-adaptive inverter parameter optimization, and cooperative thermal management and fault diagnosis self-repairing. According to the high-temperature or low-temperature failure risk of the motor and the inverter under the extreme climate, temperature distribution and load information are obtained in real time, the temperature rise trend is predicted in advance, and the current, voltage and modulation strategy of the inverter are actively adjusted, so that safe derating or torque compensation is achieved; multi-sensor cross validation and observer fusion are carried out when sensors drift or devices are aged, stable operation and efficient energy utilization of the system are kept, and the drivability and the whole vehicle reliability in an extreme environment are remarkably improved; in the process, fault diagnosis and self-repairing can be further improved through online model updating, and the durability and economical efficiency of the electric drive system are improved.

The invention discloses a servo motor dynamic overload detection and protection method based on a heat accumulation model, which relates to the technical field of servo system fault protection application, and comprises the steps of constructing a heat accumulation equivalent model, dynamically detecting an overload state, executing a heat dissipation recovery strategy, implementing a multi-stage protection mechanism, self-adaptive environment compensation and a historical data learning function. Through discretization processing of overload curve data and a nonlinear acceleration calculation strategy, the problems of protection lag and false triggering caused by traditional single-parameter detection are avoided, it is ensured that the motor can respond in time in light load, heavy load and load fluctuation scenes, the burn-out risk of the motor is reduced, and through integration of an environment temperature sensor and a heat dissipation condition evaluation unit, the reliability of the motor is improved. The heat accumulation coefficient and the heat dissipation attenuation parameter are dynamically adjusted, the problem of model deviation caused by environment interference is solved, when heat dissipation deterioration and temperature feedback abnormity are detected, the heat dissipation recovery period is automatically prolonged, calculation logic is corrected, and the continuous operation reliability of the system is improved.

The invention provides a test method and device for a motor active short-circuit relay, and a storage medium. The method includes the steps: performing the zero speed detection of a motor after a motor controller completes a low-voltage power-on operation, wherein when the motor controller is powered down, a first relay and a second relay are both switched on; controlling the second relay to be turned on if the motor passes the zero speed detection, and injecting a first excitation signal at the control ends of a first phase winding and a third phase winding through the motor controller; performing injection detection of the first excitation signal to determine whether the first excitation signal is successfully injected or not; controlling the first relay to be turned on if the first excitation signal is successfully injected, and obtaining a voltage across two ends of the first relay; and judging whether the power-on test of the first relay is successful or not according to the voltage across two ends of the first relay. The method can realize the turn-on test of the short-circuit relay, and ensures the reliability of the active short-circuit function of the vehicle motor duringdriving.

The invention provides a permanent magnet motor and a scroll inverter compressor, and relates to the technical field of scroll compressor design and manufacturing, and the permanent magnet motor comprises a stator iron core and a rotor iron core; the stator core comprises stator teeth and a stator yoke which are uniformly distributed along the circumference, fluid through grooves are formed in the outer side of the stator yoke at the tops of the stator teeth, stator grooves are formed in two adjacent stator teeth and the stator yoke between the two stator teeth, and a plurality of strands of conductive circular enameled wires are embedded in each stator groove; the outer side of the rotor core is composed of linear segments and arcs, air grooves which are evenly distributed are formed in the rotor core, non-uniform magnetic isolation bridges are formed between the air grooves and the linear segments on the outer side of the rotor core, a certain distance is formed between every two adjacent air grooves, parallel magnetic conductive ribs are formed, and permanent magnets with the magnetic field directions changing alternately are embedded in the air grooves. A rivet hole, a lightening hole and a shaft hole are arranged close to the inner side of the rotor core. Therefore, the defined proportionality coefficient Ks is kept in a reasonable range, the power density of the motor can be increased, the cost is reduced, and the efficiency is improved.

The invention relates to the technical field of equipment testing, and discloses a motor operation state vibration noise combined diagnosis generation method, which comprises the following steps: when a motor operates, performing bimodal data extraction on operation state data to obtain a vibration signal and a noise signal; performing order tracking analysis on the vibration signal to obtain an electric vibration characteristic order component; calculating a time domain energy envelope line, and performing synchronous time domain segmentation on the noise signal to obtain noise signal slices; filtering non-related components of the vibration characteristic order component in the noise signal slice, and extracting a vibration synchronous noise component of the vibration characteristic order component synchronous with the current rotation period of the motor according to a filtered result; constructing a sound-vibration fusion spectrum; analyzing the distribution rule of the sound and vibration intensity in the sound and vibration fusion spectrum, identifying a correlation mutation point, and diagnosing a specific operation state fault based on the distribution mode of the correlation mutation point; according to the invention, the efficiency of vibration noise combined diagnosis generation of the motor operation state can be improved.

The invention relates to the field of industrial production, and discloses a predictive maintenance system for an ultra-efficient explosion-proof motor based on digital twinning, which comprises the following steps: when key operation parameters of the motor deviate from a normal working condition interval, judging whether the key operation parameters reach a digital twinning model activation threshold value or not; based on historical operation data, sensor real-time data and environmental factors, a digital twin model is called to construct virtual mapping of motor operation, a current state evolution trajectory is generated, and whether the operation trend has a fault or not is predicted; the state track change mode is matched with a historical fault library, and whether a potential fault path exists or not is evaluated; according to the fault risk level and the predicted occurrence time, in combination with the current production plan and the equipment health tolerance, whether an advanced intervention measure needs to be taken is judged; and generating an intervention scheme according to state regulation and control parameters fed back by the digital twinning model in combination with specific working conditions. The method has the advantage that the operation safety and the maintenance efficiency are improved.

The invention discloses a variable air gap domain-based permanent magnet motor topology hierarchy optimization design method and a motor, and the method comprises the steps: firstly determining an electromagnetic performance layer optimization target, constructing a geometric parameter model, carrying out the dimensionality reduction of a high-dimensional parameter, and constructing a first hierarchy optimization sub-model I; performing geometric parameter optimization on the stator and rotor basic domain by combining a multi-objective optimization algorithm to obtain an optimized motor I; analyzing and optimizing the characteristic electromagnetic force of the motor I under different working conditions to serve as a second-level optimization target, constructing a second-level optimization sub-model II, performing small-scale online topological optimization in combination with a multi-target genetic algorithm, performing secondary design on a motor air gap design domain, obtaining a sample data set, constructing a parallel agent model, and constructing a second-level optimization sub-model II; then large-scale off-line topological optimization is carried out, and remodeling of a motor air gap design domain is achieved; and performing simulation evaluation on the final optimized motor. According to the method, on the premise that the vehicle permanent magnet driving electromagnetic performance is kept, electromagnetic vibration noise under multiple working conditions is suppressed, and meanwhile optimization efficiency is remarkably improved.

The invention discloses a motor control method and device based on an encoder, a medium and a program product, and relates to the field of motor control, and the method comprises the steps: receiving a position signal and a speed signal outputted by the encoder, and carrying out the filtering processing to obtain an operation state parameter; collecting mechanical vibration and electromagnetic noise generated in the operation process of the motor to obtain acoustic parameters of the motor, and extracting frequency characteristic parameters representing the rotating speed and motion characteristics of the motor; performing data fusion on the operation state parameters and the frequency characteristic parameters according to a preset weight to generate an operation state model; the operation state model is compared with a standard motion trail, and the position deviation value and the speed deviation value of the actual motion trail of the motor are calculated; and calculating a compensation control quantity according to the position deviation value and the speed deviation value, converting the compensation control quantity into a driving signal and outputting the driving signal to a motor driver so as to drive a motor to perform operation adjustment. According to the invention, the control precision of the motor in actual operation can be improved.

The invention relates to an axial magnetic field motor rotor assembly fault detection method and system, and the method comprises the steps: collecting vibration waveform data, temperature gradient distribution data and magnetic field intensity distribution data of a rotor assembly in an operation state, and constructing a dynamic monitoring data set; performing dynamic feature extraction on the data in the dynamic monitoring data set to generate a dynamic operation feature set comprising a vibration coupling feature, a temperature abnormal fluctuation feature and a magnetic field offset feature, and performing multi-dimensional correlation mapping processing based on the dynamic operation feature set to generate a comprehensive abnormal index set; according to a matching result between the comprehensive abnormal index set and a preset fault judgment threshold value, determining a fault type set of the target rotor assembly and a corresponding fault confidence score; according to the fault type set of the rotor assembly and the corresponding fault confidence score, a visual detection report is generated, the visual detection report is used for displaying a fault result at a terminal, and accurate detection and visual presentation of the fault of the rotor assembly are achieved.

Systems and methods for providing hemodynamic support to a patient with an intravascular blood pump are disclosed. In some implementations, the blood pump includes a motor and an improved motor cable for delivering electrical power to the motor. The motor includes a stator with one or more coils. The motor cable includes one or more electrical conduits. The motor cable also includes a tail portion and a head portion. In some implementations, the head portion may have an O-shape or a C-shape. The motor cable may reduce the complexity of assembling the blood pump. For example, the motor cable may reduce the risk of shorting the one or more coils and / or the one or more electrical conduits.

The invention relates to a dual three-phase permanent magnet synchronous generator rectification system and a direct current voltage stabilization control method thereof. Comprising a dual three-phase permanent magnet synchronous generator, a VSD decoupling converter, a load current observer, a dynamic load feed-forward compensator, a voltage closed-loop controller, a dead-beat predictive current controller, a maximum four-vector SVPWM modulation module and a six-phase rectifier. The double-three-phase topological structure adopted by the invention has the advantages of multiple control degrees of freedom, high reliability and the like. A dynamic load feed-forward compensator is constructed to perform dynamic feed-forward compensation on quadrature-axis current of the motor, so that the recovery time of bus voltage is shortened, and the voltage fluctuation amplitude is reduced; the designed dead-beat predictive current controller optimizes the dynamic characteristics of a current loop, improves the torque tracking performance of the motor, and further improves the voltage stabilization regulation capability of the system. The designed load current observer realizes the analysis redundancy of current detection and improves the reliability of the system.

A drink maker is provided for motor detection. The drink maker includes a mixing vessel configured to receive a drink product. The drink maker also includes a dasher, driven by a drive motor, configured to mix the drink product within the mixing vessel. The drink maker also includes a cooling circuit, including a compressor, configured to cool the drink product. The drink maker further includes a motor condition sensor configured to detect a motor condition associated with the drive motor and output motor condition signals. The drink maker further includes a controller configured to determine, based on one or more first motor condition signals of the periodic motor condition signals, whether a value of the motor condition satisfies a first motor condition threshold. The controller is further configured to, in response to determining that the value of the motor condition satisfies the first motor condition threshold, turn off the compressor.

The invention relates to the field of motor health management and predictive maintenance, in particular to a motor stator winding insulation state evaluation method and system based on a digital model. Comprising the following steps: S1, collecting high frequency of a motor stator winding, and generating multi-physical-quantity real-time data; s2, calculating a dynamic capacitance reference value according to real-time data of multiple physical quantities; s3, performing subtraction operation on the high-frequency equivalent capacitance measurement value and the dynamic capacitance reference value, and extracting an insulation degradation residual signal; s4, constructing a self-adaptive dynamic detection threshold according to multi-physical-quantity real-time data; s5, judging whether the absolute value of the insulation degradation residual signal is greater than a self-adaptive dynamic detection threshold or not: if so, judging that an insulation degradation event occurs; if not, judging that the operation state is a normal operation state; and S6, in response to the insulation degradation event, updating the insulation degradation index, and generating insulation state evaluation based on the updated insulation degradation index. According to the invention, false alarm under severe load fluctuation is avoided, and the accuracy and reliability of evaluation are significantly improved.

The invention discloses a laser scanning detection method for gear tooth form errors of gear motors, and belongs to the technical field of industrial optical detection. The method comprises the following steps of: firstly, comprehensively acquiring high-density three-dimensional point cloud data of a pinwheel tooth profile by combining laser scanning and precise rotating motion; secondly, preprocessing the original point cloud, and performing high-precision automatic registration on the actually measured point cloud and the standard three-dimensional CAD theoretical model by using algorithms such as an iterative nearest point; and finally, generating a visual tooth profile error map by calculating the normal deviation between the measured data and the theoretical model point by point, and quantitatively evaluating error parameters. According to the scheme, high-efficiency, high-precision and all-shape nondestructive testing of the gear tooth error is realized, physical contact damage is avoided, and the quality control level and the production efficiency of the core part of the speed reducer are remarkably improved.

There is provided an intravascular blood pump for insertion into a patient's heart. The blood pump comprises a slotless permanent magnet motor contained within a housing, the motor having p magnet pole pairs and n phases, where p is an integer greater than zero, and n is an integer ≥3. The motor comprises a stator extending along a longitudinal axis of the housing and having 2np coils wound to form two coils per phase per magnet pole pair. The stator comprises inner and outer windings each comprising np coils electrically connected such that the current flowing through the coils is in the same direction, the coils of the outer winding arranged on an outer surface of the coils of the inner winding.

The invention relates to a dynamic precision compensation control method based on an intelligent PCB drilling machine, and the method comprises the steps: collecting a dynamic parameter set in real time through a multi-source sensor group disposed on a drilling main shaft, the dynamic parameter set comprises displacement deviation caused by axial deformation of a main shaft, thermal deformation analyzed based on interlayer temperature gradient and frequency spectrum characteristics reflecting tool-material coupling vibration, and according to the multi-dimensional compensation vector and current drilling process parameters, a space trajectory correction instruction and a motion parameter optimization instruction are dynamically synthesized, so that the dynamic parameter set is obtained. Wherein the trajectory correction instruction reconstructs a real-time interpolation path through a B-spline curve, the motion controller receives a space trajectory correction instruction and a motion parameter optimization instruction, at least three times of compensation iteration are completed in a single drilling period, a linear motor and a spindle motor are driven to execute online precision compensation, and the execution delay of the compensation instruction is smaller than 2 ms.

The invention relates to the technical field of motor testing, in particular to an online monitoring method and system for the health state of a carbon brush of a motor, and the method comprises the steps: determining a target operation load environment cluster of a target carbon brush at the current moment according to the pre-obtained load condition and operation environment condition of the target carbon brush in the current operation time period; screening out a reference operation time period; determining an abnormal loss factor and a potential abnormal wear feature vector of the target carbon brush at the current moment; according to the Lyapunov index of the vibration signal of the target carbon brush in the current operation time period and the temperature change and the current change of the target carbon brush in the current operation time period, determining a wear fault display possible feature vector; therefore, the health state of the target carbon brush at the current moment is determined. According to the invention, the potential abnormal wear condition of the target carbon brush at the current moment is considered, the health state of the carbon brush is monitored, and the timeliness of abnormal health state monitoring of the carbon brush is improved.

The invention relates to a multi-parameter fusion motor performance evaluation method, equipment and a medium. The method comprises the following steps: firstly, acquiring electrical signals, mechanical vibration signals and thermal temperature data in operation of a motor, and performing preprocessing and standardization to form a first data set; secondly, dimension reduction is carried out on multi-dimensional parameters of the first data set, and core parameter combinations are extracted to generate a second feature data set; then, classifying and marking the second feature data set by utilizing a classification algorithm, and determining a key performance index distribution interval to obtain a third classification result set; and finally, constructing a time sequence anomaly detection model based on the third classification result set, analyzing an index change trend, identifying an abnormal point deviating from a preset threshold value, and generating a fourth anomaly detection result. According to the method, the data quality and consistency can be improved, the abnormal state in motor operation can be effectively identified, data support is provided for motor performance evaluation and fault early warning, and the method is suitable for real-time monitoring and operation optimization of a motor system.

The invention provides a cooling structure of a motor stator, an oil-cooled motor and a vehicle, and belongs to the technical field of automobiles. A guide oil duct and a stepped oil injection duct are arranged on a stator core; the middle of the stator iron core is provided with an oil inlet groove surrounding the stator iron core in the circumferential direction, and a cooling medium enters the flow guide oil channel through the oil inlet groove in the middle of the stator iron core and obliquely injects oil to the stator windings at the two ends of the stator iron core through the stepped oil injection channel. According to the invention, the oil path is directly arranged on the stator core and the stepped oil injection channels are symmetrically arranged, and the cooling medium can be intensively and obliquely sprayed to the surface of the stator winding through the stepped oil injection channels, so that the heat dissipation effect and the heat dissipation efficiency are improved, and the thermal load capacity of the motor and the working efficiency of the motor are further improved; and faults of the motor caused by non-uniform cooling, overhigh local temperature rise and temperature gradient are reduced. The structure is simple, and the overall manufacturing and maintenance cost is reduced; meanwhile, the overall size of the motor is reduced, and overall light weight is facilitated.

The invention provides an anomaly detection method and system based on motor operation vibration sound, and relates to the technical field of motors, and the method comprises the steps: obtaining an original motor signal, determining the amplitude of the original motor signal, and marking an abnormal signal therein; determining spectrum distribution characteristics of vibration signals in the abnormal signals, performing multi-scale decomposition on the vibration signals to obtain a plurality of sub-band signals, and integrating the sub-band signals to obtain a multi-band combined signal; separating the multi-band combined signal into a plurality of intrinsic mode components by adopting a variational mode decomposition algorithm, and integrating the intrinsic mode components to obtain a reconstructed signal; performing time domain analysis and frequency domain analysis on the reconstructed signal to obtain frequency domain distribution characteristics; and inputting the frequency domain distribution characteristics into a trained motor anomaly detection model to obtain an anomaly detection result. According to the invention, the multi-dimensional abnormal features in the motor operation process can be effectively extracted, and the accuracy and reliability of abnormal detection are improved.

The invention belongs to the field of driving circuits of gallium nitride (GaN) power devices in motor driving or power electronic conversion, and discloses a design method of a three-level active driving circuit for restraining bridge arm crosstalk of a GaN device, and the method comprises the steps that a circuit is connected in a bridge type topological structure, and the bridge type topological structure comprises an upper bridge arm and a lower bridge arm which are the same in structure; the upper bridge arm and the lower bridge arm are both divided into two parts, namely a traditional driving circuit and an auxiliary circuit, and the auxiliary circuit is divided into a negative voltage self-recovery circuit and a crosstalk suppression circuit. According to the invention, a negative voltage self-recovery circuit and a crosstalk suppression circuit are formed by using the output and reverse conduction characteristics of the charge pump and the auxiliary GaN device. The advantages of the two methods are combined, the defects of a traditional method are effectively overcome, the turn-off speed is increased, the turn-off loss is reduced, and the positive and negative crosstalk is reduced while the turn-on speed is hardly influenced and the reverse turn-on loss is not additionally increased. The overall design is flexible, efficient and reliable.

The invention relates to the technical field of data processing, in particular to a motor performance monitoring data processing system which comprises a signal registration module, a rhythm judgment module, a trend lag module, an effect recognition module and a label scheduling module. According to the method, the waveband gravity center is established by identifying extreme points, trend comparison is performed, a gravity center alignment structure between different channels is constructed, the time period rhythm stability is judged based on the sampling interval change trend, abnormal paragraphs are marked, and the response lag time period is positioned in combination with the rotation speed slope change and the current fluctuation behavior. And detecting the sequence and direction relationship of a plurality of parameter fluctuation frames, identifying the dense segments which alternately act to construct a label labeling index, and adjusting the state output sequence according to the occurrence frequency of different labels in a continuous time period, thereby realizing the identification and dynamic sorting scheduling of the response structure relationship among different time sequence behaviors. And the time sequence consistency identification capability and the parameter linkage structure expression capability of the monitoring data in the continuous abnormal state are improved.

System and method embodiments are described for solar panel protection against severe environmental impacts. A tracker controller may be configured to rotate a solar tracker comprising a group of solar panels to a safe position to diminish hail impact during a hailstorm. Such a rotation may be implemented using one or more motors to drive arc gears coupled to a pair of supporting purlins that support the group of solar panels. The tracker may comprise a bumper rail placed on the top when the tracker is at the safe position for hail impact absorption. Implementing solar panel protection provides a practical solution to protect solar panels from damage. Thus, the need for costly repair or replacement may be avoided, minimized, or decreased. As a result, the economic efficiency of solar power plant operations may be improved significantly.

The invention relates to the technical field of motor detection, and discloses a motor instantaneous torque measurement method and system based on a high-bandwidth sensor, and the method comprises the steps: synchronously collecting a torque signal and a multi-source interference variable through the high-bandwidth sensor, and forming an original torque sequence after time synchronization superposition; extracting disturbance frequency characteristics through multi-scale wavelet transform and spectral analysis; a pre-trained adaptive filter model is utilized to generate a filter coefficient matched with the working condition, and primary filtering is completed; residual fluctuation is suppressed in combination with Kalman state estimation, and an optimized torque estimation value is obtained; parameter self-adaptive compensation is realized through online calibration weight updating, and a stable torque measurement sequence is output; load abrupt change pre-judgment and threshold value dynamic updating are achieved based on time-frequency correlation analysis, and finally rapid measurement convergence after working condition abrupt change is ensured through a closed-loop reset mechanism. According to the method, the problem of low instantaneous torque measurement precision in the prior art can be solved.

The invention relates to a robot perception decision execution system and method, electronic equipment, a storage medium and a computer program product, and the system comprises a perception module which is used for converting task description information and environment detection information into semantic implicit vectors through a preset visual language environment model; the decision-making module is used for fusing the semantic implicit vector, the noise action sequence and the feedback information through a diffusion model running at a time step length and then carrying out iteration denoising for multiple times to generate a target action sequence; the execution module is used for converting the target action sequence into a motor driving signal through a motion strategy model to drive a motor of the robot, perception analysis under a complex environment and a complex language environment is achieved through a perception-decision-execution framework and a visual language environment model, and the motion strategy model can be used for realizing the perception analysis under the complex environment and the complex language environment through a self-adaptive feedback mechanism. The feedback information is utilized to guide the sampling process of the diffusion model, the convergence speed of the diffusion model is accelerated, and the efficiency and the performability of action planning are improved.

The invention discloses an axial flux motor temperature prediction method based on equivalent thermal circuit method calculation, and the method comprises the following steps: 1, motor thermal circuit unit division: decomposing a motor into a stator unit, a rotor unit, an air gap unit and a housing unit, and constructing an equivalent thermal network through a node-branch method; 2, calculating a multi-physics coupling heat source; 3, thermal resistance parameter dynamic calculation and CFD coupling optimization: calculating conduction thermal resistance, convection thermal resistance and contact thermal resistance; and 4, parameter self-calibration based on machine learning: constructing a PINN model according to a physical law and known physical parameters, introducing a Bayesian optimization algorithm on the basis of the PINN model, adjusting and optimizing the parameters of the PINN model by using Bayesian optimization, designing a reinforcement learning algorithm, and carrying out self-calibration on the parameters of the PINN model. Enabling the reinforcement learning algorithm to dynamically adjust parameters according to the real-time operation data of the system and the prediction result of the PINN model; 5, constructing and solving a heat balance equation; and step 6, visualizing and verifying the temperature field.

The invention is suitable for the technical field of fault detection, and provides a fault detection method and device for a joint module and electronic equipment. The joint module comprises a motor, a speed reducer connected with the motor, a first encoder arranged between the motor and the speed reducer, and a second encoder arranged at the output end of the speed reducer. The fault detection method comprises the following steps: identifying a position difference between a rotor of the motor and an output shaft of the speed reducer based on the first encoder and the second encoder; and according to the position difference and a preset difference threshold value, whether the joint module has a fault or not is determined, and the difference threshold value is associated with the gear meshing clearance of the speed reducer. According to the embodiment of the invention, whether the joint module has a fault or not can be accurately detected.

The invention relates to the technical field of motor control, and discloses a permanent magnet synchronous motor control system and method for an electric drive hydraulic source, and the system comprises a data collection module which is used for collecting the state parameters of the electric drive hydraulic source and the operation data of a permanent magnet synchronous motor in real time through multiple sensors; the sensor redundancy and fault-tolerant module is used for performing parallel sampling through hardware dual-redundancy configuration and dual sensors; the self-adaptive fuzzy logic control module is used for dynamically adjusting a rotating speed instruction and a torque instruction of the permanent magnet synchronous motor based on the collected state parameters; a data driving optimization module; and a digital twinning prediction maintenance module. A self-adaptive fuzzy logic control module is used for dynamically generating a motor rotating speed and torque instruction based on parameters such as real-time pressure, flow deviation and change rate, a fuzzy logic algorithm is used for processing a nonlinear time-varying load and quick response, a self-adaptive fuzzy logic control rule weight and a power conversion circuit parameter are optimized through a reinforcement learning algorithm, and the control precision is improved. And dynamic self-optimization of permanent magnet synchronous motor control is realized.