404 results about "Impedance control" patented technology

The invention discloses an upper limb exoskeleton rehabilitation robot control system and method, and relates to the technical field of rehabilitation robot upper limb control, and the method comprises the steps: collecting multi-modal data such as multi-channel myoelectricity, joint angles, angular velocity and interactive torque; constructing a sliding window feature vector, predicting a next joint angle increment through TCN and Bi-LSTM deep networks, and outputting intention confidence; and based on the confidence coefficient and the muscle fatigue factor, dynamically adjusting an impedance parameter, and combining an impedance control model to generate a power-assisted torque in real time so as to realize power-assisted torque output. By introducing an impedance adjustment mechanism of multi-modal perception, deep time sequence learning and myoelectricity driving, the bottleneck of a traditional upper limb rehabilitation robot in the aspects of intention prediction, parameter adjustment and training individuation is broken through, and the accuracy, safety and active participation degree in the rehabilitation training process are remarkably improved; wide clinical application prospects and industrial transformation values are realized.

The invention discloses a robot control system and method based on vision and force sense fusion and a robot, and relates to the technical field of robots. The robot control system based on vision and force sense fusion and the control method thereof analyze visual features in real time through an artificial intelligence processing unit to predict mechanical parameters; and the self-adaptive impedance control unit is combined to dynamically fuse a position instruction and force sense feedback, so that precise adaptation of target object characteristics and compliant regulation and control of an interaction process are realized, real-time sensing and dynamic adjustment capabilities are achieved, assembly damage caused by mechanical mismatching is effectively avoided, and the reliability and efficiency of precise assembly are improved.

The invention provides a robot skill learning and control method and device oriented to rich contact operation tasks. The method provided by the invention comprises the following steps: collecting human demonstration data; the human demonstration data at least comprises end effector pose data and stiffness matrix data; on the basis of the end effector pose data and the stiffness matrix data, a generalization motion track and a generalization stiffness track are obtained through time alignment, probability distribution modeling and new state constraint adaptation; constructing an obstacle model through environmental perception, taking the generalized motion trajectory and the generalized rigidity trajectory as reference sampling candidate trajectories, screening a collision-free trajectory in combination with motion consistency, rigidity consistency and smoothness cost, and performing iterative optimization to obtain an optimized motion trajectory and an optimized rigidity trajectory; and converting the optimized motion track and the optimized rigidity track into a robot joint torque instruction based on variable impedance control, and controlling the robot to execute a rich contact operation task based on the robot joint torque instruction.

The invention relates to a robot dynamic grabbing control method based on visual sense and tactile sense depth fusion. The method comprises the following steps that firstly, based on visual information, surface geometric features of a target object are extracted, grabbing adaptability scores are calculated, an optimal grabbing point is selected, and a collision-free approaching track is planned; secondly, in a contact establishment stage, detecting a contact event through a touch sensor, fusing vision and touch data to unify a coordinate system, calculating a vision-touch consistency score, and applying an initial grabbing force; and thirdly, in the stable holding stage, slip detection is conducted through wavelet packet energy entropy and pressure gradient, and the grabbing force and impedance parameters are dynamically adjusted in combination with self-adaptive impedance control. According to the method, intelligent control over the whole process from approaching to contact to stable holding is achieved, and the adaptability, stability and safety of robot grabbing in the dynamic environment are improved.

The invention discloses a traditional Chinese medicine internal medicine deficiency syndrome conditioning effect evaluation method and system based on a wearable device, and relates to the technical field of traditional Chinese medicine clinical informationization, and the method comprises the following steps: S1, building an electrode skin complex impedance time-frequency fingerprint, executing full-band sweep frequency perturbation, collecting complex impedance data in a continuous monitoring period, and carrying out the detection of the complex impedance time-frequency fingerprint; extracting resonance peak group and sideband coupling path information, and generating a self-excitation risk spectrum as a response reconstruction reference; and S2, performing anti-fact playback based on the self-excitation risk spectrum, replaying the conductance response in a non-resonance interval, comparing a stripping environment drift signal with contact pressure noise through the risk spectrum, and extracting purified anchor point data as an interface feature calibration reference. Abnormal signal recognition and positioning are achieved through complex impedance time-frequency fingerprints, self-excitation risk spectrums, anti-fact playback and micro-capacitance imaging, interference field regulation and control and self-adaptive impedance control are combined, the accuracy and stability of traditional Chinese medicine deficiency syndrome conditioning evaluation are improved, and the method has the high anti-interference capacity and the intelligent characteristic.

The invention discloses a space manipulator impedance control method based on joint hysteresis dynamic position compensation, and belongs to the field of space robot nonlinear dynamics control. The control method comprises the following steps: constructing a flexible joint space manipulator model based on a standard dynamic model of the space manipulator; according to the flexible joint space manipulator model, a virtual torque sensing strategy is designed based on motor side sensor information, and a joint torsion torque estimated value is obtained; building a joint hysteresis model based on a Bi-LSTM mixed hysteresis modeling method fusing multi-scale memory and an attention mechanism, and training the joint hysteresis model; inputting a joint torsion moment estimation value into the trained joint hysteresis model, and estimating a joint torsion angle; based on the estimated joint torsion angle, the joint angle measured by the motor side encoder is subjected to superposition correction, and track error compensation caused by joint hysteresis is achieved.

The invention discloses a glass bottle grabbing method and system based on visual inspection, and the method comprises the steps: carrying out the real-time recognition of a bottle opening, a bottle body contour and defect features through an image recognition algorithm, and outputting a detection data set containing the precise three-dimensional pose and feature identification of a glass bottle; based on the detection data set, generating an action parameter set containing the expansion and contraction amount, the rotation angle and the grabbing time sequence; according to the action parameter set, the movable guide rail is controlled to slide to a target area along the fixed guide rail, and self-adaptive adjustment of grabbing force is achieved through an impedance control algorithm; and after grabbing is completed, the conveying path is dynamically corrected through a model prediction control algorithm in combination with the real-time movement speed of the conveying belt, the conveying belt is accurately placed on a preset detection station, and a closed-loop grabbing-conveying process is formed. By utilizing the embodiment of the invention, high-precision identification, dynamic task allocation and self-adaptive flexible grabbing of the glass bottle can be realized, and the grabbing success rate and the production efficiency are improved.

The invention provides an exoskeleton man-machine motion intention cooperative control method and device and a storage medium, and relates to the technical field of robot motion control signal processing. According to the method, signal phase differences are acquired through energy buttons at human joints, and an original phase difference sequence is formed and preprocessed; calculating a cross correlation coefficient of the target and the associated joint based on the preprocessed sequence, and constructing a motion feature set in combination with the joint speed and acceleration; constructing a prediction model by using a long-short-term memory network, and outputting motion intention and joint position prediction information through multi-feature fusion training; and analyzing the prediction information by adopting a second-order linear impedance model, generating a driving torque instruction and sending the driving torque instruction to the servo motor for execution. According to the method, signal phase difference analysis, LSTM prediction and impedance control are fused, the problems of response lag and poor adaptability of a traditional exoskeleton are solved, the control real-time performance, accuracy and cooperative fluency are improved, and the use requirements of different users in different scenes are met.

The invention discloses a robot variable stiffness surface path planning method based on three-dimensional perception and application. The method comprises the following steps: processing workpiece surface point cloud data; a surface defect detection model is established, and deformation deviation generated by workpiece surface defects in the point cloud data is compensated; and performing path planning analysis on the point cloud model to generate a self-adaptive tool path. In the process that the robot executes the planned path, passive analysis is conducted through a variable stiffness impedance control law under energy constraint, force control surface treatment is achieved by collecting a force feedback track as a reference and combining a quadratic programming optimization controller, and task execution of the robot planned path is completed. According to the method, a planned path model is combined, an AI auxiliary programming framework is designed, and a user parameterization task and tool are guided through a natural language interface and a knowledge representation engine. According to the method, the adaptive capacity of the robot to the complex variable stiffness surface is improved, the machining consistency and efficiency can be remarkably improved, and the wide application prospect is achieved.

The invention relates to the technical field of industrial control, in particular to an industrial stacker intelligent control system based on machine vision, and the system comprises a state resolving module which is used for carrying out the feature region decoupling of original observation data, and resolving a position deviation matrix and a deformation state variable for a rigid subspace and a flexible subspace respectively; the dynamic modeling module is used for identifying the first-order inherent frequency and the damping ratio of the mechanical structure on line and establishing a second-order impedance contact model; the impedance control module is used for generating an expected speed based on the position deviation and adaptively adjusting an impedance parameter according to a deformation state so as to carry out compliant modulation on a speed vector; and the estimation shaping module is used for correcting system time lag by using a Kalman observer and inhibiting residual vibration in combination with a zero-vibration input shaper. Through multi-dimensional physical field fusion and dynamic modeling, the problem that a rigid control model is mismatched with a flexible operation object is solved, and self-adaptive compliant control and vibration-free accurate operation of the stacking machine in the unstructured environment are achieved.

The invention discloses a dynamic environment robot adaptive control method and system, and relates to the technical field of robot adaptive control. According to the invention, dynamic compensation is realized based on multi-sensor fusion and real-time anomaly detection in combination with impedance compliance control; through a lightweight error model and a trajectory interpolation technology, the calculation efficiency is improved compared with traditional model prediction control, and high-frequency real-time correction is supported; the system adopts a modular design, and adapts to a heterogeneous robot platform by adjusting equivalent mass-damping-spring parameters; for sudden disturbance, trajectory smoothing and impedance control technologies are fused, the oscillation amplitude of the system is reduced, and execution jitter is effectively inhibited; according to the method, high-precision force tracking and stable control are achieved in scenes such as complex terrain walking and dynamic grabbing, the problems that traditional fixed parameter control response is lagged, model dependence is high and an actuator is overheated are solved, and the adaptive capacity of the robot to the dynamic environment and the task completion rate are remarkably improved.

The invention discloses a hand-eye-force integration-based catenary cantilever robot assembly method, which comprises the following steps of: synthesizing image sequences of different exposures into a high-quality image based on a self-adaptive multi-exposure fusion technology, identifying a workpiece contour in the image based on a deep learning framework, and calculating a pose of an identified part in a camera coordinate system; the two-dimensional camera and the three-dimensional camera are matched to carry out accurate scanning, an accurate pose deviation matrix of an actual workpiece relative to a theoretical model is obtained through a nearest point cloud registration algorithm, and a corrected moving target pose is calculated; and the robot moves towards the position and posture of the moving target, when the robot is about to make contact with the assembly workpiece, the impedance control mode is switched to conduct cantilever installation, and moment data are continuously monitored in the whole process till installation is completed. According to the method, the robot can intelligently cope with uncertainty in the cantilever assembly process, and the assembly success rate and the assembly efficiency are remarkably improved.

The invention relates to the technical field of AMR robots, and provides an AMR robot-oriented anti-slip movement control method and an AMR robot, and the method comprises the steps: determining a target wheel with a slip trend based on the real-time driving torque, collected by a driving motor of the AMR robot, of each wheel; based on the four-quadrant self-adaptive impedance, the current driving torque of the target wheel and the wheel torque difference value between the adjacent wheels are combined, and self-adaptive impedance adjusting parameters of the target wheel are determined; corresponding impedance control is applied to a driving motor of the target wheel based on the self-adaptive impedance adjustment parameter of the target wheel, and the adjusted output torque of the target wheel is obtained; and the moving posture and the moving speed of the AMR robot are adjusted based on the adjusted output torque till the AMR robot does not have the slipping trend. The operation stability of the AMR robot in the operation process is improved.

The invention discloses a robot dexterous arm teleoperation sharing control method and a related device, and relates to the technical field of robotics.The method comprises the steps that smooth expected pose information and expected angle state information are obtained, and pose information of a mechanical arm of a slave end at the current stage and angle state information and contact force information of a dexterous hand are obtained; based on the expected pose information and the joint angle information of the mechanical arm, the inverse kinematics of the mechanical arm is solved through a nonlinear optimization method, and a joint angle instruction of the mechanical arm is obtained; based on the expected angle state information, the angle state information of the dexterous hand and the contact force information, utilizing a fuzzy logic theory and a dynamic compliance primitive model to carry out adaptive variable impedance control on the dexterous hand to obtain a joint torque instruction of the dexterous hand; and feeding back the contact force information of the dexterous hand in the next stage to a main end operator. The success rate and the working efficiency of the teleoperation robot can be improved.

The invention discloses an air robot control method and system oriented to a complex environment, establishes a kinetic model of an air robot according to the control requirement of the air robot for executing contact operation in the complex environment, and provides a hierarchical control framework. The framework includes an outer torque estimator, an impedance-based force / trajectory tracking module, and a position controller and an attitude controller. Firstly, a generalized torque estimator is introduced, and effective estimation of external disturbance is achieved under the condition that no additional sensor is needed; secondly, the contact force tracking performance is improved while the track precision is maintained by using an impedance control module; and finally, a position controller and an attitude controller ensure rapid convergence of the position and the attitude. Theoretical analysis shows that the designed control law can ensure the stability and convergence of the system when uncertainty and external contact force exist, and an effective control method is provided for autonomous operation of the aerial robot in a complex task environment.

The invention discloses a robot Cartesian force damping control method and system based on a process energy mechanism, and the method comprises the steps: building a robot kinetic model, constructing an impedance control law and a force control law of a Cartesian space, and achieving the dynamic adjustment of control energy through combining a process energy container mechanism, global passivity and stability of the system in contact and non-contact states are maintained; the invention relates to the technical field of robot intelligent control and man-machine interaction. According to the robot Cartesian force damping control method and system based on the process energy mechanism, high-precision, safe and stable force control and damping adjustment can be achieved in the complex processes of polishing, assembling, wiping and the like, and a universal scheme with the energy self-management capacity is provided for safe man-machine cooperation.

The invention relates to a hexapod robot leg impedance control method and device, equipment and a medium, and relates to the technical field of automation control, and the method comprises the steps: training a primary function neural network through domain adversarial invariant learning based on a force-displacement compensation data set; a robot contact force deviation value is calculated, the contact force deviation value is input into the primary function neural network to extract environment invariant features, a Kalman filter is utilized to estimate an adaptive coefficient on line according to the environment invariant features, and a displacement compensation amount is calculated in combination with the environment invariant features and the adaptive coefficient; and the displacement compensation amount is injected into a robot impedance control loop, and leg movement of the hexapod robot is adjusted. According to the method, the environment invariant features are extracted, so that the method can better adapt to various complex terrains, the sensitivity to environment parameters is reduced, and the urgent requirements of the hexapod robot on high robustness, high precision and rapid self-adaptive contact control in actual operation are met.

The invention relates to the technical field of automobile electronics and intelligent control, and discloses an intelligent cabin mechanical arm system which comprises a folding mechanical arm body, a tail end sensing interaction module, a driver state monitoring subsystem and a central control unit which are installed in a cabin. The central control unit controls the storage or working mode of the mechanical arm according to the comprehensive fatigue index of the driver; in the working mode, visual gazing information is used as a gating signal to activate electroencephalogram analysis, the operation intention is confirmed in combination with the visual prior probability and electroencephalogram signals, and the mechanical arm impedance parameters are adjusted in real time based on the fatigue state. According to the method, through Bayesian fusion of vision and electroencephalogram signals, the problem that single-mode control is unstable is solved; by means of variable impedance control and collision detection of the momentum observer, active safety protection based on the physiological state of the driver is achieved, and non-sensitive and high-safety intelligent auxiliary experience is provided in a limited cabin space.

The invention relates to the technical field of industrial automation and intelligent manufacturing, and discloses a flexible packaging forming system and method based on a modular station robot, and the system comprises a central control module, a station robot module, a flexible material conveying module and a distributed intelligent detection module. The station robot module integrates functional units such as gluing, positioning and attaching, edge folding and frame erecting, foam scraping and flattening, precise gluing and assembling and cleaning. The method comprises the following steps: the central control module analyzes an order into a control instruction; the flexible material transmission module establishes a dynamic logistics network according to the instruction; the station robot module executes a full-process automatic forming process based on force control, visual compensation and impedance control algorithms; and the intelligent detection module feeds back quality data in real time to realize closed-loop correction. The problems that a traditional rigid production line is difficult to adapt to multi-variety small-batch production, the key process precision is insufficient, and accessory assembly depends on manual work are solved, and the flexibility level and the yield of packaging production are improved.

The invention discloses a space robot compliance control method and device based on multi-dimensional visual constraints, and belongs to the technical field of space robots and autonomous control. The method comprises the following steps: collecting and fusing data through a heterogeneous visual sensor group, and carrying out uncertainty quantification to generate a perception confidence index; constructing and dynamically adjusting a visual constraint function set based on the index, solving a motion feasible region according to the visual constraint function set, and generating an expected motion track; inputting the track into an impedance controller, and adjusting the rigidity and damping parameters in real time according to the sensing confidence so as to output an instruction; the instruction is verified through digital twin simulation, and if the instruction does not pass the verification, a fault-tolerant mechanism is triggered for optimization; and finally, updating the system parameters on line according to the deviation between the actual execution data and the simulation data. According to the method, the technical problems of poor operation safety, low control precision and insufficient autonomy of the space robot in a complex environment caused by single sensing information dimension, lack of uncertainty quantization and fixed control strategy are solved.

The invention discloses a complex terrain adaptability control system for a rescue robot, and belongs to the technical field of robots. According to the invention, full-closed-loop control is realized through the instruction layer, the hardware layer, the control layer and the monitoring layer. The control layer takes a posture adjusting module as a core, is linked with a PID (Proportion Integration Differentiation) and an impedance controller, and is combined with forward / reverse kinematics and suspension detection to realize accurate correction of a joint angle; the hardware layer feeds back attitude, joint movement and contact force data in real time by means of multiple sensors; meanwhile, a whole vehicle kinetic equation is established based on a spiral theory and a virtual work principle to deduce a contact force component, and a sliding rate is defined to quantify traction characteristics. According to the invention, through fusion of multi-module cooperation and mechanical modeling, organic unification of attitude control, force control flexibility and traction performance monitoring is systematically realized, and a complete attitude-force-traction cooperative control system is constructed.

The invention belongs to the technical field of robot intelligent control, provides a robot double-source joint information impedance control method and system, a medium and a robot, and aims at motion control of a 3R-configuration robot. Joint motion information including a filtering angle, a filtering angular velocity and a filtering angular acceleration is obtained, the pose and / or velocity information of the end effector is mapped to a joint space based on a kinematic model of the robot, and joint motion information including a mapping angle and a mapping angular velocity is obtained; fusing the angle and the angular velocity to obtain a fused angle and a fused angular velocity; and generating a control torque by combining the fusion angle, the fusion angular velocity and the filtering angular acceleration with a preset target impedance parameter and an expected trajectory. The angular velocity and the angular acceleration can be obtained without adding velocity and acceleration sensors on the motor, and the increase of the size, the complexity and the cost of the joint control motor is avoided.

The invention discloses a transformer oil sample automatic collection method and device based on vision and impedance control, and the method comprises the steps: determining a relative position between an oil taking injector and an oil taking port in a transformer oil sample collection process, and determining an ideal pose of the oil taking injector controlled by a mechanical arm to reach an oil taking port mark based on the relative position; based on image information collected in real time by an image taking device arranged on the mechanical arm, a space coordinate transformation matrix of the ideal pose at the oil taking opening mark and the actual pose of the image taking device is calculated; on the basis of the ideal pose and the space coordinate transformation matrix which are calculated in real time, according to a control law of pose deviation design, a visual servo control rule for the pose of the oil taking injector is determined; based on interaction between the working environment and the tail end of the mechanical arm, a butt joint depth control rule of an oil taking injector and an oil taking opening is determined through an impedance controller; based on a visual servo control rule and a butt joint depth control rule, butt joint of an oil taking injector and an oil taking opening is controlled, and transformer oil sample collection is carried out.

The invention relates to a force control-based weld joint ultrasonic detection method for a pressure container, and solves the technical problem of how to improve the precision, stability and reliability of defect detection of a weld joint of the pressure container by a mechanical arm driving an ultrasonic probe. A zero drift value of a six-dimensional force sensor and gravity components of an ultrasonic probe in six dimensions are calculated, then actual contact force and actual contact torque are calculated, the actual contact force is input into an impedance control module, force position control of a mechanical arm is achieved, cooperative compliant control over the contact force and the pose of the probe is achieved, and the mechanical arm is controlled. And the detection stability and reliability of the surface and internal defects of the welding seam are obviously improved.

The invention belongs to the technical field of intelligent assembly, and particularly relates to an active flexible assembly method for an electronic module, a mechanical arm controls the electronic module to move along a Lissaja curve under the current contact force, and meanwhile, the descending depth of the electronic module is monitored; when the descending depth of the electronic module changes, judging that the connector on the electronic module is aligned with the radio frequency interface; inserting the KK connector until the first-stage assembly is successful under the curvilinear motion along the Lissaja; and continuing to keep the pose for downward smooth insertion until the electronic module under the pose can reach the set depth of the second stage. Through combination of force-position hybrid control and impedance control, smooth control of the whole insertion process is realized, attitude compliance is improved, and initial impact is reduced. The Lissajous curve with adjustable amplitude, frequency and phase is adopted for high-density search, the jack position is actively captured, the problem that insertion cannot be achieved due to visual alignment errors is solved, and the jack center capturing flexibility is enhanced.

The invention discloses a two-arm robot flexible assembly method, device and equipment and a medium, and relates to the technical field of robot assembly.The method comprises the steps that gravity compensation is conducted on a contact force signal of a two-arm robot, and the compensated contact force signal is obtained; dynamically adjusting an impedance control model by using a fuzzy controller based on the compensated contact force signal to obtain a parameter-adjusted impedance control model; and according to the parameter-adjusted impedance control model and the compensated contact force signal, motion planning is conducted on the double-arm robot, and a flexible assembly result of the double-arm robot is obtained. The self motion state can be adjusted in real time according to changes of the external environment, it is ensured that the contact force in the assembling process is always kept within a proper range, and therefore the assembling precision is remarkably improved; the self-adaptive impedance control strategy can effectively avoid the situation that elements are damaged due to excessive force, and the production cost is reduced.

The invention relates to the technical field of intelligent robot control and artificial intelligence, and discloses a robot dynamic trajectory control method based on reinforcement learning and multi-sensor fusion, and the method comprises the steps: firstly fusing multi-modal sensor data through extended Kalman filtering, and predicting the time sequence distribution of dynamic obstacles through a long-short-term memory network; meanwhile, the dynamic operability and singularity risk factors of the robot are calculated, on this basis, a reinforcement learning network based on an attention mechanism is constructed to generate a high-level motion strategy, the high-level motion strategy is converted into a bottom-layer execution instruction through a variable impedance controller and a convex optimization torque distribution module, and singular points are avoided by using null-space characteristics. In addition, according to the method, model parameters are finely adjusted in real time by monitoring and predicting errors and the safety intervention degree on line. According to the method, organic fusion of logic decision and physical execution is realized through a layered architecture, and the operation safety, robustness and control precision of the robot in a dynamic environment are remarkably improved.

The invention discloses an optical detection method and system based on multi-axis cooperative control, and belongs to the technical field of optical detection. Path planning: adopting a spiral path planning function to obtain a path point sequence; then multi-axis inverse solution trajectory planning is carried out; the controller samples angle vectors of all joints of the mechanical arm in real time and inputs the angle vectors to the control law function; visual compensation, including image error calculation and generation of a position compensation amount by using an image error-to-space compensation algorithm; introducing a multi-axis cooperative motion control algorithm; the active vibration prediction model describes a mechanical arm system as a dynamic equation; adding an impedance control model into the controller; splicing and fusing the images; and detecting and judging. According to the invention, high-speed, high-precision and 100% full-width coverage detection of the 300mm wafer can be realized, the detection error is stably controlled within + / -1 [mu] m, and the defect detection level and the yield control capability of semiconductor manufacturing are remarkably improved.

An articulated robot control method and system and an articulated robot. The control method comprises: establishing a single-articulated impedance control model on the basis of a dynamics model of a robot; determining a stiffness range of a single articulation on the basis of the single-articulated impedance control model, the cut-off frequency of a robot control system, and a critical damping condition; using the stiffness range to determine the maximum stiffness value of the single articulation and a corresponding damping value; establishing a multi-articulated impedance control model and a Cartesian impedance model on the basis of the dynamics model; obtaining an articulation control law on the basis of the multi-articulated impedance control model and the Cartesian impedance model; and on the basis of the articulation control law, using the maximum stiffness value of the single articulation and the corresponding damping value to perform optimal impedance control. Thus, the technical problem in the prior art that the accuracy is low when dynamic performance control is performed on a robot by using an impedance control method is solved, and the technical effect of improving the accuracy of controlling the robot is achieved.

The invention relates to the technical field of circuit fault processing, and discloses an automatic identification and remote isolation method for a fault section of a low-voltage distribution line, and the method comprises the steps: building a reference fingerprint database based on channel state information through a central coordination node; monitoring real-time channel frequency response and executing threshold comparison to judge suspected fault points; triggering an active impedance control unit of the terminal agent node to execute controlled perturbation; a transmission line network model is used for calculating a theoretical transmission function variable quantity, fitting analysis is carried out on the theoretical transmission function variable quantity and a measured value, and a physical fault is judged and load interference is stripped through a normalized residual coefficient; calculating a residual drift distance between adjacent nodes based on the topological mapping table to execute differential positioning so as to lock a fault physical interval; and issuing a tripping message, and driving the circuit breaker to execute physical isolation at the power frequency zero crossing point. According to the scheme, on-line fault identification and isolation are realized through active impedance perturbation and distributed residual analysis, and the robustness of fault judgment in a complex load environment is improved.