30032 results about "Actuator" patented technology

The invention relates to an intelligent reflux valve adjusting method based on a self-adaptive control algorithm, and aims to improve the accuracy and response efficiency of fluid adjustment. The method comprises the steps that fluid flow, pressure, temperature and flow direction data collected by sensors installed at an inlet and an outlet of the reflux valve are obtained, and the initial target valve opening degree under the current fluid working condition is calculated through a working condition opening degree prediction model in combination with structural parameters of the reflux valve; based on the relation among the flow, the pressure and the valve opening, the initial target valve opening is adjusted through a fuzzy rule base, so that the final target valve opening is obtained, and therefore the dynamic change of the complex fluid working condition is adapted; according to the final target valve opening degree, an execution mechanism is controlled to adjust the operation state of the reflux valve, and precise adjustment is achieved; working condition prediction and fuzzy control are combined, the adjusting precision and stability of the reflux valve are improved, and the method is particularly suitable for fluid conveying systems with large flow and pressure fluctuation and has wide application prospects in the industries of energy, chemical engineering, environmental protection and the like.

An electronic device can comprise physiological sensors that can generate sensor data, a device processor, an actuator, and a controller electrically connected with the device processor and the actuator. The controller can monitor the state of the actuator; communicate a notification signal to the device processor to cause the device processor to prepare for a privacy mode responsive to determining that the actuator is in a privacy state, delay implementing the privacy mode until one or more conditions have been satisfied to allow the device processor to prepare for the privacy mode pursuant to communicating the notification signal to the device processor; and implement the privacy mode to inhibit access to the sensor data responsive to satisfaction of the one or more conditions.

The invention provides a thermal power generating unit performance optimization control system and method, and the system comprises a data collection module which collects various real-time data in the operation process of a thermal power generating unit; the load prediction module is used for establishing a load prediction model and predicting a load change trend by comprehensively considering a historical load condition, a load change rate, a load change acceleration and an external interference factor; the optimization control module is used for dynamically adjusting fuel, an air door and air quantity according to a control strategy in combination with the load prediction result and the unit operation state; the actions of the regulating valve, the air door actuator and the water supply regulating valve are correspondingly controlled; the monitoring feedback module is used for realizing closed-loop control and self-correction; according to the method, a load prediction model based on the combination of time sequence analysis and a physical mechanism and a control strategy comprehensively considering multi-parameter collaborative optimization are utilized, so that quick response to load change, balance consideration of steam quality and combustion efficiency, self-adaptive stable operation under complex working conditions and improvement of overall performance are achieved.

The invention includes systems and methods for relating to improved body structures for robots. A robot assembly includes a base member (e.g., a pelvis base). The robot assembly includes a first hip member rotatably connected to the pelvis base. The first hip member is connected to a first electric actuator configured to rotate the first hip member about a first hip axis relative to the pelvis base. A first intermediate member is rotatably connected to the first hip member. The first intermediate member is connected to a second electric actuator configured to rotate the first intermediate member about a second hip axis relative to the first hip member. A first leg member is rotatably connected to the first intermediate member. The first leg member is connected to a third electric actuator configured to rotate the first leg member about a third hip axis relative to the first intermediate member.

A mechanical end effector for a humanoid robot includes a plurality of identical finger assemblies. Each of the finger assemblies is removably connected to a frame. Each of the finger assemblies is fully self-contained and operable independently of every other one of the finger assemblies and independently of every other component connected to the frame. Each of the finger assemblies includes a single electric motor and is configured to be fully operable using only the single electric motor.

An apparatus includes a housing, a fluid reservoir, a flow control mechanism, and an actuator. The housing defines an inner volume and has an inlet port that can be fluidically coupled to a patient and an outlet port. The fluid reservoir is disposed in the inner volume to receive and isolate a first volume of a bodily-fluid. The flow control mechanism is rotatable in the housing from a first configuration, in which a first lumen places the inlet port is in fluid communication with the fluid reservoir, and a second configuration, in which a second lumen places the inlet port in fluid communication with the outlet port. The actuator is configured to create a negative pressure in the fluid reservoir and is configured to rotate the flow control mechanism from the first configuration to the second configuration after the first volume of bodily-fluid is received in the fluid reservoir.

A multimodal shared telerobotic system and method for a three-arm space robot, the system at least includes a local-site system, a communication module, and a remote-site system, where the local-site system includes two force-feedback haptic devices for left and right hands, a microphone array, and upper computer software; the remote-site system includes two robotic arms provided with end-effectors, an observation arm with a stereo camera installed at an end thereof, two force sensors, a vision unit and lower computer software; an operator can control the two robotic arms of the robot outside a cabin for performing operations, and control the observation arm to obtain a better local view; and a multimodal telerobotic control method of pose control, voice control, and force control is integrated with the robot's autonomous control through a shared control algorithm.

A seating device with a swinging device is provided. The seating device includes a seat base, a seat, an ottoman, a backrest, and two moving linkages configured to move the seating device from a first position to a second position. Moreover, the seating device includes a swinging device configured to couple between the seat base and the two moving linkages, and drive the two moving linkages to swing relative to the seat base along a front and rear direction. The swinging device includes a swinging actuator; and an eccentric transmitter is configured to transmit a swing actuation torque to the two moving linkages, where the eccentric transmitter includes a crank and a transmission arm, the crank is configured to couple with the swinging actuator, and the transmission arm is configured to couple with the two moving linkage via a universal joint device.

The invention relates to the technical field of data center heat dissipation, and particularly provides a single-phase and two-phase immersion liquid cooling method and system based on AI intelligent decision, and the method comprises the steps: injecting coupled data into a dynamic feature extraction engine, and outputting a thermodynamic state evolution tensor which comprises the characteristics of a temperature change rate, a load-heat flux density coupling coefficient and the like; the thermodynamic state evolution tensor is input into the deep neural network model, the temperature and pressure matched with the current thermodynamic state evolution tensor are calculated, and a closed-loop control instruction set capable of being executed by equipment is generated; a closed-loop control instruction set is injected into an execution mechanism set, execution mechanisms execute power reconstruction and flow channel switching according to instructions, gaseous fluorinated liquid is liquefied and flows back through an efficient condenser in a two-phase mode, and heat dissipation mode self-adaptive switching and heat cycle reconstruction are achieved. The system comprises a server, an AI algorithm controller, a cooling liquid storage device, a condenser, a circulating pump, an electric valve, a pressure release valve and a temperature sensor. The heat dissipation efficiency and the system reliability are remarkably improved.

The invention discloses a deep sea underwater electro-hydraulic actuator (EHA) and a control system thereof. The system provides power through the power source module, balance of system oil pressure and pressure of external seawater is controlled through the pressure compensation module, oil circulation and oil pressure control are conducted through the integrated valve set module, a control instruction of the control module is executed through the execution mechanism module, and the control module conducts cooperative control over the whole system. According to the control system, the unbalanced pressure between the system and the deep sea high-water-pressure environment is compensated through the pressure compensator so as to reduce the influence of the deep sea high-water-pressure environment, meanwhile, the pressure compensator serves as an oil tank to supply oil, miniaturization of the system is achieved, and the reliability of the system during underwater work is improved; according to the deep-sea underwater electro-hydraulic actuator, the mounting positions and internal flow channels of all elements of the integrated valve bank are optimized, the pressure loss of fluid in the flow channels is reduced, and the energy utilization efficiency of the deep-sea underwater electro-hydraulic actuator is improved; the asymmetric hydraulic cylinder can operate in four working conditions of deep sea, and underwater high-precision movement can be completed.

The invention provides a servo system optimization method and system based on algorithm control, and relates to a motor control technology, and the method comprises the steps: firstly obtaining a real-time dynamic response parameter set during the dynamic operation of a servo device, covering inertia delay, torque fluctuation and position deviation parameters, and a corresponding optimization demand set, including optimization demands for each parameter; performing multi-level control signal generation on the real-time dynamic response parameter set according to the optimization demand priority, generating a control signal sequence set matched with a first compensation signal, a second compensation signal, a third compensation signal and the like, inputting the control signal sequence set into an execution mechanism, and driving the execution mechanism to dynamically respond according to an updating track, and finally, the control signal sequence set is optimized according to a feedback signal set generated by an execution mechanism, so that operation parameters of the servo device can be comprehensively considered, control signals are generated in a targeted manner, dynamic adjustment and optimization are realized, and the performance of the servo system is effectively improved.

A bodily-fluid transfer device includes a housing, a pre-sample reservoir, and an actuator. The housing defines an inner volume between a substantially open proximal end portion and a distal end portion that includes a port couplable to a lumen-defining device. The pre-sample reservoir is fluidically couplable to the port to receive a first volume of bodily fluid. The actuator is at least partially disposed in the inner volume and has a proximal end portion that includes an engagement portion and a distal end portion that includes a sealing member. The engagement portion is configured to allow a user to selectively move the actuator between a first configuration such that bodily fluid can flow from the port to the pre-sample reservoir, and a second configuration such that bodily fluid can flow from the port to a sample reservoir defined at least in part by the sealing member and the housing.

The invention discloses a use monitoring method and system for a knife gate valve, and relates to the technical field of knife gate valve monitoring, and the method comprises the steps: integrating a multi-mode sensor array at the root of a valve rod of the knife gate valve, an adjacent region of a sealing surface and in a valve cavity flow channel, and collecting multi-source signals in real time; performing dynamic fusion processing on the multi-source signal, and determining a feature extraction algorithm combination based on the current valve rod temperature and historical working condition data to extract a sealing surface damage feature, a transmission chain wear feature and a particle impact feature; constructing a dynamic anomaly judgment model, updating a clustering boundary of a vibration and torque characteristic space in real time, and performing decoupling diagnosis on a sealing surface dry friction risk, thread clearance expansion and gear wear in combination with time-frequency domain fluctuation analysis of a gear meshing frequency harmonic attenuation rate and an angular acceleration; and generating a three-level maintenance strategy according to the diagnosis result, dynamically adjusting the output torque of the execution mechanism and optimizing the switching frequency of the valve.

The invention provides an industrial robot control system and method. The system comprises a trajectory planning module, a dynamic compensation module, a feedback control module, an execution module, a sensor module and a data storage module. The trajectory planning module generates an expected trajectory of an end effector of the robot; the dynamic compensation module calculates a dynamic compensation torque based on the expected trajectory and a robot dynamics model; the feedback control module generates feedback control torque according to the deviation between the real-time pose data acquired by the sensor module and the expected trajectory; the execution module drives robot joints to move according to the synthesized moment of the dynamic compensation moment and the feedback control moment; the sensor module collects robot joint angle, angular velocity and torque data in real time; the data storage module stores robot dynamic model parameters, control algorithm parameters and historical motion data. High-precision and smooth robot motion control can be achieved, the dynamic response and stability of the system are improved, and energy consumption and motion errors are reduced.

The invention relates to the technical field of self-adaptive control, and discloses a self-adaptive temperature control method and system for an automobile heater, and the method comprises the steps: calculating the real-time temperature deviation and temperature change rate of an actuator according to multi-dimensional temperature data; thermal inertia dynamic analysis is carried out on the historical heating power and temperature response relation through a preset thermal inertia compensation function, and a thermal inertia index of the actuator is obtained; the real-time temperature deviation, the temperature change rate and the thermal inertia index are jointly input into a preset fuzzy PID controller, and a preliminary power adjustment instruction of an actuator is output; analyzing the temperature change trend of the actuator in the time period, and performing prospective correction on the initial power adjustment instruction based on the temperature change trend; and controlling an actuator to execute heating operation according to the temperature control instruction, collecting real-time feedback temperature after the heating operation is executed, and performing joint online correction on parameters of the thermal inertia compensation function and a prediction coefficient of the time sequence model according to the real-time feedback temperature. According to the invention, the accuracy of self-adaptive temperature control of the heater can be improved.

The invention relates to the technical field of intelligent manufacturing, and discloses an extreme manufacturing process technological parameter optimization method and system fused with machine learning. The method comprises the following steps: acquiring multi-source data from a manufacturing equipment sensor, and fusing to generate a material state vector; inputting a pre-training model to obtain a material coefficient transition trend; judging whether the trend fluctuation amplitude exceeds a preset threshold value or not, and if yes, marking key nodes and extracting feature parameters; for the key nodes, according to the characteristic parameters and the real-time data of the key nodes, a control algorithm is adopted to calculate the parameter adjustment amount; optimizing the control parameters based on the parameter adjustment amount, generating a control instruction sequence and transmitting the control instruction sequence to an actuator; and obtaining adjusted feedback data, comparing the adjusted feedback data with the transition trend, and if the deviation exceeds an allowable range, updating the pre-training model. Through deep fusion of predictive monitoring and intelligent control, accurate optimization and adaptive control of process parameters are realized, the stability of the extreme manufacturing process and the product quality are improved, and the energy consumption and the defect rate are reduced.

An agricultural implement control system, comprising at least one position sensor in association with at least one actuator and a processor in communication with the at least one position sensor configured to determine a position of the at least one actuator. The system where the at least one position sensor comprises a magnetometer and a magnet. The system including a controller wherein is controller is configured to start and stop an implement operation based on the position of the at least one actuator.

The invention discloses an intelligent maintenance system and method for an electric actuating mechanism based on fault prediction, and particularly relates to the technical field of equipment maintenance. The method comprises the following steps: acquiring historical operation data in a preset operation period, generating a historical health data set, extracting characteristic parameters to obtain a historical characteristic parameter set, and constructing a trend change characteristic matrix according to the change trend of the historical characteristic parameters; constructing a multi-dimensional state space by using the trend change feature matrix, calculating the state aggregation degree of the fault event in the space, and determining an early warning index set; meanwhile, collecting real-time operation data to extract real-time feature parameters, forming real-time feature state vectors, and performing correlation calculation on the real-time feature state vectors and early warning indexes in a space to obtain real-time risk correlation factors; and finally, generating a risk probability prediction model according to the real-time risk association factor, the historical characteristic parameter set and the trend change characteristic matrix, predicting a fault probability and outputting a maintenance scheduling suggestion, thereby realizing intelligent maintenance of the electric actuating mechanism.

An actuator, relating to the technical field of robots. The actuator comprises: a speed reducer shell (1), a planetary speed reducer (2) and an output-end supporting bearing (3), wherein the speed reducer shell (1) is provided with a connecting flange (101) and a connecting section (102), which is located on an inner side, the planetary speed reducer (2) is provided with a ring gear flange (2011) located on an outer side of a ring gear (201), the ring gear flange (2011) is arranged on one side of the connecting section (102), and the output-end supporting bearing (3) is arranged on the other side of the connecting section (102) and is connected by means of a fastener; an electric-motor rotor (4) and an electric-motor output shaft (5), the electric-motor rotor (4) being arranged on an outward extension portion of the electric-motor output shaft (5), and the electric-motor output shaft (5) being fixedly connected to an input end of the planetary speed reducer (2); and an electric-motor housing (6) and an electric-motor stator (7), wherein the electric-motor housing (6) is provided with a connecting end (601), the electric-motor stator (7) is arranged in the electric-motor housing (6), and the connecting end (601) is fixedly connected to the connecting flange (101).

A head and neck assembly for a humanoid robot, including a head portion having an exterior surface defining an overall shape resembling a human head; a neck portion extending from the head portion; a head housing assembly enclosing the head portion and neck portion; an electronics assembly contained within the head housing assembly; and a head actuator assembly configured to move the head portion relative to a torso of the humanoid robot.

The invention discloses a water flow intelligent monitoring system and method, and relates to the technical field of water flow intelligent monitoring, in combination with an actuator health degree evaluation and multi-target prediction control method, the characteristics of a valve and a water pump are finely described by arranging sensors and constructing a digital twinborn model; model predictive control or multi-agent reinforcement learning is adopted to dynamically generate a reliable and efficient control instruction; furthermore, through real-time closed-loop deviation detection and self-adaptive correction, delay, faults or communication abnormity of the actuator can be accurately dealt with; 4, quickly completing self-healing and fault-tolerant control by using a fault prediction and standby scheduling strategy to prevent failure diffusion; and 5, scenes such as rainfall flood, fire fighting and reclaimed water are incorporated into the same framework, and multi-scene coupled comprehensive water resource management is realized, so that water hammer impact and water leakage risks can be effectively reduced, and the safety of the water supply system under complex working conditions or equipment aging is remarkably improved.

Systems and methods that allow robots to perform tasks for users are provided. A robot may comprise one or more robotic arms and / or a mobile base. The arms may be controlled by electric actuators and may have six or more degrees of freedom. The robot may have sensors which can be accessed remotely. Robots may have varying levels of autonomy, including, for example, full teleoperation (in which a human can have detailed control over the robot) or full autonomy (in which the robot can complete a task without any human intervention). Various entities can interact with individual robots or groups of robots over a network, locally, directly or in person, or any combination thereof. A management system can allow entities to control and / or monitor the robots.

A theater chair comprises a flip-up / flip-down seat, a reclining backrest, and a reclining seat. An actuator is operatively connected to the reclining backrest for moving the backrest and seat from a normal or default upright position to any one of a multitude of reclined positions. The flip-up / flip-down seat is provided with a spring for returning the seat to its upright position when the seat is unoccupied. A sensor is operatively associated with the seat so as to effectively monitor the orientation of the seat. When the seat is vacated, the sensor will detect movement of the seat and send an appropriate signal to a control circuit which is operatively connected to the actuator. After a predetermined period of time, the actuator will be actuated so as to return the backrest from the reclined position to the default upright position.

The invention discloses a robot control method and system for an industrial pipeline, and relates to the technical field of robot control. The method comprises the steps that a flange plate is installed on an end effector of the robot, a binocular vision camera is installed in the center of the front end of the flange plate, and four point laser displacement sensors are symmetrically arranged on the flange plate at different heights; the binocular vision camera collects a pipeline image; the upper computer determines an initial pose control result of the robot according to the pipeline image so as to control the robot to move preliminarily; the four point laser displacement sensors are used for collecting spatial displacement data of the pipeline at different height points after the robot moves preliminarily; and the upper computer determines a target pose control result of the end effector of the robot through the spatial displacement data so as to control the end effector of the robot to carry out pose adjustment. According to the method, accurate control over the axial parallelism of the robot end effector and the pipeline can be achieved, and therefore the pipeline assembling accuracy is improved.

The invention provides an intelligent grabbing control method and system based on tactile perception, and the method comprises the steps: obtaining a tactile feedback signal through a sensor array of a humanoid robot, carrying out the frequency domain decomposition of the signal through a Fourier transform method, and carrying out the analysis of the pressure and deformation data of each contact point on the surface of a to-be-grabbed object, calculating to obtain frequency characteristic distribution of the tactile feedback signal; if the initial estimation value of the object rigidity gradient exceeds a threshold value, performing finite element analysis on the object rigidity gradient, and combining a time domain processing result of the tactile feedback signal to obtain object rigidity gradient distribution; carrying out probability modeling on the deformation field by adopting a Bayesian inference method according to the gradient distribution of the rigidity of the object, and carrying out iterative optimization on a modeling result to obtain dynamic update parameters mapped by the deformation field; and regenerating an action sequence of the end effector of the humanoid robot based on the optimized strategy according to a trigger condition of grabbing failure detection, and determining a final grabbing control parameter.

The invention discloses an actuator sealing performance test method and system, particularly relates to the technical field of industrial equipment sealing performance detection, and is used for solving the problem of positioning failure caused by signal aliasing in a multi-leakage scene in an existing method. Pressure attenuation frequency spectrum characteristics and leakage impact frequency spectrum peaks are extracted respectively by pressurizing a sealed cavity and synchronously collecting dynamic pressure and vibration signals; calculating a path loss value based on the amplitude gradient and the propagation time difference, and screening candidate leakage nodes; constructing a space grid model to solve three-dimensional coordinates of the leakage source; after the coordinates are projected to the surface of the structure model, pressure modal coherence and vibration impact energy are coupled and analyzed to generate a detection map; and finally, outputting a multi-leakage-point identification graph through spatial clustering and intensity grading. Accurate separation and spatial positioning of multiple leakage signals are achieved, and the reliability of complex sealing structure detection is remarkably improved.

The embodiment of the invention provides a filling production line control method and system based on a virtual reality technology. According to the embodiment of the invention, the method comprises the steps: synchronously collecting a real-time dynamic parameter set of a fluid medium, constructing a dynamic coupling factor, generating a dynamic response coefficient matrix through a fluid coupling identification model, generating a nonlinear control parameter combination according to the dynamic response coefficient matrix, and inputting the nonlinear control parameter combination into a motion trail planner. Generating an optimized motion track instruction, driving an execution mechanism to execute filling operation according to the optimized motion track instruction through a servo controller, monitoring the deviation degree in real time, reconstructing the fluid coupling identification model when the deviation degree exceeds a preset threshold value, and updating a dynamic coupling factor; the nonlinear control parameter combination is corrected through the updated dynamic coupling factor, a closed-loop interlocking control mechanism is generated, and the technical scheme provided by the embodiment of the invention not only improves the intelligent level of a filling production line, but also improves the precision and stability in the filling process.

The disclosure relates to an air guide control system with a flap arrangement including flaps which can be rotatably inserted into a joining partner. An actuator drives a damper and a coupling rod transmits the torque of this driven damper to the remaining dampers of the damper arrangement. In the event of a flap fracture of at least one flap, a spring, locks the flap arrangement against further movement, so that error information is reported to the actuator via the coupling rod.

A joint simulation and operation operability evaluation method based on wind power operation and maintenance ship motion dynamic response and active compensation gangway ladder motion control comprises the steps that an operation and maintenance ship frequency domain seakeeping model is built, and a hydrodynamic coefficient library is calculated; wave exciting force is reconstructed based on a Cummins time domain motion equation, and ship motion response prediction is realized by adopting implicit generalized alpha time domain composite integral; the dynamic positioning system extracts low-frequency motion through a Kalman filter and optimizes thruster thrust distribution to stabilize the position of the ship. A gangway ladder dynamic model is established based on a Lagrange equation, real-time control over displacement, speed and acceleration of the top end of the gangway ladder is achieved through a feedforward-feedback composite control strategy, and nonlinear output of a hydraulic actuator is optimized. And realizing joint simulation of the coupling system through time domain synchronization and self-adaptive PID (Proportion Integration Differentiation) control. And checking gangway ladder movement based on a preset threshold value and a space boundary condition, and evaluating the operability of the climbing operation. According to the method, the limitation of traditional single-disciplinary analysis is broken through, and the forecasting precision of wind power operation and maintenance operation operability is effectively improved.

The invention discloses an automatic control method and device for a thermal management system of an electric vehicle, relates to the field of intelligent control, and realizes multi-step prediction of battery and motor heat production and thermal load change in the future by fusing external information such as a navigation path and weather forecast, plans a thermal management strategy in advance, and improves the response perspectiveness of the system. A multi-source disturbance dynamic structured correlation equalization technology is adopted, the coupling relation between heat sources is modeled, cross disturbance is compensated through a joint state function, and multi-heat-loop cooperative control is achieved. On the basis of a model predictive control (MPC) framework, temperature tracking errors and energy consumption penalty are optimized, the energy consumption of actuators such as a compressor and a water pump is reduced while a safe temperature interval is met, and the endurance is prolonged. And in combination with a state estimator fusion model and observation data, the control precision and robustness under a complex working condition are enhanced, and finally global optimal thermal management considering the service life of parts, the comfort of passengers and the energy efficiency is realized.