10467 results about "Force sensor" patented technology

Disclosed in the present invention are a multi-modal shared teleoperation system and method for a three-arm space robot. The system at least comprises a master-side teleoperation system, a communication module and a slave-side robot system, wherein the master-side teleoperation system at least comprises two force feedback hand controllers, a microphone array and upper computer software, and the slave-side robot system comprises two operating arms each equipped with a gripper at the end, an observation arm having a binocular camera mounted at the end, a vision unit, a force sensor and lower computer software. The method comprises: an operator controlling two operating arms of an extravehicular robot to execute a task, and controlling an observation arm to acquire a better local field of view. In the method, a multi-modal teleoperation method comprising pose control, voice control and force control is fused with autonomous control of a robot by means of a shared control algorithm, and thus, human-robot collaborative control over the position, orientation and contact force of a robotic arm can be realized on the basis of the requirements of the operator, and the robot autonomously executes other relatively simple tasks, thereby reducing the operation burden of operators, and improving the control efficiency.

The invention provides a magnetic core intelligent cutting parameter self-adaptive optimization system based on multi-mode perception, and relates to the technical field of data processing.The method comprises the steps that a multi-mode sensor module is integrated on magnetic core cutting equipment, and the module comprises a force sensor, a visual sensor and a temperature sensor; the acquisition units are respectively used for acquiring cutting force dynamic signals, cutting track image sequences and cutter temperature time sequence data in real time; magnetic core surface texture features and three-dimensional contour data are captured through a visual sensor, and an initial cutting parameter set is generated in combination with a magnetic core material type recognition result, associated parameters in a historical process database and preset process constraint conditions; and first workpiece trial cutting is executed based on the initial cutting parameter set, multi-modal data fusion collection is synchronously started, cutting force frequency domain feature vectors, a tool temperature change rate curve and cutting surface defect image features are obtained, and multi-modal data are obtained. According to the invention, multi-objective collaborative optimization of processing efficiency and energy consumption is realized.

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.

The invention relates to the technical field of grinding, in particular to a self-adaptive force control grinding system and method for a complex curved surface machining robot. Three-dimensional point cloud data of a workpiece are obtained through machine vision, gridding processing is carried out, and normal vector and curvature characteristic parameters are calculated; performing operation area division and operation path planning based on curvature characteristics; calculating operation parameters according to the normal vector and curvature characteristics; a self-adaptive impedance control algorithm is adopted, the polishing force is monitored in real time through a force sensor, and the rigidity and damping parameters of the robot are dynamically adjusted; and performing defect identification on the surface image of the processed workpiece by using the deep learning model, and when defects are identified, re-planning the operation path. According to the method, self-adaptive grinding of the complex curved surface workpiece is achieved, and the grinding efficiency and quality of the complex curved surface can be improved.

The invention provides an intelligent pressure sensor temperature compensation system, and relates to the technical field of pressure sensors, and the system comprises a hardware sensing module which comprises an elastic sensitive element and is used for reducing the temperature drift magnitude of a pressure sensor; the environment data acquisition module comprises a flexible thermoelectric sensor array and is used for acquiring temperature and humidity data; the humidity correction module is used for integrating a dynamic humidity correction algorithm and establishing a cross-sensitive matrix model to correct the original signal to generate a first pressure correction signal; the temperature compensation module is used for carrying an incremental neural compensation network and constructing a compensation model to perform temperature compensation on the first pressure correction signal to generate a second pressure compensation signal; and the fault compensation module is used for triggering a digital twinborn compensation model to perform fault compensation on the second pressure compensation signal to generate a target pressure output signal when a fault of the single sensor is monitored, so that the pressure measurement error in the whole temperature range can be accurately controlled, and the environmental adaptability and the intelligent level of the system are improved.

The invention discloses a stress analysis method for bridge incremental launching construction, and particularly relates to the field of stress analysis. According to the method, a mechanical state matrix is generated by combining wavelet noise reduction and Kalman filtering through distributed optical fibers, a piezoelectric force sensor, a vibrating wire stress meter and other equipment and real-time data; a pushing system-temporary support-beam body coupling dynamic mechanical model is established, and a generalized alpha method is adopted for solving and Bayesian optimization calibration parameters are adopted; key parameters are identified on line through a three-level progressive framework, boundary conditions are dynamically updated in combination with a total station and a laser tracker, and supporting rigidity self-adaptive adjustment is achieved through fuzzy PID control. Model confidence evaluation adopts a residual norm-modal confidence criterion-Bayesian update three-level mechanism, finally, stress distribution, support reaction and displacement deviation are calculated based on a correction model, and a safety index, threshold alarm and risk analysis report is generated through a fuzzy comprehensive evaluation method and fed back to a construction control center in real time.

Embodiments of the invention provide a pen-stylus that comprises a first antenna having a hemispherical shape at a proximal end of the pen-stylus where the pen-stylus engages with a display of a tablet device. The pen-stylus also includes a second antenna, wherein the first antenna and the second antenna communicate with the tablet device to enable a pen-stylus user to draw on the display of the tablet device. The pen-stylus additionally includes an insulating material between the first antenna and the second antenna that prevents interference between the first antenna and the second antenna. In some embodiments, the first antenna and the insulating material reside in a marker tip attached to the pen-stylus, the marker tip transmits axial forces received by engagement of the pen-stylus with the display on the tablet to a force sensor. The pen-stylus further includes a force sensor that converts axial forces received from the marker tip into an electrical signal and transmits the electrical signal to the tablet by at least one of the first antenna and the second antenna.

The invention provides an industrial robot multi-station intelligent sorting and stacking method based on visual guidance, which relates to the technical field of robot control, and comprises the following steps: determining a target station by acquiring multi-station real-time state information, calculating an optimal grabbing time window by using a graph neural network state predictor, and obtaining a target grabbing time window; and the placement strategy is dynamically adjusted based on the visual image and the force sensing data in the article stacking process. According to the multi-station intelligent stacking system, the sorting efficiency in a multi-station scene can be improved, the grabbing precision of dynamic objects is enhanced, and stable and reliable intelligent stacking operation is achieved.

The invention relates to an AI server cooling water pump vibration quantity self-adaptive calibration test method and system, an intelligent test platform integrates a six-dimensional force sensor and a temperature compensation vibration exciter, the platform rigidity is automatically calibrated, a water pump-pipeline system transfer function is obtained, and a rotating speed-lift-modal frequency three-dimensional mathematical model is established; a three-axis MEMS accelerometer array is arranged at sensitive parts such as a water pump bearing seat and a motor shell, and vibration, current and pressure signals are synchronously collected; carrying out time-frequency domain signal processing by adopting variational mode decomposition in combination with self-adaptive S transformation, and extracting a 128-dimensional full-frequency domain feature vector containing a modulation side frequency band; effective values of vibration acceleration, speed and displacement are calculated through a frequency domain integration algorithm, and current harmonic interference is corrected through an electromagnetic vibration compensation model; and finally, a vibration health degree evaluation model containing 18 characteristic parameters is established based on a support vector machine, the test system comprises an intelligent test platform unit, a multi-source sensing unit, an edge calculation unit and a data management unit, and microsecond-level synchronous acquisition and GB-level data throughput are realized through a time sensitive network. And online incremental learning and automatic generation of a test report are supported. The method has the effect of improving the water pump vibration quantity test precision.

The invention discloses an intelligent health management system and method based on edge calculation and reinforcement learning. The system comprises an old people data acquisition module, an edge calculation module, a multi-modal fusion module, a reinforcement learning intervention module and a block chain evidence storage module. Physiological and environmental data are collected through a wearable device, a millimeter-wave radar, a pressure sensor and the like, data noise reduction and anomaly detection are realized at an edge end, a cloud end adopts a CNN-LSTM neural network to fuse multi-modal features, reinforcement learning is combined to dynamically generate personalized intervention actions, intervention behaviors and results are stored through a block chain technology, and the intervention effect is improved. And safe and credible strategy optimization is realized. According to the invention, continuous monitoring and intelligent intervention of the health state of the old people can be realized, and intelligence and credibility of community health management are improved.

Embodiments of the invention provide an active pen-stylus that emulates a paper feeling for users of the active pen-stylus. The active pen-stylus comprises a writing shaft that receives physical forces arising from use of the pen-stylus by a user. The active pen-stylus also includes a force sensor that receives forces from the writing shaft, the force sensor configured to convert received forces into an electronic signal. A writing spring receives forces from the force sensor and reflects back to the user a reactionary force that emulates a paper feeling. The writing spring compresses and undergoes geometric deflection in creating the reactionary force that emulates the paper feeling. The geometric deflection produced by the writing spring arises from deformation of the writing spring by the received forces.

The invention discloses a rapid demolding device and method for a small prefabricated part, and relates to the technical field of prefabricated part production. The mold bearing table is mounted on the substrate of the demolding rack and is integrated with a multi-point temperature sensor and an acoustic vibration signal collector; the ejection demolding assembly is installed on the stand columns of the demolding rack in a liftable mode and comprises an ejection plate assembly, and an ejection force sensor and a high-frequency vibrator are arranged on the ejection plate assembly; the visual identification module is mounted on the demolding rack; and the controller is electrically connected with the multi-point temperature sensor, the sound vibration signal collector, the ejection force sensor, the high-frequency vibrator, the visual recognition module and a driving mechanism of the ejection demolding assembly. Multi-source sensing information is fused, the component condensation state and the demolding time are accurately judged, the ejection force and vibration in the demolding process are adaptively controlled, accurate and flexible control over the demolding time and process is achieved, and the demolding success rate and the component yield are remarkably increased.

The invention relates to the field of image processing, and discloses a lightweight container correction method and system based on machine vision, and the method comprises the steps: building a detection model through enhancing the feature response of a corner fitting region, detecting a corner fitting, calculating a disparity map of a multispectral image, reconstructing the three-dimensional coordinates of the corner fitting, and carrying out the pose conversion; identifying time-varying parameters on line to construct a state transition matrix, calculating predicted vibration displacement, projecting the vibration displacement to a world coordinate system, and calculating innovative sequence variance to dynamically adjust noise parameters; an inner and outer ring control framework is constructed, and an outer ring visual controller generates target force by calculating pose errors in a world coordinate system; an inner loop force control compensator combines predicted vibration offset and force sensor feedback to correct a mechanical arm control instruction, control gain is scheduled through a task stage, and vibration frequency self-adaptive adjustment parameters are analyzed; and performing force control compensation based on the target force, and discretizing the continuous impedance model to obtain a recursive control law to resist external disturbance.

The invention relates to the technical field of mine equipment monitoring and maintenance, and discloses a mine equipment state monitoring and maintenance method based on the Internet of Things, which comprises the following steps: S1, multi-source data acquisition: synchronously acquiring equipment operation parameters and environmental parameters through vibration, temperature and pressure sensors and environmental sensors deployed on mine equipment; s2, edge calculation processing: performing filtering and anomaly detection on the sensor data at a mine edge gateway to generate a compressed data packet; s3, online learning and model dynamic updating; s4, new equipment is accessed; s5, maintenance decision and resource scheduling; and S6, performing closed-loop feedback optimization. High-error historical sub-trees are dynamically eliminated, new sub-trees are generated, model parameters are adjusted in combination with maintenance feedback data, on the basis that historical effective knowledge is reserved, equipment dynamic features are extracted, accurate matching of prediction results and maintenance strategies is ensured, and the self-learning ability and maintenance decision reliability of the model are remarkably improved.

The invention relates to the technical field of robot joint control, and discloses a robot dog mechanical joint control method. The method comprises the following steps: acquiring a whole-body joint real-time sensing data set which covers the torque reading of a multi-axial force sensor, the angle data of a joint encoder and the body attitude data of an inertial measurement unit; motion state compensation is carried out on the sensing data based on a dynamic window mechanism, and a dynamic compensation matrix containing kinematics compensation parameters is generated; and inputting the multi-modal motion control data set into a gradient descent model under space-time constraint to complete multi-modal motion feature fusion so as to obtain a fusion motion control data set. Joint behavior abnormity is detected through a Lyapunov stability analysis algorithm, and abnormal nodes are identified; and iteratively optimizing control parameters through a fuzzy PID optimization algorithm to generate an optimized control parameter set, finally constructing a three-dimensional virtual motion space model, and establishing a dynamic mapping relationship between a virtual track and an actual mechanism.

Embodiments of the invention provide a plurality of safety features for a pen-stylus. The pen-stylus may comprise a writing shaft that receives mechanical input forces as a user engages the pen-stylus on a display of a tablet device, a force sensor that translates mechanical input forces received from the writing shaft into electrical ones for operation by electronics in the pen-stylus; and a writing shaft impact shock absorber that receives heavy forces imparted to the pen-stylus to shield the force sensor from receiving such heavy forces. The heavy forces impacting the pen-stylus may arise from the pen-stylus being dropped onto a hard surface.

The invention discloses a battery cell simulation type state sensing and feedback method and system, and the method comprises the steps: providing a simulation battery cell detection device which flows on a production line along with an actual battery cell; the device is provided with a shell matched with an actual battery cell in boundary dimension, a film pressure sensor covering the surface of the shell, and a built-in collector, in the circulation process, the sensor collects pressure data applied by the production line equipment in real time; the built-in collector stores data and sends the data to the upper computer processing system in a wireless mode; and the upper computer processing system receives and analyzes the pressure data, judges abnormity according to a preset pressure threshold value and generates a report. By simulating the real stress condition of the battery cell, comprehensive, real-time and automatic monitoring of the pressure state in the production process is realized, the abnormal reason can be accurately positioned, the problems of lack of monitoring means and difficulty in problem tracing in the prior art are solved, the product quality and the production efficiency are effectively improved, and the potential quality hazard is reduced.

The invention discloses a hydropower station expansion tank water level prediction alarm method and system, belongs to the technical field of hydropower station automatic control, and aims to solve the technical problems of limited monitoring points, high false alarm rate, response delay and the like of a traditional hydropower station expansion tank water level alarm system. According to the invention, the multi-mode sensing network is constructed, and data of the pressure sensor array, the radar level meter and the float switch group are fused, so that space continuous monitoring is realized; a three-level sensing architecture is adopted, heterogeneous data is subjected to normalization processing, and dimensional differences are eliminated; the LSTM network is used for liquid level prediction, and a self-adaptive window adjustment mechanism is combined, so that the prediction flexibility and accuracy are improved; a DQN algorithm is adopted to optimize a control strategy, fine adjustment of the liquid level is achieved by adjusting the opening degree of the valve, the accuracy, timeliness and intelligent level of water level monitoring and alarming of the expansion water tank of the hydropower station are remarkably improved, the stability of the liquid level of the water tank is ensured, the system operation efficiency is optimized, the manual intervention requirement is reduced, and safety is improved.

The invention discloses an industrial bolt intelligent identification and accurate grabbing control method and system based on depth vision, and the method comprises the steps: obtaining multispectral image data, carrying out the fusion detection of the nut edge, thread texture and other features of a bolt through an enhanced YOLOv8 network, screening an effective bolt, and eliminating the interference of a gasket, chippings and the like; extracting feature points to solve a 6DoF attitude, fusing vibration data of the mechanical arm to realize motion compensation, and outputting a three-dimensional coordinate and an attitude angle under a coordinate system of the mechanical arm; the three-dimensional coordinates are converted into motion coordinates, and the grabbing position is corrected in combination with the normal vector of the assembly surface; planning a path and generating grabbing strategies such as clamping jaw opening amplitude and clamping force matched with the bolt specification; the clamping force is dynamically adjusted based on feedback of the six-dimensional force sensor, and accurate grabbing is achieved. The system comprises a visual perception subsystem, an intelligent decision-making subsystem and a precise execution subsystem. The bolt recognition precision and grabbing stability in the complex environment are improved, and the assembly requirements of bolts of multiple specifications can be met.

The invention discloses a multi-mode cooperative intelligent infant tending control system and method. The system comprises a sensor module, a data fusion module, a path planning module, a trajectory prediction module, a parameter optimization module and a trajectory generation module. According to the invention, data are collected through the sensor module on the RGB-D camera, the laser radar and the six-dimensional force sensor arranged on the mechanical arm, an environment sensing model is constructed, and a feeding bottle is positioned; the mechanical arm plans a path according to the sensing information and completes the actions of grabbing a feeding bottle, measuring milk powder and receiving water; when the two arms cooperatively work, the distance is monitored in real time to prevent collision, the grabbing and scraping actions are accurately controlled by virtue of feedback of a force sensor, and meanwhile, the rotating and shaking actions are dynamically adjusted by virtue of IMU (Inertial Measurement Unit) attitude compensation and vibration monitoring; the milk frothing device can efficiently and safely realize milk frothing.

Disclosed herein is a urine collection bag, system, and methods directed to automated measurement of a quantity of urine. The urine collection system can include the urine collection bag, a catheter, and flexible drainage tubing. The urine collection bag can include a collection area, force sensors, and circuitry configured to determine the volume of urine in the collection area based on pressure or weight measured by the force sensors, and the specific gravity of the urine. The catheter may include a small female external catheter (FEC) with an opening on a top side, a wicking catheter with a wicking area on a top side, a finger-mountable catheter, or a male external catheter (MEC). The tubing may be secured to a patient's leg with a stabilization device or a fabric strap. The catheter can remain on a patient while the patient stands or walks.

The invention discloses a preparation and measurement method of a polymer-based multi-point force flexible sensor for knee joint pose measurement, and relates to the technical field of polymer-based flexible sensors and soft measurement. The structure of the multi-point force polymer-based flexible sensor shaped like a Chinese character'ao 'is designed for knee joint stress and posture state measurement, and the flexible sensor is prepared and packaged through a silk-screen printing method. A flexible sensor strain input-output knee joint stress data mapping set and a flexible sensor strain input-pose angle output data mapping set required by modeling are completed through a flexible sensor, a thin film force sensor corresponding to multi-point force and an inertial sensor corresponding to pose angle measurement of installed multi-point force polymers. And establishing a neural network soft measurement model based on an MLP algorithm, and carrying out training and verification. And the knee joint pose angle with reliable precision and the maximum stress state of the knee joint are obtained. The sensor has the advantages of being flexible, thin, skin-friendly, high in sensitivity and stable in signal output.

The invention provides a coffee machine mechanical arm acceleration compensation control method and device based on toppling spill prevention, and relates to the technical field of mechanical arm control. A coffee machine calls a real-time acceleration sequence from an acceleration control library after receiving a real-time order, and a pipetting mechanical arm moves along a pipetting collision-free track in the process of clamping an order coffee cup to move along the pipetting collision-free track; the liquid gravity center offset is measured in real time through a six-axis force sensor integrated on a clamping jaw, and lagging shake offset of a real-time acceleration sequence is carried out according to the real-time gravity center offset. The technical problem that in the prior art, when a mechanical arm of a coffee machine transports coffee drinks containing heterogeneous liquid, the displacement control stability is insufficient, and pouring and scattering are likely to happen is solved. The technical effects that the coffee liquid is effectively prevented from spilling and leaking in the transportation process, the transportation stability of complex coffee drinks containing ice blocks, foam and the like is remarkably improved, safety and high efficiency of collaborative operation of the multiple mechanical arms are ensured, and the delay or overflow risk caused by liquid shaking is greatly reduced are achieved.

The invention provides a method for automatically centering and assembling a bearing on a long-axis part, and belongs to the technical field of bearing assembly.The method comprises the steps that position information of the long-axis part and the bearing is collected in real time through a binocular camera and a laser distance measuring sensor, a central line equation is calculated through the least square method, and position deviation is determined; a centering adjustment vector is generated to control a multi-degree-of-freedom precise attitude adjustment platform to perform preliminary adjustment, a mechanical arm is matched with high-precision laser ranging to perform precise centering, the centering process is modeled into a weighted undirected graph, an optimal adjustment path is solved, optimal press fitting parameters are calculated based on a bearing press fitting physical mechanics equation, and press fitting is performed. Meanwhile, the assembling process is monitored through a force sensor and a displacement sensor, an assembling quality evaluation matrix is constructed, finally, the assembling result is detected and evaluated, and high-precision automatic assembling of the long-axis part and the bearing is achieved.

According to the man-machine interaction system and method for robot training and data acquisition, a main device instruction system captures an operator hand posture generation instruction through a wearable sensor of an action acquisition subsystem, and meanwhile, the direction and strength information of force is transmitted by means of an annular vibration motor array of a tactile feedback subsystem; the data processing system is responsible for converting the attitude instruction into a mechanical arm control signal and processing feedback force data; the slave equipment responds to a multi-degree-of-freedom mechanical arm execution instruction of the system, and a force sensor collects environment interaction force data and transmits the environment interaction force data back; a robot self-learning module trains a diffusion model by using synchronously acquired time-aligned vision, trajectory and force feedback multi-modal data sets, a tactile feedback subsystem realizes force information transmission through single-motor direction mapping and PWM wave adjustment, and the self-learning module adopts DDIM to accelerate reasoning to generate an action sequence. And the autonomous operation capability of the robot in a complex scene is improved.

The invention discloses a compliance control method for a massage robot with a rigidity self-adaption function. The massage robot is composed of a six-degree-of-freedom mechanical arm, an end effector, a six-dimensional force sensor, a control host and other modules. The six-dimensional force sensor is installed at the tail end, the contact force of the robot and the surface of the human body can be collected in real time, tail end motion data obtained through the pose sensor is combined, the system executes a compliant control closed loop, and self-adaptive and safe massage operation is achieved. According to the method part, a force control closed loop can be constructed in real time, accurate, safe and smooth massage operation can be achieved through a force sensor installed at the tail end of the robot in combination with a smooth control algorithm based on displacement errors without depending on a visual system, meanwhile, massage area rigidity detection and self-adaptive control are achieved, and the user experience is effectively improved.

The invention relates to a pressure sensor (1) for detecting a leakage in a first separating membrane (8), with - a process adapter (6) with a membrane system (7) comprising the first separation membrane (8) and a second separation membrane (9), which are arranged such that the first separation membrane (8) faces the medium (24) and the second separation membrane (9) faces away from the medium (24) and a first intermediate space (10) is enclosed between the first separation membrane (8) and the second separation membrane (9), which has a vacuum, - a sensor unit (14) with a carrier (15), a second pressure sensor (16) and a communication unit (17), wherein the sensor unit (14) is attached to the pressure sensor (1) in a pressure-tight manner by means of the carrier (15) and is arranged such that the second pressure sensor (16) monitors the vacuum in the first space (10), wherein the second pressure sensor (16) and the communication unit (17) are electrically connected to each other and are arranged on a surface of the carrier (15) facing the vacuum.

The invention discloses an automatic spring steel wire forming device with a guide structure and a use method thereof, and relates to the technical field of spring forming, the automatic spring steel wire forming device comprises a wire feeding mechanism, a pre-straightening and online detection module, an active flexible guide module, a force feedback forming module and a central control system; the pre-straightening and on-line detection module, the active flexible guide module and the force feedback forming module are sequentially connected in series along a feeding path of a steel wire and are electrically connected with the central control system; a precise actuator controlled by the central control system is arranged in the active flexible guide module; and the force feedback forming module comprises a forming part and a force sensor connected with the forming part, and the force sensor is used for feeding back the real-time forming force in the forming process to the central control system. Through closed-loop control of online sensing, active guiding and force feedback, intelligent adaptation to steel wire parameter changes is achieved, the spring forming precision and consistency are remarkably improved, the equipment reliability is remarkably improved, and the service life of the equipment is remarkably prolonged.

The invention discloses a pressure injury risk early warning method and equipment, and relates to the technical field of medical monitoring instruments. The pressure sensor array layout can be self-adaptive to the body shape of a patient, a key osseous process part is covered, no monitoring dead angle is ensured, a temperature compensation mechanism is built in, environmental interference is reduced, the measurement precision is improved, an abnormal pressure threshold value can be dynamically set based on individual medical record data, data verification is performed before early warning is triggered, false alarm is avoided, and the array structure is light, thin and flexible. The mask is comfortable to fit skin, supports long-term wearing and is easy to disinfect and maintain; environment temperature and humidity parameters and pressure data are subjected to fusion analysis, the influence of a high-temperature and high-humidity environment on skin microcirculation can be recognized, the risk of pressure sores can be evaluated in an auxiliary mode, a calibration algorithm is built in a sensor, environment fluctuation interference is reduced, and data reliability is ensured; and the early warning unit comprises sound-light alarm equipment which supports a multi-stage alarm mode and is used for triggering an early warning signal and pushing information when the risk index exceeds a threshold value, so that the early warning timeliness is ensured and the false alarm risk is reduced.

The invention discloses a high-precision dynamic error real-time compensation method based on five-axis linkage, and relates to the technical field of machine manufacturing, and the method comprises the following steps: multi-source dynamic error perception: collecting geometric errors of a machine tool through a grating ruler, collecting temperature field distribution through an infrared thermal imager, and collecting cutting force disturbance through a piezoelectric force sensor; the method comprises the steps of constructing a grating ruler, constructing a thermal infrared imager, constructing a multi-source data acquisition system, carrying out nonlinear coupling modeling, and establishing a dynamic error model based on improved Volterra series, and has the advantages that the multi-source data acquisition system is constructed through the grating ruler, the thermal infrared imager and the piezoelectric force sensor, geometric, thermal and force multi-source dynamic errors are sensed synchronously, and the dynamic error detection accuracy is improved. The nonlinear coupling characteristic of the thermal-force-geometric error is accurately quantified by combining an improved Volterra series model and Lyapunov exponent analysis, the problem that a traditional single-source error model cannot accurately describe a complex error field is solved, and the accuracy of error prediction is remarkably improved.