210 results about "Vibration compensation" patented technology

The invention relates to the technical field of flow measurement calibration, in particular to a flow instrument intelligent calibration system based on multi-sensor fusion, which comprises a data acquisition unit, a deep coupling compensation unit and a closed loop verification unit, a data acquisition unit obtains a differential pressure value, an environment temperature, a pipeline pressure, a vibration frequency spectrum and sensor accumulated working time, a depth coupling compensation unit constructs an aging prediction model based on a Weibull distribution life model, and a temperature-pressure coupling equation and a vibration compensation mechanism are combined to obtain an aging real-time value and a time sequence deviation. Multi-parameter coupling characteristics are extracted through a neural network, an environment disturbance compensation coefficient matrix is constructed, a joint compensation amount is generated through dynamic weight distribution, a closed-loop verification unit optimizes model parameters, the problems that multi-source disturbance coupling analysis is insufficient and calibration precision is low in the prior art are solved, accurate calibration of a flow instrument under complex working conditions is achieved, and the calibration precision is improved. The metering stability is improved.

The invention provides a color steel plate coating flatness evaluation method and system based on artificial intelligence. According to the method, the three-dimensional point cloud data is generated by collecting the interference fringe image, and the surface fluctuation characteristics are quantified; capturing a multi-dimensional vibration spectrum of the transmission roller shaft, generating a servo motor compensation control signal, driving a multispectral scanning head to perform reverse displacement compensation, and generating real-time compensation data; inputting the surface topography features in the three-dimensional point cloud and the real-time compensation data into a lightweight convolutional neural network, and outputting fusion features; and dynamically classifying and identifying surface defects and uneven areas based on the fusion result, adjusting a classification threshold in combination with the speed of the production line, outputting a flatness evaluation result, and synchronizing the flatness evaluation result to a speed regulation system of the production line to realize closed-loop optimization. According to the method, laser interference, vibration compensation and lightweight AI technologies are fused, dynamic high-precision evaluation of the surface flatness of the color steel plate of the high-speed production line is achieved, and the problems of defect misjudgment and measurement distortion caused by vibration interference are solved.

The invention relates to the technical field of laser control, and provides a high-dynamic-range multi-channel laser interference control method and related equipment. Channel signals of a plurality of target channels are obtained in real time according to a plurality of preset photoelectric detectors, time domain-frequency domain-space three-dimensional sampling is performed on the channel signals to construct an original tensor, joint optimization processing is performed on the original tensor to obtain a noise reduction tensor, phase unwrapping is performed on the noise reduction tensor to obtain an absolute phase matrix, and the absolute phase matrix is subjected to noise reduction processing to obtain an absolute phase matrix. Performing dynamic range expansion on the absolute phase matrix to obtain an enhanced phase matrix, performing multi-wavelength calculation and environment compensation on the enhanced phase matrix to obtain a distance matrix, and performing vibration compensation on the distance matrix to obtain a piezoelectric driving signal. According to the channel laser interference control method, through a series of advanced algorithms and processing means such as multi-dimensional signal acquisition, combined noise reduction optimization, precise phase unwrapping, dynamic range expansion and vibration compensation, comprehensive improvement of laser interference measurement signals is realized.

The invention discloses a three-dimensional panoramic intelligent monitoring method and device for a coal conveying gallery, and relates to the technical field of industrial automation and intelligent monitoring, and the method comprises the steps: obtaining initial point cloud data and an initial multispectral image of the coal conveying gallery through a rotary laser radar, a high-dynamic-range camera and an infrared thermal imager; inertial measurement units are arranged in the devices to collect vibration data, and the vibration data are used for carrying out vibration compensation on point cloud and images to generate target point cloud data and target multispectral images; thirdly, performing three-dimensional modeling and multispectral texture mapping on the coal conveying gallery based on the data to obtain a target three-dimensional model; and finally, mapping equipment, personnel and environment data into the three-dimensional model in real time, displaying each piece of state information, and realizing comprehensive monitoring. According to the application, high-precision three-dimensional panoramic monitoring can be realized in a complex vibration environment of the coal conveying gallery, and the safety management level and the operation and maintenance efficiency of the coal conveying gallery are effectively improved.

The invention relates to the technical field of intelligent control, in particular to a numerical control lathe cutting precision optimization method and system for metal part machining, and the method comprises the steps: constructing a multi-mode key feature set with aligned timestamps; the initial compensation amount in the cutting feeding direction is obtained from the tool compensation lookup table; searching a corresponding historical cutting state from the processing state matrix, and inputting the key temperature distribution gradient of the cutter side, the key vibration absolute peak value of the lathe spindle and the corresponding historical cutting state into a weight coefficient model to obtain a temperature compensation weight and a vibration compensation weight of the current cutting state; calculating a dynamic correction factor, and correcting the initial compensation amount in the cutting feeding direction through the dynamic correction factor to obtain a cutting feeding direction compensation amount with a timestamp; the compensation rate of the cutting feeding direction compensation amount and the target feeding displacement under the same timestamp is calculated; and the cutting precision is optimized according to the comparison result of the compensation rate and the cutting key feeding relative deviation rate. And the requirements of high precision, low cost and fast response are met.

The invention discloses a shield attitude control method and system based on machine vision, and the method comprises the steps: constructing a motion state model of a shield tunneling machine according to the motion track of a feature point, and carrying out the prediction and correction of a motion state through a Kalman filtering algorithm, and obtaining the real-time attitude data of the shield tunneling machine; vibration data of the shield tunneling machine are obtained, the vibration data are obtained based on a vibration compensation model of an inertial measurement unit, the vibration data and visual sensor data are combined, a data fusion algorithm based on particle filtering is adopted to suppress vibration interference, and stable attitude information is obtained; and constructing a multi-modal data fusion model based on a graph convolutional neural network, and fusing the visual data, the inertial data and the motion state data to obtain a high-precision attitude estimation result.

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 a laser self-adaptive cutting method and system for a heavy special-shaped thickness steel pipe, and relates to the field of heavy special-shaped workpiece cutting technology application, and the laser self-adaptive cutting method comprises the steps that according to a collected surface image of a workpiece, the geometrical shape, surface defects and material texture features of the workpiece are recognized, and thickness distribution information of the workpiece is obtained; obtaining thickness data of different positions of the workpiece based on the thickness distribution information; based on the geometrical shape, the surface defect, the material texture feature and the thickness data, an optimal cutting path is obtained; and based on the optimal cutting path, a laser cutting task is executed, the laser power, the pulse frequency and the cutting speed are automatically adjusted according to the thickness change, and meanwhile, when vibration is detected, vibration is compensated through reverse excitation or dynamic damping adjustment. The key technical problems in heavy special-shaped workpiece cutting are solved, and the heavy special-shaped workpiece cutting device has wide industrial application prospects and extremely high popularization value.

The invention relates to the technical field of road defect detection, in particular to a road pit detection method and system, and the method comprises the following steps: S1, obtaining an original image flow of a road surface through a vehicle-mounted multispectral camera, and carrying out the motion artifact elimination to generate a vibration compensation image; s2, generating a shadow suppression image through asymmetric gamma correction; s3, adopting a dual-threshold connected domain analysis method to extract candidate pothole regions; s4, when the contrast difference value exceeds a texture mutation threshold value, determining that the area is a surface damaged area; s5, extracting a continuous pixel cluster statistical area proportion, and when the proportion is greater than 60%, determining that the feature is an effective pothole feature; and S6, calculating the minimum enclosing ellipse eccentricity rate and the ellipse area ratio, and generating a final pothole detection report. According to the method, through a multi-source information fusion and multi-stage feature extraction method, high-precision identification and standardized output of the pothole area in a complex road environment are realized, and the detection accuracy and the application reliability are improved.

The invention discloses a dynamic self-adaptive calibration method and device for hands and eyes of two arms of a robot. The method comprises the steps that calibration plates are fixed to the tail end of a left mechanical arm and the tail end of a right mechanical arm respectively, the mechanical arms are controlled through an automatic program to execute N times of translation and rotation movement in the view field of a camera, and calibration plate images are collected after each time of movement; based on the collected calibration plate image, the angular point position of the calibration plate is extracted, and the pose of the calibration plate in a camera coordinate system is calculated; and the pose of the calibration plate corresponding to each calibration plate image in the mechanical arm coordinate system is obtained, and the rotation matrix and the translation vector of the camera coordinate system and the mechanical arm coordinate system are solved. According to the technical scheme, the pose is corrected in real time through dynamic environment perception and vibration compensation, closed-loop re-projection error optimization and spiral / grid path planning are combined, high-precision robot double-arm hand-eye calibration is achieved, the environment interference calibration failure rate is reduced, and efficiency is improved.

The invention relates to the field of ocean engineering construction monitoring, and discloses a pile body penetration identification method based on multi-modal perception and dynamic coupling modeling, which comprises the following steps: collecting pile body motion data by deploying vision, inertia and laser ranging sensor networks, constructing a pile body-foundation dynamic model in combination with finite element discretization, and constructing a pile body penetration identification model; separating vibration interference and real displacement by using extended Kalman filtering; the YOLOv8 model is improved to realize pile body contour tracking in a low-illumination environment, and multi-source data is fused to predict a pile body motion state; the high-precision penetration is calculated through vibration compensation correction, weighted fusion and dynamic threshold judgment, and grading alarm and construction control instructions are triggered. According to the invention, the problems of low multi-sensor data fusion precision and weak anti-interference capability in a complex marine environment are solved, real-time monitoring and closed-loop feedback of the penetration of the pile body are realized, and reliable technical support is provided for piling construction.

The present invention discloses a laser metal curved surface automatic focus processing system and method thereof, including: a multimodal data fusion device, a curved surface detection module with a secondary tracking structure, integrated 3D structured light vision and vibration sensing equipment; a dynamic focus correction module, configured with an adaptive energy control unit and a beam shaping component; a nonlinear motion control console, including a six-degree-of-freedom parallel mechanism motion platform, and its servo control system integrates a time-space phase compensation algorithm; a core control unit, the core control unit has an embedded fusion algorithm model, and establishes a nonlinear mapping between material removal efficiency η and multivariable dynamic parameters. The processing quality level of the present invention is improved through the multi-source data fusion of 3D structured light and vibration sensing, the curvature recognition accuracy is improved, and the focus offset is reduced in combination with the axial vibration compensation mechanism, thereby effectively improving the processing quality.

The invention discloses an improved vibration compensation method suitable for an atom interference gravimeter. The method comprises the following steps: acquiring an atom interference signal and a vibration voltage signal output by a seismometer; initializing population parameters of the improved whale optimization algorithm, wherein the population parameters comprise a search space of a population size, a maximum number of iterations, a gain coefficient K and a delay coefficient tau; the method comprises the following steps: generating an initial whale population by adopting a method of combining Logistic chaotic mapping and Latin hypercube sampling LHS; calculating a phase shift caused by vibration noise and an atomic interference phase delta phi, and calculating the fitness of the whale individual by taking a root-mean-square error of compensated interference fringes as a target function; iteratively updating the population position through an improved whale optimization algorithm, outputting an optimal gain coefficient and an optimal delay coefficient, and obtaining an atomic interference signal after vibration compensation; according to the atomic interference gravimeter vibration compensation method, the global search capability, the local development precision and the stability of a vibration compensation algorithm are improved.

The invention discloses a 12-axis PCB drilling machine AGV path planning system with an intelligent obstacle avoidance function, and relates to the technical field of path planning, a first machine learning model of an AGV chassis steering angle and a first machine learning model of a mechanical arm shaft joint angle are obtained through training according to historical AGV operation parameters and simulated workshop operation parameters; identifying ground flatness compensation, vibration compensation, gravity center shift compensation and light influence compensation according to the real-time workshop parameters, determining a proportionality coefficient by using an optimal sequence diagram method, and further determining a second machine learning model; and a control instruction for AGV chassis steering and mechanical arm joint movement is generated based on the second machine learning model. Through multi-source data fusion, a dynamic compensation mechanism and machine learning optimization, the accuracy, the obstacle avoidance capability and the system robustness of path planning are improved, and efficient and safe execution of a PCB drilling task is ensured.

The invention discloses a monitoring system, belongs to the technical field of liquid level monitoring, and particularly relates to a hot well liquid level remote transmission monitoring system which comprises a signal acquisition unit, an automatic control unit and a cloud platform unit, and the signal acquisition unit is composed of a liquid level acquisition module and a visual module; the liquid level acquisition module and the visual module are used for double acquisition of liquid level values and data processing, filtering processing, temperature compensation processing and vibration compensation processing are carried out on two signals respectively, then data correction is carried out, stable and accurate reading data are obtained, meanwhile, the cloud platform unit is used for achieving real-time display of identification results, and the identification accuracy is improved. According to the system, unmanned and real-time monitoring of the boiler double-color liquid level meter is achieved, meanwhile, the recognition result is stable, and the safety of factory production is guaranteed.

The invention discloses an electronic scale with a dynamic compensation function, and aims to improve the weighing precision and stability, the electronic scale comprises a pressure sensor module, a dynamic compensation controller and a communication module, the pressure sensor employs an MEMS technology, and supports a 0-1000g measuring range; the dynamic compensation controller is internally provided with a temperature and vibration compensation algorithm, the weighing stability is ensured by collecting temperature and vibration data in real time and dynamically adjusting output signals of the sensor, the controller supports an automatic calibration mode, calibration is automatically conducted according to different weights, calibration data are stored, and the sensor module and the controller are connected through a four-core shielding wire. The controller and the communication module are integrated on the main control board, in addition, the controller supports multi-device ID management and Bluetooth wireless calibration, the long-term stability and high precision of the system are guaranteed, the relation between sensor output signals and the weight is optimized through linear regression and the least square method, it is guaranteed that the weighing result is accurate, and the weighing accuracy is improved. The electronic scale is widely applicable to industrial and precise weighing requirements.

Architectures and techniques are provided for improved vibration compensation for a boom lift-robot-mounted (BLMR) system, which can result in improved BLMR operating precision and safety at a reduced cost. Boom lifts typically contain extendable large-scale, variable-stiffness structures, subject to complex nonlinear static deformation and dynamic motion / gust-induced vibrations. Said vibrations can be compensated for at an end effector of a robot via a Jacobian-based vibration compensation via IMU (JVCI) procedure. The output of the JVCI procedure can rely on IMU feedback and can be combined with other vibration-mitigation techniques, including various feedforward techniques.

The invention relates to a data acquisition and analysis system and method for laser interference measurement, and aims to solve the problem of limited measurement precision caused by asynchronous signal acquisition, imperfect environmental interference compensation and algorithm errors of the existing system. The system comprises a photoelectric conversion unit, a signal conditioning unit, a high-speed synchronous acquisition unit, a real-time processing unit and an error compensation module. The photoelectric conversion unit adopts a four-quadrant PIN photodiode array to receive interference light signals and convert the interference light signals into analog electric signals; the signal conditioning unit performs gain adjustment and bandwidth limitation on the signal; the high-speed synchronous acquisition unit realizes femtosecond-level synchronous acquisition of signals; the real-time processing unit performs phase solution and eliminates harmonic errors based on an improved arc tangent algorithm; and the error compensation module fuses temperature sensor data and accelerometer data to realize thermal drift and vibration compensation.

The invention relates to a dam slope deformation monitoring method based on fusion of a measuring robot and a GNSS (Global Navigation Satellite System). The method comprises the following steps: performing signal synchronization and delay correction on a dual-mode observation pillar of a GNSS and a prism target of a measurement robot, and constructing a space-time reference network; controlling the measurement robot to emit an anti-interference laser pulse, counteracting environment vibration, and outputting a vibration compensation coordinate set; obtaining a dam slope displacement field through variable weight adaptive fusion processing; performing encryption scanning on an abnormal area exceeding a first deformation threshold in the displacement field to generate a polarization interferometric phase diagram, forming an adaptive data stream through three-stage dynamic classification coding, calculating a reference point drift component in combination with a dual-mode observation pillar, and extracting a net deformation set; and finally, mapping the net deformation set to a BIM model, constructing a color temperature gradient three-dimensional deformation situation map, triggering early warning for an area exceeding a second deformation threshold value, and generating a three-dimensional early warning map. According to the method, high-precision space-time unification of multi-source data can be realized, and the monitoring consistency and the anti-interference capability in a complex environment are remarkably improved.

The invention discloses an intelligent helmet control system based on an IMU (Inertial Measurement Unit), particularly relates to the field of riding monitoring, and is used for solving the technical problems that an existing intelligent helmet is high in collision misjudgment rate under strong road surface vibration and complex riding actions and is difficult to stably trigger a reliable rescue process. A helmet inertial measurement unit and a reference inertial measurement unit are respectively arranged on a helmet and a vehicle structural member, coordinate calibration and time synchronization are carried out, and a road vibration compensation model is constructed by using a frequency domain analysis result of the reference inertial measurement unit in a sliding time window. Road vibration and vehicle body vibration are separated from signals of the helmet inertial measurement unit, residual acceleration and angular velocity characteristics representing relative movement of the head are obtained, an accident confirmation signal is generated based on multi-threshold joint judgment, and a communication unit and a vehicle control interface are linked for execution.

The invention discloses a forking operation track generation method and device for a forklift, and the method comprises the steps: determining the pose of a target tray when the distance between the forklift and the target tray reaches a first distance; according to the target tray pose, the current fork tooth pose and the forking environment illumination intensity, the first pose deviation between the target tray and fork teeth is determined, and a first forklift linear speed and angular speed instruction is obtained through calculation; in the process that the forklift travels to the second distance, the ground friction coefficient and the vibration compensation amount are determined according to the friction-vibration joint estimation model and the first forklift linear speed and the first forklift angular speed; when the second distance is reached, determining a second pose deviation between the target tray and the prongs; and simulating the obtained parameters to obtain a second linear velocity and angular velocity instruction so as to complete the forking operation. Through rough adjustment and fine adjustment of the two distances, high-precision track planning of the forklift is achieved, and through calculation of the ground friction coefficient and the vibration compensation amount, the curve insertion precision of the tray is further improved.

The invention relates to the technical field of transmission shaft machining, and discloses an intelligent clamping method and system for universal joint transmission shaft machining. The method comprises the steps that the geometric dimension, the form and location tolerance number, vibration signal data, unbalance data and pressure distribution data of a transmission shaft are obtained; performing precision correction based on preset machining precision to obtain transmission shaft positioning parameters; adjusting parameters in real time through an adaptive control algorithm to obtain real-time positioning parameters; performing feature extraction to obtain vibration spectrum features; outputting a vector diagram to obtain an unbalanced vector diagram; performing Kalman filtering processing to obtain filtering parameters; calculating by adopting a fuzzy control algorithm to obtain a vibration compensation amount and an unbalance correction amount; performing data processing to obtain a corrected pressure matrix; inputting into a pre-trained neural network model to obtain a predicted risk level; and risk prediction and judgment are carried out, clamping strategy adjustment is carried out, a corrected clamping strategy is obtained, machining of the transmission shaft is carried out, and the machining accuracy is improved.

The invention discloses a rail-mounted robot inspection control method and system based on the Internet of Things, and relates to the technical field of robot inspection, and the method comprises the steps: carrying out the data collection based on a rail-mounted robot, synthesizing the rail width and rail slope data, calculating an accumulated cost value, and dynamically planning an inspection track; and collecting a vibration signal in track operation to calculate a vibration compensation amount. According to the method, through calculation of the dynamic balance load difference, the running stability and the track keeping capacity of the robot are guaranteed, through weighted fusion of a crack fault distribution probability curve and a wear trend chart, a comprehensive fault feature graph is constructed, multiple types of fault features are effectively unified, cracks and wear can be independently detected, and the fault detection efficiency is improved. And for fault points extracted from the comprehensive fault feature map, feature mean values and standard deviations of cracks, wear and composite faults are calculated respectively, and a fault classification probability is generated based on a classification Gaussian model, so that the accurate classification capability of a multi-fault area is enhanced.

The invention discloses a wafer carrier size laser measurement device, and relates to the technical field of laser measurement, the wafer carrier size laser measurement device comprises a measurement platform mechanism, the measurement platform mechanism comprises a mounting table, the front surface of the mounting table is provided with a control terminal, and the top of the inner cavity of the mounting table is fixedly connected with a mounting rack; and the surface of the mounting frame is fixedly connected with a first motor. According to the invention, through the arrangement of the horizontally distributed self-adaptive nodes, flexible deployment is realized by utilizing a magnetic attraction structure, and the electric telescopic rod and the silica gel contact head are matched, so that complex curved surfaces such as a three-dimensional buckle and a deep groove of a carrier can be attached in a self-adaptive manner; a vertical plane and a concave structure which are difficult to detect by a traditional device can be subjected to multi-angle scanning, a measurement blind area is thoroughly eliminated, the coverage rate of three-dimensional size detection is remarkably increased, meanwhile, a temperature and vibration compensation model is built in an intelligent compensation algorithm module integrated by a control terminal, and the influence of environmental factors on a measurement result is corrected in real time.

The invention discloses an optical fiber positioning method and system based on an environment compensation vector algorithm model. The method sequentially comprises the steps that a quantitative impact hammer is selected, and a distributed vibration sensor is calibrated; collecting vibration vectors of the optical fiber measurement points in different environments; learning the environment compensation vector algorithm model, and determining a vibration compensation vector and a burial depth prediction formula; a quantitative impact hammer is used on the spot to hit the ground along the optical fiber and the trend, and the optical fiber burial depth and the trend are calculated through an environment compensation vector algorithm model. The system comprises a quantitative impact hammer, a distributed vibration sensor, an environment compensation vector algorithm model mobile terminal APP and an optical cable routing management system. According to the invention, measurement errors caused by environmental factors are effectively corrected, so that the optical fiber positioning method and system can still maintain high precision in a complex and changeable environment, and the positioning reliability is remarkably improved; through cooperation among different facilities, a systematic solution is provided for communication optical cable measurement.

The embodiment of the invention discloses a self-propelled hyperspectral imaging control method and system. The method comprises the following steps: based on an ultra-wideband wireless multilateral positioning method, acquiring ultra-wideband positioning information corresponding to a self-propelled hyperspectral imaging platform, and acquiring relative positioning information and a platform high-frequency vibration signal; based on a Bayesian fusion method, carrying out weighted fusion processing on the ultra-wideband positioning information and the relative positioning information; obtaining deformation data corresponding to the platform based on strain gauges arranged at a plurality of key positions of the platform; and according to the fused positioning information, the deformation data and the high-frequency vibration signal of the platform, performing adaptive closed-loop control on the platform so as to complete path correction of the platform, structural deformation offset, intelligent damping design between a vibration sensor and a pneumatic tire, and vibration compensation processing on a hyperspectral imaging module of the platform. According to the embodiment of the invention, the imaging precision is improved while the navigation positioning precision is improved.

The invention relates to the technical field of power systems, in particular to a dynamic calibration method and system for multi-physics field data fusion of an oil-immersed transformer, and the system comprises a data calibration unit which carries out the dynamic calibration of the multi-physics field data of the transformer through a cross-physics field coupling calibration model, and evaluates the calibration effect based on an objective function; wherein the multi-physical field data comprises temperature data, vibration data, UHF signal data and gas data; the cross-physics field coupling calibration model comprises establishment of a temperature-vibration compensation equation and a gas-UHF trigger mechanism; according to the method, data fusion is carried out on multiple sensors, dynamic calibration is carried out by adopting a cross-physics field coupling calibration model, an edge GAN generates an adversarial sample, updating of the cross-physics field coupling calibration model is triggered in combination with confidence, and comprehensive characteristic parameters are intelligently analyzed by a hierarchical fusion architecture based on a Shapley value. The health state of the transformer can be accurately judged, and the accuracy of fault diagnosis is improved.

The invention discloses a mechanical arm vision distance measurement method and a distance measurement system thereof, and relates to the technical field of intelligent vision perception, a camera is installed on a mechanical arm to collect images, and through an optimization matching algorithm, the images shot by the left eye and the right eye are rapidly compared to generate a clear and accurate disparity map; the motion state of the mechanical arm is detected in real time through a vibration compensation mechanism, a shot image is corrected, and it is ensured that the distance measuring process is stable and reliable; and in combination with the corrected disparity map, the accurate distance from the target object to the camera is obtained by utilizing a depth calculation formula, and the result is transmitted to a control system of the mechanical arm. The depth value is fed back to the mechanical arm controller in real time through depth calculation and linkage with a control system, the precision of dynamic path planning and action execution of the mechanical arm is improved, and the mechanical arm shows higher anti-interference capacity in a dynamic vibration environment.

The invention relates to the technical field of injection molding automatic feeding, in particular to an automatic nut feeding machine which comprises a sorting table, a vibration disc, a trough and an adsorption assembly. The vibration disc is fixedly installed in the middle area of the sorting table and used for containing nuts of different models. The vibration disc comprises an upper-layer vibration disc and a lower-layer vibration disc; a connecting assembly is arranged between the upper-layer vibration disc and the lower-layer vibration disc and used for detachably connecting the upper-layer vibration disc to the lower-layer vibration disc. A vibration compensation assembly is arranged on the upper-layer vibration disc and used for enhancing the vibration frequency of the upper-layer vibration disc, and the upper-layer vibration disc and the lower-layer vibration disc conduct vibration arrangement on nuts of different sizes. The adsorption assembly is arranged at the edge position of the sorting table and used for conveying the nuts of different models in the material groove. The material groove is fixedly installed in the middle area of the sorting table and used for containing the nuts arranged in a vibrating mode. The problem that the occupied space is large when different vibration discs work at the same time is solved.

The invention discloses a novel double-crystal-configuration overpressure sensor with a vibration compensation function. Based on a vibration interference arrival end compensation thought, a set of compensation sensitive element assembly is added on the basis of a traditional piezoelectric pressure sensor, a compensation sensitive element which is the same as a sensor main sensitive element in material and size and opposite in placement direction is adopted, and charges generated by vibration impact are sensed synchronously; the method is used for counteracting vibration spurious charges generated when a main sensitive element is interfered by flat plate vibration, compensation of vibration interference is achieved, and the test precision of shock wave pressure signals is improved.