178 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 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 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 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.

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 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 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 relates to the technical field of laser cutting, in particular to an automatic control method and system for laser cutting, and the method and system achieve the automatic control of laser cutting through the key technologies of multi-source data fusion, intelligent path planning, vibration compensation, parameter optimization and the like. Full-process automatic control from data collection to final cutting effect evaluation is achieved, and the precision and efficiency of laser cutting are remarkably improved.

The invention relates to a method and a system for adaptively adjusting vibration compensation of an unmanned aerial vehicle based on a multi-band IMU (Inertial Measurement Unit), and the method comprises the steps: W1, in the process that the unmanned aerial vehicle executes a flight task, cooperatively collecting data information of vibration signals of an unmanned aerial vehicle structure based on a plurality of airborne vibration detection IMU arrays, and constructing an unmanned aerial vehicle vibration spectrum analysis model, and calculating the body dominant vibration frequency of the unmanned aerial vehicle to obtain the data information of the body dominant vibration frequency of the unmanned aerial vehicle, and optimizing the acceleration and angular velocity of the unmanned aerial vehicle by adopting an improved weighted average optimization algorithm based on dynamic fusion weight to obtain the optimized data information of the acceleration and angular velocity of the unmanned aerial vehicle. According to the method, the problem of measurement distortion of a single IMU in a resonance frequency band is effectively avoided, it is ensured that high-fidelity inertial data can be output under all working conditions such as low-frequency maneuvering, intermediate-frequency cruising and high-frequency disturbance, and the method can be deployed on a mainstream unmanned aerial vehicle platform and has good popularization value.

The invention relates to the technical field of electric connector weak light assembly vibration compensation alignment methods, particularly discloses an electric connector weak light assembly vibration compensation alignment method, and aims to solve the problems of low electric connector assembly positioning precision and high pseudo soldering rate caused by vibration in a weak light environment. The method comprises the following steps: monitoring the thermal radiation change of a vibration source in real time through an infrared thermal imaging sensor, and pre-judging a vibration acceleration vector in combination with a lightweight long-short-term memory neural network; synchronously triggering dual polarization angle imaging to respectively capture a housing reference mark and an enhanced terminal metal feature; the vibration data and the polarization image flow are fused in the field programmable gate array, a self-adaptive optical flow algorithm is adopted to resolve the displacement compensation amount, and a piezoelectric ceramic actuator is driven to carry out submicron order reverse displacement compensation; when the compensation amount exceeds a threshold value, a low-delay correction instruction is sent to the robot through an Ethernet control automation technology bus, and the steady-state error is ensured to be smaller than 0.3 micrometer by combining a strain gauge fine tuning feedback loop. According to the technical scheme, the assembling precision, efficiency and production line adaptability are remarkably improved.

The invention discloses a linear friction welding machine vibration compensation control method based on iterative learning, and the method comprises the steps: collecting a vibration signal of an electro-hydraulic servo vibration system of a linear friction welding machine in a welding process, determining a vibration amplitude, frequency and vibration center deviation, and when the vibration amplitude or the center deviation exceeds a preset threshold value, starting the linear friction welding machine; the controller starts vibration compensation control; an electro-hydraulic servo vibration system model is established, the rigidity characteristic and the dynamic load change of the system are comprehensively considered, an iterative learning control law of a controller is designed, and control convergence conditions are analyzed to ensure the stability and the high efficiency of control; based on the output of the controller, the error trend of the vibration signal is predicted in real time in combination with historical iteration data, and a feed-forward control signal is generated through a feed-forward compensation mechanism to adjust the vibration signal error in advance. According to the method, the iterative learning is applied to the vibration compensation control of the linear friction welding machine, so that the precise compensation of the vibration signal is realized.

The invention relates to the technical field of motor control, and discloses a bearingless composite rotor cage type asynchronous motor vibration real-time compensation control method, which comprises the following steps: acquiring and preprocessing a rotor displacement signal to obtain a filtered displacement signal; processing the filtered displacement signal based on a second-order generalized integrator, and extracting a fundamental frequency harmonic component synchronous with the mechanical angular velocity of the rotor; adopting a simplified LMS algorithm to dynamically optimize the amplitude weight and the phase weight of the compensation force, and generating a feedforward compensation force according to the optimized weights; a two-channel control framework is constructed, and total control force is synthesized; the suspension force winding is driven by the inverter to generate corresponding radial suspension force, so that unbalance vibration of the rotor is counteracted; according to the invention, the second-order generalized integrator harmonic observer is adopted to realize high-precision extraction of the fundamental frequency component, and the mechanical angular velocity change of the rotor can be tracked in real time in cooperation with a frequency adaptive adjustment mechanism.

The invention relates to a commodity quality multi-dimensional detection method and device, equipment and a medium. The method comprises the following steps: acquiring environment data and commodity appearance image data in real time through a sensor and a camera deployed in a commodity transportation environment; performing clock synchronization and vibration compensation processing on the environment data to obtain environment data after synchronous compensation; performing spatial-temporal feature fusion processing on the sensor data and the commodity appearance image data after synchronous compensation to obtain a fusion feature vector; calculating a commodity recessive deterioration probability value based on the fusion feature vector in combination with commodity physiological metabolism characteristics; and generating a multi-dimensional quality inspection result based on the commodity recessive deterioration probability value in combination with the environment data and the commodity appearance image data. By the adoption of the method, efficient collaborative collection of multiple sensors can be achieved in a dynamic environment, recessive degradation caused by microbial activity or water loss in the fresh goods is captured, and multi-source heterogeneous data is fused into a unified fresh goods quality detection result.

The invention relates to the technical field of equipment calibration, and discloses a collaborative directional calibration method and system, electronic equipment and a storage medium, and the method comprises the steps: obtaining the circumferential strain distribution data of a drill rod, and extracting the amplitude-frequency characteristics of a dominant vibration mode and the phase offset of an associated coupling vibration mode; generating an amplitude compensation coefficient according to the amplitude-frequency characteristics, generating a time-varying phase compensation factor in combination with the phase offset, and generating a dynamic vibration compensation parameter based on vibration energy distribution dynamic weighted fusion; based on a pre-trained nonlinear phase distortion compensation model, inputting a dynamic vibration compensation parameter and then outputting a gyroscope angular velocity signal after phase correction; performing vibration interference frequency band suppression processing on the accelerometer signal, and outputting the processed accelerometer signal; and performing iterative optimization on the corrected angular velocity signal and the processed accelerometer signal, and outputting a directional calibration result in combination with filtering smoothing processing. According to the invention, high-precision cooperative calibration of the inertial sensor in a multi-mode mechanical vibration environment can be realized.

This application relates to a six-axis CNC machine tool for achieving precision burr control. The six-axis CNC machine tool includes: a workpiece fixing device for placing the workpiece to be machined; a machining tool kit including a tool holder and a machining tool arranged on the tool holder; a vibration sensor disposed at the tool clamping point for acquiring vibration signals from the machining tool when it cuts the workpiece; a drive controller for controlling the machining tool kit and the workpiece fixing device to collaboratively execute cutting actions; and a processor communicatively connected to the vibration sensor and the drive controller, configured to: acquire the vibration signals from the machining tool; generate a vibration compensation signal based on the vibration signals, wherein the vibration compensation signal has the same amplitude, opposite phase, and the same frequency as the vibration signal; and send the vibration compensation signal to the drive controller to adjust the cutting actions. The solution provided in this application can accurately suppress burr generation when cutting the workpiece.

The invention relates to the technical field of mine material metering, and particularly discloses a mining conveyor belt coal flow intelligent metering method and device based on sub-pixel-level light bar center extraction. According to the method, an infrared laser is adopted to construct a light plane on the coal flow surface above a conveying belt, and a grating sensor camera is adopted to collect light plane deformation light strips on the coal flow surface; a dust scattering compensation model is innovatively provided, and sub-pixel-level light strip center extraction is achieved; correcting point cloud coordinates in real time in combination with vibration compensation, and converting light strip pixel coordinates into coal flow surface point clouds based on a three-dimensional reconstruction technology; the coal flow sectional area and the belt speed output instantaneous flow are calculated through fitting of a conveyor belt reference surface and integral calculation; aiming at the technical defects of dust interference, much vibration, sensor data fusion failure and the like existing in a traditional monitoring technology in a high-dust and strong-vibration environment of an underground coal mine, the laser is combined with a grating visual sensor, the dust penetration rate is increased, and high-precision coal flow measurement is performed by using a non-contact more scientific and reasonable method.

The embodiment of the invention is suitable for the technical field of gas detection, and provides a control method of gas detection equipment and unmanned aerial vehicle-mounted gas detection equipment, the gas detection equipment is carried on an unmanned aerial vehicle, and the method comprises the following steps: in the process that the unmanned aerial vehicle flies in a detection area, the unmanned aerial vehicle carries out detection on the detection area; collecting sensing data through a plurality of sensors deployed on the gas detection equipment; based on the sensing data, monitoring motion state information of the gas detection equipment and gas concentration information of target gas in the detection area; according to the motion state information, the gas detection equipment is controlled, and the motion state information is used for determining a vibration compensation signal of the gas detection equipment. Through the method, when the gas concentration is detected through the unmanned aerial vehicle, the stability of the gas detection equipment can be kept, so that the accuracy of the detected gas concentration is improved.

The present application belongs to the technical field of metallurgical equipment intelligence, and provides a strip steel transverse flatness measurement method and system based on multiple laser vision sensors, comprising: sequentially installing a laser speed measuring instrument, a first set of laser vision devices, a second set of laser vision devices and a third set of laser vision devices on a support above a strip steel roller, and collecting laser stripe images on the surface of the running strip steel; performing ROI region processing on the laser stripe images to identify the laser stripes in the laser stripe images; using a gray center of gravity method to extract the center coordinates of the laser stripes, and using a least squares method to fit the center coordinates to obtain a fitting equation; performing vibration filtering on the fitting equation, setting a vibration compensation term, calculating the strip steel transverse flatness, and adjusting the equipment parameters of the rolling mill and the straightening machine and the placement position of the flattening machine pad based on the strip steel transverse flatness. The present application realizes high-precision dynamic detection of the flatness of the strip steel.

The invention relates to the technical field of image data processing, in particular to a processing parameter monitoring method and system for wire harness terminal production, and the method comprises the steps: obtaining continuous multi-frame images in a wire harness terminal crimping process; calculating the initial sectional areas of the wire harness conductor and the crimping wing in the crimping area of any image; respectively performing temperature compensation and vibration compensation on the initial sectional areas of the wire harness conductor and the crimping wing to obtain the actual sectional areas of the wire harness conductor and the crimping wing, and calculating the compression ratio of the wire harness terminal in the crimping area based on the actual sectional areas of the wire harness conductor and the crimping wing; adjusting the crimping force according to the compression ratio by using a PID control model; and evaluating the crimping quality of the wire harness terminal based on the compression ratio. The sectional area is dynamically calibrated by introducing temperature compensation and vibration intensity, quality misjudgment caused by only depending on pressure data is avoided, the crimping force is adjusted in real time through the PID control model, pressure output is dynamically optimized according to the crimping state, and it is ensured that the crimping process is stable and accurate.

The application provides a steel plate shape measurement calibration method, belongs to the field of three-dimensional shape measurement and calibration, and aims to realize three-dimensional reconstruction and shape measurement of a steel plate surface. In order to realize high-precision detection of the plate shape, the application obtains X, Y and Z coordinate data of the steel plate surface through a double-line laser measurement system. The measurement system is composed of multiple cameras and two line lasers, the installation positions of the cameras are determined to ensure that the cameras have a certain overlapping field of view, so that the data can be spliced. In the measurement process, the image captured by the camera is processed, the position information of the laser line in the image is extracted, the pixel coordinates are converted into actual world coordinates according to the calibration parameters and the working distance of the camera, and the X, Y and Z three-dimensional coordinate data of the steel plate surface are obtained. Vibration compensation is carried out in the measurement process to ensure the accuracy and stability of the measurement result.

The present application relates to the technical field of unmanned aerial vehicle photoelectric load vibration control, and particularly relates to a multi-frequency band vibration compensation control method for an unmanned aerial vehicle airborne photoelectric platform based on a disturbance observer, comprising: obtaining unmanned aerial vehicle task phase information, synchronously collecting piezoelectric sensing signals and fiber grating sensing signals, performing time-frequency domain feature fusion and generating a composite feature description in combination with the task phase information; performing mode classification on the current disturbance based on the composite feature description and selecting a corresponding compensation algorithm, predicting the disturbance trend according to the task phase information and activating the compensation algorithm in an event-triggered manner by scheduling computing resources; obtaining an optical axis residual error and a deviation between an actual disturbance and a predicted disturbance, modifying time-frequency domain feature fusion parameters and mode classification discrimination boundaries based on the optical axis residual error, and modifying feature library parameters of the task phase information and a trigger threshold of event-triggered scheduling based on the deviation. The present application realizes adaptive and accurate suppression of wide-frequency band disturbances and improves long-term operation reliability.

The invention provides a fresh flower harvesting trolley based on stalk adaptive cutting and vibration compensation, and relates to the field of agricultural automatic picking, and the fresh flower harvesting trolley comprises a rack (10), a moving mechanism (20), a harvesting self-balancing mechanism, a platform (40), a guide rail sliding table mechanism, a retractable picking mechanical arm mechanism, a tail end cutting mechanism, a storage mechanism and a binocular camera, the bottom ends of the four corners of the rack (10) are each provided with a set of moving mechanism (20). The four harvesting self-balancing mechanisms are sequentially arranged at the four corners of the top end of the rack (10), and the top ends of the harvesting self-balancing mechanisms are connected with the bottom face of the platform (40). The guide rail sliding table mechanism is arranged on the end face of the platform (40) and located in the middle of the platform (40) and provided with the retractable picking mechanical arm mechanism, and the tail end cutting mechanism is arranged at the bottom end of the retractable picking mechanical arm mechanism. According to the harvesting trolley, high-precision positioning and high-success-rate cutting of various fresh flowers can be achieved, and the picking efficiency and the quality of the picked fresh flowers are improved.