48 results about "Vector decomposition" patented technology

The invention relates to the technical field of automatic laying of composite materials, in particular to an automatic compensation method, system and equipment for errors between silk laying belts and a storage medium. The method for compensating the error between the automatic silk laying belts comprises the following steps: establishing a mathematical mapping relation between the error compensation amount between the belts and robot control parameters through a standard sample piece laying test, and forming an error compensation theoretical model; the method comprises the following steps: aiming at a robot type fiber placement machine structure, constructing an inter-band error model based on pose kinematics modeling, robot and additional axis multi-axis interpolation modeling and error vector decomposition; the tail end target position, the attitude angle and the error compensation amount in the laying program are read in real time, and real-time control input is obtained; and on the basis of the error model, the corrected tail end position is inversely solved into a real-time adjustment angle of each joint, a robot inverse solution algorithm is corrected, and a joint control instruction is generated. According to the automatic tow belt laying device, the laying position precision of the automatic tow belt laying can be remarkably improved.

The invention provides a three-dimensional flow velocity field inversion method and system based on coherence-assisted SAR adaptive offset tracking, and a storage medium, so as to improve the problem of decoherence caused by time heterogeneity in a synthetic aperture radar interferometry (InSAR) technology, and relates to the technical field of electric power engineering geological disaster monitoring. The method comprises the following steps: establishing a space-time baseline network between SAR images; obtaining coherence data after geocoding; selecting a pair of SAR images from the space-time baseline network as a reference unit, calculating an offset result through a pixel offset tracking technology for the reference unit, and determining an optimal matching window parameter of the reference unit; establishing a mapping function between coherence and optimal matching window parameters; according to the established mapping function, calculating an optimal matching window parameter of each remaining SAR image pair; and in combination with the line-of-sight average deformation rate fields of the ascending and descending rails, inverting a surface three-dimensional flow velocity deformation field of the target area through a geometric vector decomposition model.

The invention belongs to the technical field of electric power measurement, and discloses a calibration method and system of an intelligent measurement switch and a multi-switch synchronous measurement method, and the method comprises the steps: obtaining voltage and current waveform data of the intelligent measurement switch under a nonlinear load condition, and extracting a frequency spectrum feature matrix of the voltage and current waveform data; constructing an amplitude-phase coupling error model representing a nonlinear incidence relation between amplitude fluctuation and phase deviation, inputting the spectrum characteristic matrix into the amplitude-phase coupling error model, and calculating an amplitude-phase coupling error vector; performing vector decomposition on the amplitude-phase coupling error vector, and separating out an in-phase component error and an orthogonal component error; and generating a calibration compensation coefficient according to the in-phase component error and the orthogonal component error, and performing vector calibration on the intelligent measurement switch, thereby improving the calibration precision of the intelligent measurement switch.

The invention discloses a symbol coding and vector decomposition method based on a super-dimensional calculation model, and belongs to the technical field of neural symbol models and super-dimensional calculation. According to the method, a symbol coding method is used, and an embedding space of additional information is added in coding, so that representation of multiple subclass levels is supported; an efficient decomposition method is designed, redundant classes are selectively eliminated by identifying labels of target classes, the anti-noise capability and mathematical characteristics of super-dimensional vectors are fully utilized, the calculation efficiency and accuracy when multiple objects with class-subclass relations are expressed and decomposed are remarkably improved, and the method is suitable for large-scale popularization and application. And the limitation of an existing super-dimensional calculation model is overcome.

The invention discloses a lightweight bridge and dynamic task vector federated multi-task learning method, which comprises a federated learning system, the system comprises a plurality of clients and a central server, and the method comprises the following steps: 1) initialization and distribution; 2) performing local training and processing on the client; 3) performing dynamic task vector decomposition and compression transmission; 4) aggregation and reconstruction of the central server side; and 5) updating and issuing the model. According to the method, the communication efficiency is improved in order of magnitude, the communication bottleneck is relieved fundamentally, the personalized performance of the model is remarkably enhanced and exceeds that of an existing baseline method, inter-task interference is effectively restrained, training stability and convergence are improved, excellent balance between communication overhead and calculation / personalized performance is achieved, and good adaptability and robustness are achieved.

The invention provides a second-hand vehicle data set construction method and device based on data governance and a storage medium, and the method comprises the steps: obtaining an original vehicle description text in a second-hand vehicle transaction scene, carrying out the text cleaning and standardization processing, obtaining a to-be-processed vehicle description text set, carrying out the event unit extraction of the to-be-processed vehicle description text set, and obtaining a to-be-processed vehicle description text set; the method comprises the following steps: identifying and extracting event units containing operation behaviors and state changes in a to-be-processed vehicle description text set, performing double-base vector decomposition processing on each event unit to obtain double-base vectors, embedding the double-base vectors into a preset three-dimensional event space, detecting the double-base vectors in the three-dimensional event space, and obtaining a vehicle description text set; and identifying and correcting the event units with contradictions, generating a correction vector set for eliminating the contradictions, projecting the correction vector set to a preset second-hand vehicle valuation model data field space, and generating a structured data unit aligned with the second-hand vehicle valuation model data field space.

The method for quickly inverting aircraft wake vortex parameters based on mobile platform laser remote sensing comprises the following steps: a laser radar system scans a wake vortex influence area, and measurement data are subjected to quality control processing; a wake vortex core position and a vortex core radius are estimated; a wind speed of an arbitrary measurement point A located in the wake vortex range is subjected to vector decomposition, and the wind speed is expressed as a function of a wake vortex circulation parameter W 、 V 、 U A background wind speed and a laser radar motion speed are eliminated by using a non-wake vortex area measurement point; a difference between radial velocities of two measurement points in and out of a wake vortex influence range in the same laser emission direction is expressed as a function of a wake vortex circulation; and a turbulent disturbance is weakened by multiple measurements in the wake vortex influence range, and then a least square method is used to fit and solve the wake vortex circulation. The present application can accurately invert and correct aircraft wake vortex parameters by using less observation data. The calculation result is fast and accurate, and can provide scientific and reliable data support for aviation safety and aircraft cooperative operation.

The invention provides a synchronous modulation phase alignment method and device, and belongs to the technical field of motor operation control. The method comprises the steps that when phase deviation is larger than a set deviation threshold value, a second phase alignment mode is started, and the output frequency of actual output voltage is equal to the expected frequency of expected output voltage; determining a plurality of sampling points according to a preset selection principle; recording an angle between two adjacent output vectors in synchronous modulation as shown in the specification, recording an angle between output vectors in an adjustment process as shown in the specification, and recording an angle deviation between an adjustment starting vector and an adjustment ending vector as shown in the specification; determining the number of intermediate vectors according to the adjustment ending vector and the carrier direction of the jump point; obtaining the duration of the vector through vector decomposition; determining a carrier direction according to a carrier diversity principle, and determining a clamping mode according to sector division; and determining a vector arrangement sequence according to the carrier direction and the clamping mode. In this way, no deviation exists between the output vector and the expected vector in the adjusting process, and the adjusting speed is increased.

The invention discloses a moving track prediction method and a related device, which are applied to scenes such as artificial intelligence and games. The method comprises the steps of representing object state information, game environment information and game task information and features associated with a target object in a first target time period in a target game as object state features, game environment features and game task features; performing hybrid coding to obtain a prediction output vector of the target object in a second target time period after the first target time period in the target game; and decomposing each prediction output vector into a prediction mean vector, a prediction standard deviation vector and a prediction probability vector so as to accurately determine a prediction moving track of the target object in the second target time period in the target game. Even if the movement track of the player in the game is very complex, the method can accurately predict the movement track of the player in the game in the future time period, so that the prediction effect of the movement track in the game is improved.

The application provides a synchronous modulation phase alignment method and device, and belongs to the technical field of motor operation control. The method comprises the following steps: when the phase deviation is greater than a set deviation threshold, a second phase alignment mode is started, and the output frequency of an actual output voltage is equal to the expected frequency of an expected output voltage; a plurality of sampling points are determined according to a preset selection principle; the angle between two adjacent output vectors of the synchronous modulation is denoted as, the angle between the output vectors in the adjustment process is denoted as, and the angle deviation between the adjustment starting vector and the adjustment ending vector is denoted as; the number of intermediate vectors is determined according to the carrier direction of the adjustment ending vector and the jump point; the duration of the vector is obtained through vector decomposition; the carrier direction is determined according to the carrier difference principle, and the embedding mode is determined according to the sector division; and the arrangement sequence of the vector is determined according to the carrier direction and the embedding mode. In this way, there is no deviation between the adjustment process output vector and the expected vector, and the adjustment speed is accelerated.

The invention provides a federated learning robust aggregation method and system for resisting backdoor attacks, and belongs to the technical field of network and information security. The method comprises the following steps: acquiring model update vectors submitted by a plurality of clients, and decomposing the model update vectors into a plurality of hierarchical update data according to the hierarchical relationship of a global model; according to each hierarchy update data of each client, extracting a multi-dimensional feature of the client; determining a global total abnormal score of the client according to the multi-dimensional features of the client; and calculating a comprehensive reputation of the client according to the global total abnormal score, determining an aggregation weight according to the comprehensive reputation, aggregating updating data of each level of the client according to the aggregation weight, and updating the global model. According to the method, the attack success rate of malicious updating can be remarkably reduced, and the method has the advantages of better robustness and safety.

The invention provides a multi-level vector index construction method, a customer service scene image retrieval method and electronic device.The method comprises the steps that image vectors corresponding to customer service scene image data are obtained, the image vectors are decomposed into sub-vectors, sub-vector codebooks corresponding to the sub-vectors are constructed, and the sub-vector codebooks correspond to the customer service scene image data; obtaining an original code word index sequence corresponding to each image vector; and constructing a coarse index structure based on each original code word index sequence to obtain each cluster, and constructing a fine index structure based on each cluster to obtain a multi-level vector index structure. The problems that an existing image retrieval method is single in index structure, low in retrieval speed, difficult to balance the speed and precision and the like can be effectively solved.

The invention provides an article automatic identification method and system based on X-ray imaging and artificial intelligence, and the method comprises the following steps: obtaining dual-energy X-ray data of an article, and constructing the dual-energy X-ray data into a potential energy field model containing elevation and texture; determining a core aggregation region of each independent object in the model through gradient flow analysis, and segmenting the core aggregation region into a plurality of independent sub-regions based on a texture heterogeneity index; and carrying out vector decomposition on pixel points which generate signal aliasing due to vertical overlapping in the sub-regions by utilizing a preset material end member vector library so as to separate and reconstruct independent feature data of each material layer. And inputting each sub-region after feature reconstruction into an artificial intelligence model for category determination, and outputting a final identification result. According to the method, the technical problem of low article identification accuracy caused by the fact that a traditional AI model cannot identify composite features generated by signal superposition is solved.

A method for calculating the levelness of a mirror plate during the turning process involves first obtaining the azimuth and levelness of the mirror plate through vector decomposition, then adjusting each support bolt to level the mirror plate, then obtaining the axis adjustment scheme after the mirror plate is leveled, and finally obtaining the rotation center adjustment scheme after obtaining the axis adjustment scheme.

The application discloses an egg circle type scanning laser radar wave refraction correction error correction method, belongs to the technical field of airborne laser depth sounding, and is used for wave refraction correction of underwater terrain measurement of an airborne laser radar and comprises the following steps: filtering and processing sea surface point clouds by adopting a statistical outlier removal filtering method; extracting a sea surface slope normal vector corresponding to each point by adopting an optimized moving least square method; simplifying an egg circle type scanning laser radar measurement process to be carried out in a carrier coordinate system; constructing a refraction correction model by using Snell's law and a vector decomposition method; and obtaining corrected sea bottom point cloud coordinates. The application removes noise from sea surface point cloud data, fits the measured sea surface point cloud by using a moving least square method, adopts characteristic decomposition of a covariance matrix instead of polynomial fitting, and thus, the calculation is simple, polynomial fitting errors are avoided, the process is greatly simplified by using vector decomposition calculation, and there is only a single solution.

The application discloses a ship fuel consumption prediction and correction method based on AIS and marine environment data, and relates to the technical field of ship fuel consumption prediction, and comprises the following steps: acquiring AIS dynamic data of a target ship and constructing a continuous navigation state sequence; acquiring wind speed, wind direction, flow speed, flow direction and effective wave height at a corresponding moment according to space-time position matching; calculating relative water body speed and relative wind speed based on vector decomposition, and respectively calculating ship body resistance, wind resistance and wave additional resistance; superimposing the three to obtain total resistance; inversely calculating propelling power according to the dynamic relationship between total resistance and relative water body speed; and finally calculating real-time fuel consumption according to the propelling power and a preset main engine fuel consumption rate. The method realizes ship fuel consumption prediction based on a physical model under the condition of no actual measured fuel consumption data. The application realizes high-precision physical model prediction of ship fuel consumption through dynamic coupling and power inversion of AIS and marine environment data under the condition of no actual measured fuel consumption data.

The application provides a three-dimensional flow velocity field inversion method and system based on coherence auxiliary SAR adaptive offset tracking and a storage medium to improve the de-coherence problem of synthetic aperture radar interferometry (InSAR) technology caused by time heterogeneity, and relates to the technical field of power engineering geological disaster monitoring. The method comprises the following steps: establishing a space-time baseline network between SAR images; obtaining the coherence data after geographical coding; selecting a pair of SAR image pairs from the space-time baseline network as a reference unit, and calculating the offset result through a pixel offset tracking technology for the reference unit, and determining the best matching window parameters thereof; establishing a mapping function between the coherence and the best matching window parameters; calculating the best matching window parameters of the remaining SAR image pairs according to the established mapping function; and combining the average deformation rate fields of the line-of-sight of the ascending track and the descending track, and inversely calculating the surface three-dimensional flow velocity deformation field of the target area through a geometric vector decomposition model.

This invention provides a condition monitoring method and system for a high-pressure fan-type shaftless external rotor motor, relating to the field of motor condition monitoring and fault diagnosis technology. Specific steps include: First, uniformly arranging four sensors on each of the upper and lower guide rails of the shaftless external rotor motor to construct a 360° circular monitoring array; second, acquiring eight channels of vibration data, and improving the signal-to-noise ratio through adaptive multi-scale filtering and wavelet envelope analysis; then, using a spatial vector decomposition and fusion algorithm to compress the eight-dimensional signal into a three-dimensional equivalent vector, and constructing a five-dimensional feature vector by combining speed normalization and temperature compensation; next, inputting the data into a lightweight Lite-CNN model for fault identification and severity quantification, and achieving fault location through confidence weighting; finally, triggering online incremental learning and updating the model using knowledge distillation. This invention has significant advantages in terms of recognition rate, positioning accuracy, and power consumption.

The present application relates to the technical field of geological engineering safety risk assessment, and particularly relates to a regional tectonic stress risk quantitative analysis method for tunnel engineering. The method comprises the following steps: collecting multi-source geomechanics parameters, simulating and inverting tectonic stress field and checking; building a multi-scale geomechanics model, coupling simulation of tectonic stress and gravity stress, and generating stress space basic layers; obtaining stress value and direction layers by using Kriging interpolation and inversion decomposition; calculating the angle between the maximum principal stress direction and the tunnel axis, and vector decomposition to obtain the vertical stress component; normalizing the factor, determining the weight to calculate the risk value, and finally generating a tectonic stress risk quantitative classification map and performing GIS visual rendering. The present application retains the directionality and spatial heterogeneity characteristics of the tectonic stress tensor, and builds a risk quantitative analysis mechanism for tunnel engineering, significantly improving the authenticity, resolution and engineering applicability of tectonic stress identification.

Embodiments are disclosed for a method. The method includes determining a granularity of hypervectors. The method also includes receiving an input hypervector representing a data structure. Additionally, the method includes performing an iterative process to factorize the input hypervector into individual hypervectors representing the cognitive concepts. The iterative process includes, for each concept: determining an unbound version of a hypervector representing the concept by a blockwise unbinding operation between the input hypervector and estimate hypervectors of other concepts. The iterative process further includes determining a similarity vector indicating a similarity of the unbound version of the hypervector with each candidate code hypervector of the concept. Additionally, the iterative process includes generating an estimate of a hypervector representing the concept by a linear combination of the candidate code hypervectors, and weights of the similarity vector.

The present disclosure relates to a filter, a filtering method, a data processing system, and a chip. A filter for performing N-dimensional Gaussian filtering on an N-dimensional data set, where N is 2 or 3, the filter including: a calculation factor obtaining module configured to obtain N calculation factors for N dimensions, where the N calculation factors correspond to N one-dimensional Gaussian kernels derived from performing N-dimensional vector decomposition on an N-dimensional Gaussian kernel to be used for the N-dimensional data set; and a calculation module including N calculation sub-modules for N dimensions that are arranged in a cascading manner, where each calculation sub-module is configured to perform, in a respective dimension using a respective calculation factor, one-dimensional Gaussian filtering on an N-dimensional data set input into the calculation module.

The present application relates to a kind of self-adapting Kalman filtering real wind direction wind speed acquisition method for gas inspection, belong to gas safety detection technical field, by cooperating with multiple stage algorithm to solve the wind field estimation deviation problem in mobile detection.Its technical means is in that: first, the original data timestamp is corrected with equipment delay;Subsequently, vehicle speed and vehicle direction are accurately calculated based on spherical geometry model;The core is to set the adaptive filtering algorithm of quantitative threshold to the apparent wind vector and the vehicle direction vector are pretreated, dynamically suppress noise and track mutation;Finally, the true wind observation value obtained by vector decomposition superposition is input into two-dimensional Kalman filter for smoothing optimization, and the real wind speed and wind direction are finally output, effectively overcome the contradiction between the noise resistance and fast response of traditional fixed parameter filtering, significantly improve the stability and accuracy of wind field estimation data, provide reliable basis for subsequent accurate positioning of gas leakage source.

This invention relates to the field of traditional Chinese medicine (TCM) manufacturing technology, and discloses a large-scale feature classification algorithm and system for detecting anomalies in the TCM processing process. The algorithm includes: acquiring a multimodal real-time dataset, parsing it in parallel to obtain information emergence points, and reconstructing them into a feature respiration spectrum; using the feature respiration spectrum to construct a process semantic graph and process manifold, performing vector decomposition to obtain the semantic orthogonal decomposition distance between representative traits and progress deviations; constructing a virtual correction force field to obtain active intervention instructions, driving risk inference to generate a structured anomaly diagnosis report. This invention achieves accurate capture and digital reconstruction of the processing sensitivity window, transforming qualitative anomaly judgment into quantitative diagnosis, solving the problems of difficult identification of latent anomalies and lack of correction suggestions, and improving the inherent safety, batch quality uniformity, and reliability of quality traceability in the TCM processing process.

This invention discloses a linear vector factorization (LVM) AI processing architecture, including vector convolution units, vector fully connected units, and vector register accumulation units. There are no data caching units between these units, and no input data caching structure precedes the vector convolution units. Convolution calculations are performed using local convolution windows. The vector register accumulation unit consists of a state selection unit, a register addition unit, and an output selection unit. The state selection unit specifies the storage, accumulation, and output states. By specifying the location of the input data and configuring a valid data address, when the location of the input data matches the valid address, the vector register accumulation unit saves, adds, or outputs the data according to the current input state. The output unit then outputs the calculation result for its respective location; otherwise, the output is 0. This invention reduces the cache time between linear layers and their connections, ensures output integrity, and guarantees real-time data transmission and computation.

The invention relates to a pushing type rotary guiding pushing force control method and system based on higher harmonics. The method comprises the steps that vector decomposition is conducted on sidewall contact type rotary guiding lateral force, and sidewall contact force corresponding to a hydraulic device is obtained; based on the pushing force of the corresponding hydraulic device, designing a pushing force higher harmonic expression of the corresponding hydraulic device; according to the designed pushing force higher harmonic expression, extreme value solving is conducted on the higher harmonic signals through a conjugate ladder method, the pushing force extreme value of the corresponding hydraulic device is obtained, and a pushing force signal coefficient is obtained based on the pushing force extreme value; and obtaining a pushing force expression of the corresponding hydraulic device based on the obtained pushing force signal coefficient. The control method and system are simple, the pushing force can be changed gently, the design difficulty of an execution mechanism of the control system is reduced, good engineering application value is achieved, and the conjugate gradient method is small in storage amount needed for solving the extreme value, has step convergence and high stability and does not need any external parameter.

This invention discloses a microgrid lifecycle planning method based on a physically decoupled surrogate model in the field of microgrid planning and optimized operation technology. This method includes: constructing a two-layer microgrid planning model covering the entire equipment lifecycle; establishing a physically decoupled surrogate model architecture; decomposing the objective vector into a smooth continuous subspace and a sparse abrupt subspace, and designing corresponding loss functions for each; adaptive active learning sampling during the execution phase, utilizing an uncertainty quantification method based on committee queries, and introducing a dynamic decay weighting mechanism; and employing a hybrid oracle-based online correction integer-encoded multi-objective evolutionary algorithm to solve for the optimal configuration scheme. This invention can eliminate the feature masking effect between heterogeneous objectives, improve the accuracy of identifying physical hard constraint boundaries, and achieve efficient and high-fidelity planning scheme solutions under limited computing resources.

This disclosure presents embodiments of a compensation and adjustment method, apparatus, electronic device, and medium applied to turbine blades. One specific implementation of the method includes: performing adaptive compensation detection on the turbine blade to be tested to obtain a three-dimensional point cloud dataset of the blade; performing point cloud feature registration processing on the three-dimensional point cloud dataset of the blade and a preset three-dimensional model of the turbine blade to obtain a blade point cloud registration transformation matrix; determining a set of normal vector deviation values ​​and a set of tool position normal compensation vectors; performing multi-dimensional direct-axis vector decomposition and rotary axis interpolation adjustment on the tool position normal compensation vector set to obtain a set of decomposed compensation vector values ​​and a set of rotary axis adjustment vector values; generating a cutting tool instruction set; and controlling the cutting tool on the spindle of a CNC machine tool to perform compensation cutting adjustment to obtain a compensated and adjusted turbine blade. This implementation completes the machining of the turbine blade in one step, which can improve the quality and adjustment efficiency of the turbine blade, shorten the machining and adjustment time, reduce equipment wear, and improve performance.

The invention provides a space manipulator three-dimensional force reconstruction method based on a load response basis matrix superposition principle, and relates to the technical field of space three-dimensional force reconstruction. The method comprises the following steps that a three-dimensional force sensing module is installed at an end effector of the space manipulator, and a plurality of fiber grating sensors are arranged on the three-dimensional force sensing module; carrying out vector decomposition on dependent variables actually measured by the fiber grating sensors to obtain strain components along the orthogonal direction of a space coordinate system; constructing a sensing module dynamic load model, and decomposing the strain orthogonal component matrix into a load-strain response basis matrix and a multi-dimensional load weight vector; according to the load-strain response basis matrix, the displacement, the speed and the acceleration at the center position of the three-dimensional force sensing module are calculated through inversion; through a dynamic response equation, a superposed load component of the three-dimensional force sensing module in a three-dimensional space is obtained through calculation; and controlling the joint of the space manipulator to realize flexible operation according to the calculated superposed load component.

The embodiment of the invention discloses a compensation adjustment method and device applied to turbine blades, electronic equipment and a medium. A specific embodiment of the method comprises the steps of performing adaptive compensation detection on a turbine blade to be detected to obtain a three-dimensional point cloud data set of the blade; performing point cloud feature registration processing on the blade three-dimensional point cloud data set and a preset turbine blade three-dimensional model to obtain a blade point cloud registration transformation matrix; determining a normal vector deviation value set and a cutter location normal compensation vector set; performing multi-dimensional direct-axis vector decomposition and rotating shaft interpolation adjustment on the tool location normal compensation vector set to obtain a decomposition compensation vector value set and a rotating shaft adjustment vector value set; generating a cutting tool instruction set; and a cutting tool on a spindle of the numerical control machine tool is controlled to perform compensation cutting adjustment, and the turbine blade after compensation adjustment is obtained. According to the implementation mode, machining of the turbine blade is completed at a time, the quality and adjusting efficiency of the turbine blade can be improved, the machining and adjusting time is shortened, equipment loss is reduced, and performance is improved.

This application discloses a multi-degree-of-freedom dynamic lateral force loading device, test bench, and control method. The device includes a base frame (1), an orthogonal actuation system, and a dynamic controller (11). The base frame is provided with a guide rail fixing seat (2) that can slide along the crossbeam (14) of the test bench; the orthogonal actuation system includes two electric cylinders (7) arranged at a 90° angle, one end of which is hinged to the base frame, and the other end is connected in sequence to a force sensor (8) and a vibration damper mounting fixture (9), and the fixture is provided with two orthogonally arranged sensor fixing seats (10); the dynamic controller receives the target resultant force vector, controls the output of the two electric cylinders based on the vector decomposition principle, and performs closed-loop calibration through force sensor feedback to realize dynamic lateral force loading with continuously adjustable direction from 0° to 360° and programmable frequency from 0 to 10Hz. This application solves the problem that existing test benches cannot reproduce multi-angle dynamic lateral loads.