263 results about "Parametric identification" patented technology

A motion assistance device has a biological signal detection means for detecting a biological signal from the wearer of the device; a motion assistance device installation member having a drive source for applying torque acting to the wearer by use of each joint of the wearer as a rotating shaft; a control means for controlling the drive source to generate torque corresponding to the biological signal detected by the biological signal detection mean; a drive torque estimation means for estimating the drive torque generated by the drive source; a joint angle detection means for detecting angular displacement of a joint; and a parameter identification means for substituting the drive torque estimated by the drive torque estimation means and the angular displacement detected by the joint angle detection means into an equation of motion to specify the wearer-specific dynamics parameter, the equation relating to the entire system and including wearer-specific dynamics parameter. The control means controls the drive source according to a predetermined control method, based on the equation of motion into which the dynamics parameter identified by the parameter identification means is substituted.

The invention discloses a transmission tower modal parameter identification method based on an improved subspace algorithm and used for completing the modal parameter identification of a large span transmission tower structure through individually utilizing response data under the excitation of a field environment. According to the identification process, multi-group packet response data are integrated into synchronous pulse response data based on a random subspace identification principle; the integrated data avoid fitting errors caused by the packet identification, so the synchronous integrated identification of the data is realized; and a stable graph is constructed by utilizing modal parameter identification results under different system orders, so a modal parameter identification order determination problem under the environment excitation is solved, modal omission and repetition phenomena of traditional methods of a peak value method and the like are avoided, the obtained identification result is accurate and stable, and bases are established for subsequent structure damage detection and life estimation.

Provided are systems and methods for minimizing co-channel interference on-board a satellite. An up-link signal received by the satellite is post-compensated, where the up-link signal includes a desired signal transmitted by a first transmitter and an interfering signal transmitted by a second transmitter. The post-compensating includes identifying the interfering signal based on post-compensation parameters. In addition, a down-link signal to be transmitted from the satellite to a receiver is pre-compensated. The pre-compensation process includes determining gain relations between a gain of a first satellite antenna which transmits the down-link in a direction of the receiver and a gain of a second satellite antenna which transmits an interfering signal in the direction of the receiver, sampling and scaling interfering signals at the satellite based on the gain relations, and estimating a co-channel down-link interference component that the down-link signal is expected to experience on a path to the receiver.

The invention provides a travel time predicting method based on a network convergence and taking account of a traffic state time-space relation. The method obtains high-precision data by subjecting floating car data to refined processing. In particular, the process for subjecting the floating car data to refined processing ingeniously uses a convolutional neural network and a recurrent neural network which are mainly used in the field of artificial intelligence currently, fuses the networks, fully takes account of the time-space relation of a traffic state, deeply excavates a traffic state evolution rule, and ultimately achieves precise travel time prediction. Compared with various conventional travel time prediction models, the method fuses the time-space relations of the traffic state, fully excavates historical data characteristics, overcomes a difficulty that other methods cannot cope with the high time-varying characteristics and non-linear change characteristics of the traffic flow, does not need priori knowledge and parameter identification, and has good fault tolerance and robustness, high precision, and good stability.

The invention discloses a structural modal parameter identification system based on binocular stereo vision. The method of the system comprises the following steps of building a binocular stereo vision system, calibrating two camera units, and acquiring internal and external parameters of the two camera units to carry out three-dimensional correction; establishing easily identifiable key points of a detected structure surface; loading impact force to enable the detected structure to move freely, obtaining a synchronic image sequence file, identifying the three-dimensional coordinates of all key points to each frame of image orderly, and obtaining the three-dimensional movement data of all key points in the whole test time finally; through the three-dimensional movement data of all key points, carrying out modal identification by using a characteristic system realization algorithm, obtaining the modal parameters of the detected structure, and outputting a result. Compared with the traditional technology, the structural modal parameter identification system can measure the modal parameters of the detected structure in a non-contact way or in a way that less impact is applied to the detected structure, and the system has the advantages of low cost, fast speed and high precision and is especially suitable for the modal parameter measurement of large lightweight structure with inconvenient layout of sensors.

A method of catching systematic eigenfunctions and signal eigenvalues under the condition of only response output available belongs to the parametric recognition technique in dynamic test field. The technique is a method of adopting cross spectral density functions of each response point instead of frequency response functions to perform time-frequency filtering and the parametric recognition of frequency domain, and includes the following steps: (1) carrying out analytic calculation of the cross spectral density functions of different metering signal of output points; (2) analyzing and calculating the nonorthogonal wavelets in the time-frequency domain according to the cross spectral calculating result; (3) inversing the fourier transformation to gain the time-frequency analyse coefficient; (4) adding a rectangular window to perform the time-frequency filtering; (5) calculating the cross spectrum of the output signal after filtering as the systematic function for recognition; (6) performing curvefitting to obtain the systematic parameter; the technique improves the recognition precision of the systematic parameters, precisely recognizes modal parameters, is simple and convenient, and is suitable for the dynamic analyses, the performance verification and the failure diagnosis of large civil engineering establishments such as large and complex mechanical equipments under operation status, high-rise buildings, bridges, etc.

A computer implemented system for adjusting the placement of an implant in a patient through the use of a dimensioned grid template placed relative to patient anatomy on a fluoroscopic machine and a method to digitally quantify alignment parameters is provided. This system can be used for determining: 1) leg length, offset, and cup position during arthroplasty replacement surgery; 2) fracture reduction/correction position during trauma procedures and 3) an apparatus to be used for deformity correction planning is provided; 4) placement and positioning of instruments and implants relative to bone and anatomical architecture; 5) bone anatomy boundary parameter identification relative to reaming and cutting landmarks of bone.

A six-DOF high-precision calibrating method for an articulation type coordinate measuring machine comprises the following steps of: using the articulation type coordinate measuring machine as a calibrated machine, using a three-coordinate measuring machine with higher precision as a standard machine, and disposing the calibrate machine into the measurement space of the standard machine; respectively obtaining the standard coordinates of probes in a standard coordinate system and the measurement coordinates of the probes in a calibrated coordinate system; using the standard coordinates and the measurement coordinates as sampling data, and obtaining the error parameter of the calibrated machine with least square method. The method is characterized in that the sampling density is that each joint of the calibrated machine at least locates at two equally divided angle positions in each circle (360 DEG), and the placement attitudes of the calibrated machine formed by the combination of the six joints with different angle positions are at least 64 types. The inventive method can further improve parameter identification precision, and improve the entire precision of the measuring machine.

The invention relates to a two-dimensional human skeleton point locating method for a monocular depth video. The method comprises model building, a training process and an identification process. The training process comprises the following steps of S21, collecting a training sample; S22, generating a training target; S23, randomly initializing a deep model (a long-short-term memory convolutional neutral network) and model parameters, wherein the parameters consist of parameters of a convolutional layer and parameters in a long-short-term memory convolutional layer; and S24, by adopting a model optimization algorithm, updating the parameters of the deep model by utilizing the training sample in an end-to-end manner. The identification process comprises the following steps of S31, inputting monocular depth video frames; and S32, inferring and predicting human skeleton point positions by utilizing the trained deep model. By setting a reasonable learning target, the deep long-short-term convolutional neutral network is established; human skeleton point prediction features are obtained by adaptive learning according to a data driving mode; and a stable and reliable human skeleton point locating effect is achieved.

The present invention relates to the field of the electric power system electric power transmission line relay protection, especially to a technique of the single-phase self-adapting reclosing with a parallel reactor electric power transmission line, and the invention discloses a method for judging the permanent fault of the electric power transmission line with a parallel reactor. The method adopts the parameter recognizing principal and constructs an identification equation which uses the circular parallel reactor and neutral point small reactor a parameter to be determined basing on the network equation when the instantaneous fault has disappeared. The solving to the inductor parameter is realized by the sound phase voltage, sound phase current, parallel reactor current and neutral point small reactor at this side. According to the least square parameter estimate redundant algorithm the inductor parameter is solved, and the instantaneous fault and permanent fault are discriminated using the comparison between the solved inductor parameter and the actual inductor parameter.

The invention belongs to the bridge monitoring technical field and provides a bridge structure modal parameter authenticity and falsity discrimination method and a terminal device. The method includesthe following steps that: the monitoring data of the structure of a bridge under an environmental excitation condition are obtained through data acquisition devices disposed in a plurality of measuring points of the bridge; the NExT (natural excitation technique) is adopted, at first, the cross power spectrum density function of the monitoring data is calculated, and Fourier inverse transformation is performed on the cross power spectrum density function, so that the cross-correlation function of the monitoring data is obtained, the cross-correlation function is adopted as the input data of amodal parameter identification algorithm, so that modal parameter identification can be carried out, and a stability diagram can be drawn; the auto-power spectrum density function and cross-power spectrum density function of the monitoring data of the measuring points are calculated, the auto-power spectra and cross-power spectra of all the measuring points are summated, and the auto-spectra andthe cross spectra are summated in the same order of magnitude, so that the sum function of the power spectra can be obtained; and a diagram of the sum function, and true and false modal parameters canbe discriminated according to the stability diagram of the sum function. According to the method, the stability diagram method and a power spectrum summation peak method are combined to perform bridge structure modal parameter authenticity and falsity discrimination, so that discrimination accuracy can be improved.

The invention relates to a universal electromagnetic signal automatic searching method. The method mainly comprises the following steps of: (1) performing frequency-domain scanning and threshold value detection to form a list of signals to be searched; (2) performing frequency-domain feature extraction on the signals in the list of the signals to be searched, and matching the extracted frequency-domain features with the set frequency-domain features of the signals to be searched; (3) identifying modulation parameters of the signals of which the frequency-domain features are matched with the set frequency-domain features of the signals to be searched, and matching the modulation parameters with the set modulation parameters of the signals to be searched; and (4) performing demodulation processing and time-domain feature parameter extraction on the signals of which the modulation parameters are matched with the set modulation parameters of the signals to be searched, and then matching the time-domain features with the set time-domain features of the signals to be searched; and if the similarity is greater than a set similarity coefficient, then determining that the current processed signal is a target signal to be searched. According to the method provided by the invention, electromagnetic signals with certain specific features can be searched automatically without human intervention; the intercept probability of the signals can be improved remarkably; and the work efficiency of detection personnel can be improved greatly.

The invention discloses an MIMO (multiple input multiple output) based high-resolution underwater target detection device and method. According to the invention, a potential target is actively detected through a plurality of mutually-orthogonal detection waveforms transmitted by a transmitting transducer array in a hydroacoustic environment, and a hydrophone-array received target echo is received. Through MIMO processing, a method for carrying out detection and estimation on an MIMO frame is established, and the extension of waveform diversity gains and virtual array apertures is obtained. By using the MIMO based underwater target detection method disclosed by the invention, in the process of carrying out hydroacoustic target detection, compared with conventional phase control, a higher detection resolution and higher parameter identification performance can be obtained.

The invention discloses a method of recognizing asynchronous vibration parameters of blades under variable speed excitation. According to the method, aliasing frequency is acquired by means of increasing sampling rate by interpolation of measurement data of adjacent two blades, vibration aliasing frequency and phase is acquired by full-phase FFT (fast Fourier transform), and a fractional part of non-integer order is acquired; order tracking is performed according to a relation between the phase and the sensor mounting angle, and an integral part of asynchronous vibration order of the blades is recognized; an algorithm is verified by deceleration multi-octave asynchronous vibration data generated by a four-blade simulation model, simulation data is vibration data of the single blade measured by a single sensor, recognition results are compared to simulation parameters, and the ability of the algorithm to correctly recognize the asynchronous vibration parameters of the blades is verified. The method is correct, reliable, simple and feasible.

The invention discloses a method for identifying unfrozen meat and fresh meat based on an impedance spectrum. The method comprises the following steps of: 1, generating a plurality of continuous sine wave signals with different frequencies and mean amplitude of zero and loading the sine wave signals on a raw meat sample; 2, including the raw meat sample and a resistor R1 with fixed nominal value on a branch circuit through which the sine wave signals flow, and detecting voltage division values of impedance and the resistor R1; 3, converting the ratio of the voltage division values into a voltage form and then into a digital signal, calculating the impedance of each frequency fi according to the resistor R1 and the digital signal, and representing the change of the impedance along with thefrequency fi as a curve to obtain the impedance spectrum; 4, detecting phase difference between a plurality of sine wave signals generated in the step 1 and the signal passing through the raw meat sample to be measured, converting the phase difference into voltage output and then into a digital signal, and representing the change of the phase difference along with the frequency fi as a curve to obtain phase spectrum; and 5, identifying the unfrozen meat according to the impedance spectrum and a phase spectrum export parameter. By the method, the unfrozen meat and the fresh meat can be completely and objectively identified.

A method for identifying parameters of a resonant fatigue crack propagation test vibration system based on a soft sensing technology comprises the following steps: 1, establishing a system three-degree-of-freedom vibration mechanical model to obtain a kinetic equation, and deriving to obtain a system frequency equation about a relationship among the system inherent frequency, the spring rigidity and the particle mass; 2, calculating according to a finite element technology to obtain the rigidity of a test piece under different crack lengths, and testing the system resonant frequency when a crack is propagated to different lengths; 3, substituting the system resonant frequency value and the corresponding test piece rigidity under different crack lengths into the system frequency equation in order to obtain overdetermined equations about the mass to be identified and unknown rigidity; 4, solving the overdetermined equations through a least squares technique to obtain nonlinear equations about the mass and rigidity; and 5, solving the nonlinear equations by using a Newton-Raphson formula, and identifying the vibration system parameters comprising the mass and the rigidity. The method has the advantages of good maneuverability, low cost and good accuracy.

In aspects, the present invention discloses a method for replacing a first field device with a second field device using a commissioning tool. The method comprising retrieving a device description file associated with the first field device, analyzing the device description file, generating a first object by mapping a parameters of the second field device to a parameter from the identified one or more parameters based on a first index and a second index, generating a configuration file associated with the second file device based on the device description file and the generated first object, and transmitting the configuration file to the second field device for commissioning operation of the second field device. The step of analyzing the device description file comprises identifying one or more parameters from the plurality of parameters for mapping based on a predetermined criteria.

The invention provides a bridge impact coefficient optimization method based on the parameter identification technology, solving the problems in the calculation of impact coefficient and the optimization of impact coefficient sensitivity in stochastic dynamics, which can reduce the damage of bridge. The method is carried out in this manner: (1) defining a vehicle model, (2) deriving the equation of motion MU<..>+CU<.>+KU=F<g>+F<w>, according to the D'Alembert's principle; using the PIM method to solve deterministic response and using the PEM to calculate random response, U(t)=integral H(t-[tau], t)(F<g>([tau])+F<w>([tau])) differential [tau], t belongs to (0, t). The invention provides an effective optimization method for non-stationary random vibration of a vehicle-bridge coupling system, and improves comfort and safety of the vehicle and the bridge. The method of the invention has both accuracy and efficiency, and can provide better technical support for vehicle-bridge coupling vibration sensitivity analysis and optimization. The computational time required by the PEM-PIM numerical method is more than ten times that of the Newmark method when the computational accuracy is the same, and the method of optimizing the sensitivity of the self-identification design variables is proposed.

The invention discloses an air conditioner control method and device and belongs to the technical field of automobile electronic control. The air conditioner control method comprises judging whether an automobile satisfies boundary conditions or not and obtaining throttle valve parameters of an acceleration pedal of the automobile when the automobile satisfies the boundary conditions; identifying whether emergency acceleration power supply is needed or not according to the throttle valve parameters; performing control to close the air conditioner if the emergency acceleration power supply is needed and the air conditioner is in an opening state; and performing control to open the air conditioner if the emergency acceleration power supply is not needed and the air conditioner is in a closed state. The air conditioner control method enables the accuracy of air conditioner control to be improved due to the fact that when an air conditioner switch is at an opening position, whether the automobile satisfies the boundary conditions or not is firstly judged, then whether the emergency acceleration power supply is needed or not according to the acceleration pedal throttle valve parameters is judged to confirm whether the air conditioner is controlled or not; the flexibility of air conditioner control is increased due to the fact that judging whether the automobile satisfies the boundary conditions or not is added before judging the acceleration pedal throttle valve parameters.

The invention discloses a recognition device and method for parameters of an execution mechanism in an electro-hydraulic linear velocity servo system. The recognition device comprises a step current signal generator, an electro-hydraulic servo valve, a hydraulic cylinder, a mechanical load, a liner-velocity detection sensor, a recorder and a hydraulic source; and the recognition method comprises the steps of: inputting step current signals into the electro-hydraulic servo valve, and detecting the motion liner velocity of the mechanical load; recording the varying process of the step current signals and linear velocity signals with the time till the steady-state value of the linear velocity signal is achieved; dividing the amplitude of the step current signals by the steady-state value of the linear velocity signals to obtain an equivalent viscous damping coefficient of the execution mechanism; and multiplying the equivalent viscous damping coefficient by a time value corresponding to a state that the 0.632 times of the steady-state value of the linear velocity signals is reached to obtain an equivalent mass of the execution mechanism. By means of the recognition device and method disclosed by the invention, the regulation of the parameters of a controller of the electro-hydraulic linear velocity servo system is timesaving and laborsaving, and the electro-hydraulic servo system can achieve better static and dynamic properties.

The invention discloses a method for identifying the model of an air conditioner. The method comprises the following steps: detecting a model identification instruction and reading the level state of a model selection input and output interface of a model control chip; searching a parameter list which is provided with model information corresponding to level states in advance according to the read level state; and obtaining the model information corresponding to the level state from the parameter list and reading pre-stored model parameters corresponding to the model information from a storage device of the air conditioner according to the obtained model information. The invention also discloses a device for identifying the model of the air conditioner. According to the air conditioner model identification method, the parameter list is searched according to the read level state of the model selection IO interface of the model control chip; the model information corresponding to the level state is obtained from the parameter list; the model parameters corresponding to the model information are further read; and therefore, the beneficial effect of improving the accuracy of model parameter identification is achieved.

The invention discloses a dynamic calibration method for a high-frequency force balance, which comprises the steps of performing whitening on a measurement signal x(t) to acquire a whitened signal z(t); seeking an orthogonal matrix V, enabling the whitened signal z(t) to equal to Vq(t), and thus acquiring a separated signal q(t); performing natural frequency and modal damping ratio recognition on the separated signal in modal coordinates; correcting the separated signal according to recognized parameters; and inversely deducing according to the separated signal to acquire a corrected pneumatic load. According to the invention, separation is performed on a coupling signal, and for independent components acquired by separation, natural frequency and modal damping ratio recognition is performed on the separated signals one by one by adopting a curve fitting method through combining aerodynamic characteristics, so that a dynamic amplification effect of a modal coupling system is corrected and eliminated, a real aerodynamic load spectrum density matrix is acquired finally, the reliability of parameter recognition and corresponding HFFB (High-Frequency Force Balance) dynamic signal calibration can be improved to the maximum extent, and an important basis is laid for subsequent accurate estimation for high-rise building prototype wind-induced responses.

The invention provides a power transmission line parameter identification method and system. The method comprises the following steps: reading a double-ended wave recording file of a faulty line, andobtaining double-ended electrical quantity information of the faulty line; carrying out time synchronization on the double-ended electrical quantity information of the faulty line; and carrying out line parameter identification according to the synchronized double-ended electrical quantity information of the faulty line, so that a reactance identification value is obtained. By virtue of the technical scheme provided by the invention, power transmission line steady state parameter identification based on fault wave recording data is realized, and synchronization alignment treatment is carried out on the fault wave recording data, so that non-synchronous time of the double-ended wave recording file is shortened, a new means and a good data foundation are provided for accurately identifying power grid branch circuit parameters of a dispatching master station, power grid branch circuit steady state impedance parameter identification accuracy is practically improved, and further the accuracy and availability of a power grid online dispatching analysis software result are improved.

The invention discloses a measurement and control method in a suspension pouring construction process of a continuous rigid frame bridge, and belongs to the technical field of measurement and control of highway engineering. According to the method, a parameter identification step is added based on the prior art. The measurement and control method comprises the steps of obtaining overall rigidities EI1 and EI2 of to-be-identified rigidity beam segments; obtaining weights mL1 and mL2 of to-be-identified weight beam segments; performing identification in a high-order mode under the condition that the identification effect is greatly influenced by test environment conditions or is interfered by other influence factors; and adjusting an elevation of the front end of a hanging basket on site to realize suspended poured line shape control. According to the method, the overall rigidity and the quality are identified, the down-warping amount generated by a to-be-poured beam segment is predicted, and the construction camber is reserved, so that a reasonable completed bridge line shape of the bridge is realized. The method has the main advantages that the temperature influence is avoided and the measurement does not need to be carried out at night, so that the potential safety risk of operation is lowered; software and hardware are mature, data processing is concise, and sensors can be connected for wireless communication, so that unmanned monitoring is realized; and the precision is improved and passive control methods and means are added.