397 results about "Impulse response" patented technology

The invention relates to an intelligent monitoring alarm method and system for a motor controller, and the method comprises the steps: obtaining an internal circuit signal and a body vibration signal of the motor controller, carrying out the combined noise analysis, and generating a dynamic noise baseline; performing component fault identification based on the dynamic noise baseline and the internal circuit signal to obtain a fault precursor current feature; performing component impact response separation based on the dynamic noise baseline and the body vibration signal to obtain hidden fault vibration characteristics; performing component association mapping on the fault precursor current feature and the hidden fault vibration feature to obtain an internal fault component identifier; and performing alarm analysis based on the fault component identifier, the fault precursor current feature and the hidden fault vibration feature to obtain a graded alarm decision. According to the invention, early fault features can be captured more sensitively, and false alarms and missing alarms are reduced.

The invention relates to the technical field of RFID tag signal optimization, and discloses an RFID tag signal optimization method and system based on deep learning. According to the method, feature extraction is carried out on a backscattering signal, core features of a multipath channel are quantized from a frequency domain and a time domain respectively, numerical representation of a channel state is further obtained, then obtained data information is used as input of a deep learning network, training and forward calculation are carried out, original emission parameters are adjusted, and a multi-path channel is obtained. Therefore, the conversion from blind extensive control to precise control of the transmitting end is realized, so that the problem of mismatching of parameter control and channel state caused by information splitting of the transmitting end and the receiving end in the prior art is solved; according to the signal optimization method for realizing joint adjustment of transmitting and receiving parameters through an end-to-end deep learning architecture, the optimization effect of an RFID tag signal in a complex environment is remarkably improved.

The invention discloses a frequency domain ground penetrating radar transmitting source coding and receiving signal synthesis method and system. The method comprises the following steps: constructing a frequency domain coding continuous wave ground penetrating radar transmitting signal by extracting amplitude and phase information of multiple frequency points of a time domain ultra-wideband transmitting pulse; adopting a fast forward modeling method based on impulse response to realize forward modeling of a coding source emission signal of the typical geoelectric model; in-phase components and orthogonal components of all frequency points are extracted, frequency responses are synthesized into responses of quasi-time-domain transmitted pulses through an inverse Fourier transform method, the high resolution equal to that of time-domain ultra-wideband transmitted signals is obtained, and higher anti-noise performance is achieved. According to the invention, the amplitude phase coding continuous wave transmitting signal is adopted, so that the frequency spectrum shaping of the quasi-time domain pulse of the transmitting frequency spectrum is realized, the resolving power of the synthetic signal is improved, and a theoretical basis is laid for signal synthesis of frequency domain ground penetrating radar hardware design.

A motor fault prediction method for an HT80 general turbine controller comprises the steps that pressure signals of an inlet and an outlet of a hydraulic servo valve are obtained, and impulse response decomposition and time domain envelope analysis are conducted on the pressure signals to extract a microbubble nucleation characteristic spectrum in pressure fluctuation; and based on the microbubble nucleation characteristic spectrum, constructing a mapping relation between the bubble volume fraction and the system equivalent damping coefficient, and smoothing a damping coefficient time sequence through Kalman filtering to obtain a damping coefficient curve. And calling a hydraulic system pulse response model to calculate the instruction response time of the hydraulic servo valve according to the damping coefficient curve, and comparing the instruction response time with the adjustment target to obtain response delay. The lagging threshold curve is determined through experimental simulation calibration, whether the response delay exceeds the safety threshold or not is judged based on the lagging threshold curve so as to trigger an alarm, early warning of the hydraulic response delay trend is achieved, and the problem that millisecond-level rapid adjustment cannot be completed in operation can be avoided.

The invention provides a machine tool machining shaft anomaly detection method and system based on double-order excitation, and relates to the technical field of numerical control machine tools. The method comprises the steps that a key machining shaft of a numerical control machine tool is determined; constructing a shaft transmission anomaly detection model; a double-order reverse test sequence is injected into the key machining shaft through the controller, and a double-order pulse response sequence corresponding to the double-order reverse test sequence is recorded through the encoder; a pulse arrival time sequence is analyzed, and reverse response delay, static lag section length and speed transient characteristics are calculated; and inputting into a shaft transmission anomaly detection model for analysis, and outputting a reverse gap detection value of the key processing shaft. The technical problem that in the prior art, due to the fact that tiny anomalies of the numerical control machine tool are difficult to accurately detect, the machining anomaly detection precision is insufficient is solved, and the machining anomaly detection accuracy of the numerical control machine tool is improved through the double-order reverse test sequence and the shaft transmission anomaly detection model.

Linear unretimed interfaces lack clock and data recovery and retiming circuits implemented on a sophisticated digital signal processor. When the interface is not a retimed interface, it can be especially useful to extract some information about the link to allow for debugging and optimization of system deployment. An efficient solution can be implemented in unretimed interfaces to compute metrics such as the impulse response and signal histogram. Having the metrics allows for the solution to check and monitor the quality and the status of the link. Based on the link quality and status information, it is possible to address non-idealities and optimize performance of the unretimed interfaces and the link.

The invention discloses a natural language processing technology-based cultural and creative element data analysis method, which comprises the following steps of: based on AI intelligent plush doll interaction data, generating a cultural and creative structure embedding degree index through named entity recognition and semantic network topology analysis; an impulse response function is constructed based on the cultural creative structure embedding degree, and a cultural creative memory cycle index is calculated in combination with the path length and information backflow; fusing the multi-modal features and the ideal innovation region, and outputting a perception novelty score; screening high-potential-energy elements to construct a semantic sub-graph, simulating a thermodynamic process, and identifying a text-creative fusion hotspot chain; and decoding the hotspot chain into a design semantic tag, matching a material database to generate an appearance scheme, and converting the appearance scheme into an interaction template, thereby realizing a customized design closed loop from a user dialogue to a doll form and behavior. Through data driving and cross-modal analysis, implicit culture preferences in user dialogues are dominated, and creativity of the appearance of the AI intelligent plush doll and humanization of interaction are improved.

The invention belongs to the field of sound field environment modeling, and particularly discloses a room impulse response simulation method and system based on a generative adversarial network. The method comprises the following steps: carrying out convolution on a public room impulse response data set and a pure audio data set, and adding noise at the same time to obtain a reverberation audio training data set; inputting the constructed reverberation audio training data set into a physical parameter estimation network for pre-training, calculating a loss function of the network, and adjusting network parameters through gradient back propagation; and freezing the physical parameter estimation network, jointly training the generative adversarial network, taking the pre-trained physical parameter estimation network as a physical constraint module, and guiding a generator in the generative adversarial network to output a room impulse response conforming to a physical rule. According to the invention, the problem of distortion of the generated pulse response can be effectively reduced, and the generated pulse response is closer to real data.

The present disclosure relates to the technical field of audio control. Provided are a computer-implemented method for audio control, and an electronic device and a storage medium. The computer-implemented method for audio control comprises: on the basis of a specified measurement signal, performing acoustic effect testing on a target space, in order to obtain environmental response information, wherein the environmental response information comprises impulse response information and post-separation impulse response information; analyzing the environmental response information, in order to obtain acoustic characteristic information of the target space; on the basis of the acoustic characteristic information, performing compensation processing on audio to be processed, in order to obtain regulated audio; regulating gains of multiple channels corresponding to the regulated audio, in order to obtain re-regulated audio; and performing multi-channel collaborative optimization processing on the re-regulated audio, in order to obtain audio having a target effect. The method achieves precise compensation for spatial acoustic defects, resolves inter-channel crosstalk, improves the acoustic image localization and spatial perception, significantly improves the perceptual audio quality, and optimizes an output.

The invention relates to the technical field of automatic control, in particular to a switching positive system identification method and system and a storage medium, and aims to solve the problems that in the prior art, a model violates non-negative physical constraints, hyper-parameter estimation is prone to local optimum, calculation efficiency is low, and switching path identification precision is insufficient. The method comprises the following steps: firstly, determining non-negative priori of a system model and pulse response truncated Gaussian distribution through a preparation module; constructing a Bayesian network, and iteratively optimizing a switching path by adopting Gibbs sampling; and finally, based on regularization optimization and Gibbs sampling in combination with Monte Carlo approximation, accurately estimating the pulse response of the subsystem. According to the method, the non-negative characteristics are embedded into the whole identification process, global parameter optimization is achieved, high-dimensional integral calculation is simplified, identification precision and stability are improved, and the method is suitable for multi-scene engineering application.

Data transceivers including a transmitter configured with a digital filter, and a receiver configured with an equalizer, are equipped with logic to measure a combined pulse response to a symbol generated by the transmitter at an output of the equalizer, adjust the combined pulse response by an impulse response of the digital filter to generate an adjusted pulse response, and modify the digital filter with one or more floating taps based on the adjusted pulse response.

A distributed ultra-wide band (UWB) radar system and methods for operating the same are disclosed. The distribute radar system uses a plurality of separate UWB radios or nodes that do not use a centralized clock or source of time. However, the distributed UWB system operates to provide radar-like functionality and fine-grain sensing capabilities through synchronization based on line-of-sight (LOS) signal processing and noise estimations. Synchronized channel impulse responses (CIRs) can be processed for general object detection and tracking, gesture recognition, or even micro-motions such as monitoring vitals

Methods and systems are disclosed for an audio system for a vehicle system. In one example, a noise cancellation system includes a vehicle having a plurality of speakers and a plurality of microphones, a plurality of sensors, and a controller. The controller includes instructions stored on non-transitory memory that when executed cause the controller to generate a noise cancellation signal using a set of head-related impulse responses for the plurality of speakers and the plurality of microphones based on a head position of one or more occupants and a plurality of transfer functions, including to selectively update only a subset of the plurality of transfer functions responsive to the plurality of sensors detecting head movement greater than a threshold.

The invention provides a space target orbit maneuver identification method and system based on adaptive LSM, and the method comprises the steps: obtaining the orbit data of a space target, calculating the six orbit elements based on the orbit data, and coding the six orbit elements into a pulse sequence; and inputting the pulse sequence into an improved adaptive LSM for detection to obtain an orbit maneuver behavior identification result of the space target. According to the method provided by the invention, six orbital elements are calculated through the speed and the position of the orbital, then the orbital parameters are input into an improved LSM, and the improved LSM adopts an adaptive threshold neuron as a calculation unit, so that the threshold can be dynamically adjusted according to the current pulse response and attenuated along with time; meanwhile, an improved particle swarm optimization algorithm is combined to carry out optimization setting on an initial value of a neuron, so that the initial performance of the model is improved; and a learnable neuron connection weight based on an attention mechanism is introduced, so that the accuracy and reliability of orbit prediction are improved.

The invention discloses a digital twinning-based multistage water-saving ship lock navigation safety guarantee method and system, and the method comprises the steps: collecting multi-source sensing data, generating an alignment data flow and a quality evaluation report, and updating a digital twinning state; by means of the aligned data flow and the quality evaluation report, through non-contact observation and probability fusion, mooring force probability distribution is obtained; based on the digital twinning state and the alignment data flow, identifying a hydraulic impulse response and adopting hydraulic phase lock tracking to generate a vibration suppression opening template; and in the digital twin system, integrating the mooring force probability distribution and the vibration suppression opening template, executing distribution robust random control barrier optimization, and outputting an executable valve track. According to the method, water hammer oscillation can be actively inhibited, robust safety guarantee is provided for uncertain mooring force, and the navigation safety of the large water-saving ship lock is effectively improved.

The invention relates to the technical field of controller fault diagnosis, in particular to a controller fault root cause distinguishing method and system. A VAR model is adopted to distinguish the fault root cause of the controller, a plurality of mutually associated communication parameters in the controller are modeled into a unified multi-dimensional time sequence system, and modeling and analysis are performed on multivariable time sequence data of the integrated controller in the communication process. A collaborative decision-making mechanism of residual analysis, Granger causal relationship and impulse response function mode comparison is integrated to accurately distinguish whether communication abnormity is originated from an external network problem or an internal processing bottleneck of the integrated controller so as to realize intelligent monitoring of a communication link health state and accurate distinguishing of a fault source. Therefore, the technical problem that the fault root cause of the controller is difficult to accurately position in the prior art is solved.

The invention relates to an LPDDR4X simulation method and system based on a statistics theory. The method comprises the steps that a single-byte BYTE time domain simulation platform used for simulating LPDDR4X signal transmission characteristics is constructed; routing delay analysis is carried out on packaging and PCB channels corresponding to each signal in the single-byte BYTE, time sequence inconsistency in signal transmission is captured, and then the influence of phase crosstalk noise on eye height is captured; carrying out pulse response analysis on the signal, and quantifying ISI noise basic data caused by packaging and a PCB channel; independently analyzing the influence of crosstalk noise on each signal to obtain direct influence data of noise on eye height; processing ISI noise basic data and direct influence data by utilizing an MATLAB script, and extracting a main cursor voltage value, an ISI noise amplitude and crosstalk noise; according to the main cursor voltage value, the ISI noise amplitude and the crosstalk noise, the final eye pattern eye height is calculated. According to the method, the problem that a traditional simulation method is insufficient in eye pattern height evaluation is solved, and more accurate and efficient simulation support can be provided for high-speed low-power-consumption DDR design.

The invention discloses a detection method, equipment and medium for a new energy high-power direct-current charging pile, and relates to the technical field of charging pile stability detection, and the method comprises the steps: controlling a direct-current electronic load to generate a load disturbance signal at N characteristic working points, collecting instantaneous value change data through a broadband data collection center, and calculating the stability of the charging pile according to the instantaneous value change data; and based on the dynamic load disturbance signal and the instantaneous value change data, calculating the pulse response characteristics of the to-be-tested DC charging pile at the N characteristic working points through a correlation function analysis method, constructing a dynamic impedance characteristic model, and based on the safe working area three-dimensional boundary map, the electric energy quality indexes of the N characteristic working points and the dynamic impedance characteristic model, calculating the dynamic impedance characteristic of the to-be-tested DC charging pile. And evaluating and diagnosing the comprehensive performance of the direct current charging pile to be tested. According to the direct current charging pile comprehensive performance detection method based on dynamic load disturbance, accurate physical examination of the overall performance of the charging pile is achieved, and the detection depth, precision and predictability are improved.

The present disclosure relates to systems and methods for enrollment-free automated speech recognition (ASR) in multi-speaker environments. A system can process mixed audio signals containing speech from a target speaker and one or more interfering speakers. By applying acoustic characteristics such as room impulse responses (RIRs) and / or speech-to-interference energy ratios, the system can simulate environments to improve speech separation and recognition accuracy. A neural network model can be trained to identify and transcribe the speech of target speakers and / or secondary speakers, while filtering out interference. The system can update the model using ground-truth text and performance feedback, thereby facilitating real-time or near real-time ASR in multi-speaker environments without requiring predefined speaker data.

The invention relates to the technical field of image recognition control, in particular to a linear motion module accurate control method and system based on AI vision, and the method comprises the following steps: obtaining an interference fringe image and extracting a gray path, analyzing central point displacement to generate a coordinate sequence, repairing an interference feature position, and aligning the image and a control time sequence to generate a synchronization time table. The mapping structure response forms a set of control output configurations. According to the method, a peak path is constructed through interference fringe gray scale information in an image frame, central point pixel displacement is extracted, a coordinate migration sequence is constructed, fine-grained capture and tracking of an execution state are realized, an external interference area is identified according to image gradient change, vector repair is carried out, and image data stability and feature reliability are guaranteed. And aligning the repaired image response with a control instruction time sequence, constructing an impulse response lag statistical mechanism, realizing accurate mapping adjustment of the control frequency, and improving the control precision and response consistency in high-frequency displacement execution.

The invention relates to the technical field of electrical detection, in particular to a multi-stress coupling environment reliability testing method for an electricity consumption information acquisition terminal. Comprising the steps of applying a combined stress field to an electricity utilization information acquisition terminal through an environment test box; acquiring power utilization information acquisition terminal parameters; the method comprises the following steps of: capturing metering pulse response and carrier communication interaction signals of an electricity utilization information acquisition terminal under the excitation of a combined stress field by utilizing an electrical sensor, extracting carrier signal-to-noise ratio data and metering reference drift data, and generating a reference voltage compensation coefficient and an impedance matching threshold value; projecting the carrier signal-to-noise ratio data to an impedance matching threshold value, and constructing a stress failure envelope surface according to a hardware overload protection threshold value; and mapping the communication quality distortion residual vector to a stress failure envelope surface, and calculating a reliability life prediction value. According to the method, a uniform excitation environment is constructed, and performance degradation of different dimensions is uniformly quantified into accumulative stress damage integral, so that the comprehensive anti-interference capability of the terminal in a multi-stress coupling environment can be truly reflected.

The invention discloses a scene-adaptive multipath time delay alignment method and device for a wireless communication system, and the method comprises the steps: employing an SISO channel detection system to actually measure channel data, employing rectangular or RRC shaping filtering to generate a CAZAC oversampling sequence as a template function, calculating a cross-correlation matrix of an IQ signal and the template function, and enabling the CAZAC oversampling sequence to serve as the template function; a noise threshold is calculated based on the median power and the false alarm rate, dynamic threshold filtering is executed, a cross-correlation matrix after denoising is generated, and preliminary estimation of the time domain impulse response is completed; extracting multipath time delay and complex gain from the cross-correlation matrix by using an SAGE algorithm; drawing a power delay spectrum PDP for the channel impulse response; and performing alignment operation on the PDP in combination with the geographical location information of the transceiver during actual measurement. According to the method, the defect of traditional alignment in a severe scene is overcome, the statistical modeling accuracy is improved, the multipath time delay can be effectively aligned through experimental verification, and reliable support is provided for channel modeling.

The invention discloses an ultrasonic cross-metal channel estimation method based on improved block sparse Bayesian learning, and belongs to the field of ultrasonic cross-metal communication channel estimation. Constructing a pilot signal relationship between the receiving end and the transmitting end on the two sides of the metal wall; dividing a to-be-estimated metal channel impulse response into zero-value blocks or non-zero blocks of block sparse Bayesian according to whether the to-be-estimated metal channel impulse response is zero or not; the method comprises the following steps: iteratively updating hyper-parameters a, b, Bi and lambda of a non-zero block by adopting an expectation maximization algorithm, realizing structured sparse learning, calculating a maximum posteriori estimation result by utilizing a final hyper-parameter of the non-zero block, and taking the maximum posteriori estimation result as an estimation value of ultrasonic cross-metal channel pulse response. According to the method, a block sparse Bayesian learning algorithm is improved by utilizing the characteristics of metal channel pulse response, and compared with an original algorithm, the accuracy of channel estimation in a low signal-to-noise ratio environment is improved.

The invention discloses a ship channel modeling method for a marine unmanned aerial vehicle, and relates to the field of wireless channel modeling, and the method comprises the steps: obtaining the position information of an unmanned aerial vehicle and the position information of a ship; according to the position information of the unmanned aerial vehicle and the position information of the ship, constructing a three-dimensional model of the marine unmanned aerial vehicle to the ship channel; according to the three-dimensional coordinate system and the position relation, based on a sea surface fluctuation model and an unmanned aerial vehicle rotation model, coordinates of a receiving antenna and coordinates of a transmitting antenna are determined respectively; according to the three-dimensional coordinate system, the position relation, the propagation path, the coordinates of the receiving antenna and the coordinates of the transmitting antenna, determining the impulse response of the marine unmanned aerial vehicle to the ship channel; determining a space-time-frequency correlation function of the marine unmanned aerial vehicle to the ship channel; further carrying out modeling on the ship channel; according to the method, the non-stationary statistical characteristics of the marine unmanned aerial vehicle to the ship channel can be accurately described, and a theoretical basis is provided for design and performance optimization of an unmanned aerial vehicle auxiliary communication system in a complex marine environment.

An equalizer circuit includes: an analog front end circuit configured to receive an analog input signal from a transmission line; an analog finite impulse response filter circuit including: a sample and hold circuit configured to sample an output of the analog front end circuit; and a weighting circuit configured to weight the output of the analog front end circuit to generate a feedforward signal; and a decision feedback equalizer circuit configured to receive an output of the analog front end circuit and the feedforward signal.

The invention belongs to the field of quantum computing, and particularly relates to a distortion correction method for a quantum measurement and control link and a quantum computer, and the method comprises the steps: carrying out fractional expansion on a system function in a general expression form, and obtaining a system function expressed by a subitem of a target system function and a sum of products of corresponding coefficients, the target system function subitems are determined according to signal response characteristics of the quantum measurement and control link and comprise a pure zero item, a real pole item and a complex pole item, the pure zero item represents impulse response of finite length of the quantum measurement and control link, the real pole item represents exponential response of the quantum measurement and control link, and the complex pole item represents impulse response of finite length of the quantum measurement and control link. The complex pole item represents the oscillation attenuation response of the quantum measurement and control link; determining the reciprocal of the system function of the quantum measurement and control link as a distortion correction digital filter; a distortion correction digital filter is arranged on the quantum measurement and control link to correct signal distortion of the quantum measurement and control link. According to the invention, the distortion of the quantum measurement and control link can be rapidly corrected.

The application discloses a kind of fresh stewed bird's nest cold chain transport process temperature field monitoring method and system, belong to cold chain monitoring technical field.Through heat inertia pulse test, heat capacity and thermal resistance are obtained, which are respectively taken as node attribute and edge attribute;Optimize sensor distribution based on the principle of random walk entropy minimization;Construct a dynamically updated directed weighted heat propagation path graph;Using sparse deconvolution combined with system impulse response function matrix, separate event excitation and identify abnormal events;Linearize the heat balance inverse problem in the rolling time domain, reconstruct the product temperature sequence and heat flow vector, calculate the equivalent heat damage dose, and generate the solidified causal directed acyclic graph evidence chain.The above scheme integrates heat inertia into the graph model, realizes event and heat response separation, risk quantification and full-process traceability, effectively improves the accuracy and reliability of cold chain temperature monitoring.

The invention discloses a bearing fault diagnosis method based on feature mode decomposition and heterogeneous model fusion, and belongs to the technical field of mechanical fault diagnosis. An original vibration signal of the rolling bearing is collected; independent of any bearing geometric parameter or fault characteristic frequency information, a finite impulse response (FIR) filter is iteratively optimized to maximize a correlation kurtosis (CK) value, and a plurality of intrinsic mode functions (IMF) are adaptively decomposed; selecting first M IMFs with the highest CK value, extracting time domain, frequency domain and nonlinear complexity features of the IMFs, generating high-order derivative features by adopting depth feature synthesis DFS, and constructing an enhanced fusion feature vector; and finally, inputting a stacked integrated classifier consisting of six types of heterogeneous basic learners and an XGBoost element learner, and outputting a fault diagnosis result. According to the method, high-precision and high-robustness diagnosis can still be realized under the working conditions of speed change, strong noise and weak faults.

The application provides a lateral control method and device based on a vehicle dynamic prediction model, and the method comprises the following steps: inputting a first steering wheel steering angle in a target time window obtained in advance into the vehicle dynamic prediction model; performing convolution on the input first steering wheel steering angle in the target time window and a unit impulse response of the vehicle dynamic prediction model, to obtain a predicted yaw rate; and obtaining a predicted steering wheel steering angle based on the predicted yaw rate and a pre-established cost function. The application improves the accuracy of the predicted steering wheel steering angle, reduces the adjustment of an actuator while ensuring the accuracy, improves the durability of the actuator, and reduces the total cost of ownership (TCO); in addition, a large amount of operation data is used to iteratively optimize the constraint conditions in the algorithm, so that the automatic driving behavior is more accurate.

The application discloses a kind of arbitrary waveform nuclear pulse conversion methods, for the trapezoidal shaping of arbitrary waveform nuclear pulse signal.First, the arbitrary waveform nuclear pulse signal is regarded as the impulse response of rational fraction transfer function system.Second, rational fraction transfer function is decomposed into multiple first-order inertia link and the form of sum, then, multiple first-order inertia link and the form of sum is carried out Laplace inverse transformation into time domain expression, and then its time domain expression is discretized and transformed, then the parameter of discretized expression is obtained using particle swarm algorithm, finally, the transfer function of trapezoidal shaping and shaping recurrence formula are obtained, the trapezoidal shaping of arbitrary waveform nuclear pulse signal is realized to a certain extent, the symmetry of trapezoidal pulse is improved, the accurate acquisition of pulse amplitude is facilitated, the energy resolution of system is improved and the counting rate is improved, which has great significance for improving the precision of radioactivity measurement.