1826 results about "Distortion" patented technology

The invention relates to the technical field of integrated circuit test and calibration, and discloses a chip test and calibration method and a chip tester. The chip test calibration method is applied to a chip test module and specifically comprises the following steps that S101, a starting signal sent by a user terminal is received, environment initialization operation is executed, and after initialization is completed, a system automatically enters a standby mode and waits for an external trigger signal or a user instruction; and S102, synchronously capturing input and output signal waveforms of the tested chip at a preset sampling frequency through a high-precision current sensor and a voltage sampling circuit. Through a dynamic parameter acquisition and real-time compensation technology, a voltage reference error is effectively reduced, the temperature control precision is superior to + / -0.3 DEG C, signal distortion caused by environmental interference is effectively inhibited, a multi-dimensional calibration model is combined with time domain, frequency domain and statistical characteristic analysis, nonlinear errors and system drift can be dynamically corrected, and the system performance is improved. And the attenuation error of a test signal transmission path is lower than 0.02 dB.

The invention discloses a microwave radio frequency link multi-index comprehensive measurement method, and relates to the technical field of radio frequency communication testing, and the method comprises the following steps: S001, building a peak power prediction model, generating a peak power probability curve based on the statistical distribution characteristics of a plurality of carrier signals, and forming a peak early warning vector containing an estimated time point and an amplitude value; and S002, executing synchronous sampling scheduling according to the peak early warning vector, and by adjusting a sampling trigger threshold and a time window parameter, enabling a sampling window to aim at peak power occurrence time and cover a time interval of amplitude limiting protection. According to the method, through peak value prediction, accurate sampling, multi-dimensional difference and distortion identification, efficient capture and dynamic regulation and control of amplitude limiting abnormity are realized, a prediction-identification-adjustment-optimization closed-loop process is constructed, the monitoring integrity and adaptive capacity of a microwave radio frequency link to sudden distortion are remarkably improved, and stable operation of a system is guaranteed.

The invention relates to the technical field of data processing, in particular to an accelerometer vibration rectification error analysis method, which comprises the steps of receiving multiple paths of accelerometer original current signals, processing acquired data and outputting a feature point coordinate sequence with confidence; according to the confidence and the optimization algorithm combination in the frequency band distribution characteristic dynamic scheduling knowledge base, calculating a local statistical data set; inputting the data set into a mechanical dynamics model to execute trajectory simulation, and inputting a control model reconstruction signal to compare a dual-path positioning drift distance difference to generate an error correction coefficient matrix; outputting a knowledge base updating instruction and a parameter resetting instruction by adopting a matrix reconstruction vibration rectification error quantized value; a quantized value is imported to calculate theoretical angle deviation and verify convergence, and the neural network is triggered to be retrained when the deviation exceeds a threshold value. Through a non-smooth feature extraction algorithm and a closed-loop feedback mechanism, the problem of signal distortion caused by smooth operation in the prior art is solved.

The invention relates to the technical field of flow measurement and control, and particularly discloses a cheese filling flow real-time calibration control method and system.The cheese filling flow real-time calibration control method comprises the following steps that working condition information of cheese in a filling pipeline is collected in real time, and the working condition information comprises the temperature, the pressure, an original flow signal, the pump rotating speed and the proportional valve opening degree; dynamically selecting a filtering order according to the signal-to-noise ratio of the original flow signal, and outputting the filtered flow; and based on the acquired working condition information, predicting the dynamic viscosity of the cheese in real time through a neural network, fitting a flow-working condition relation function and calculating a target flow value. The signal-to-noise ratio of an original flow signal is dynamically adapted to optimize filtering processing, signal distortion caused by interference such as temperature drift and mechanical vibration is effectively eliminated, and the flow detection precision is improved; by means of the neural network, the dynamic viscosity of cheese is predicted in real time, the model is dynamically adjusted, the problems that traditional viscosity estimation lags behind, and the batch adaptability is poor are solved, and an accurate basis is provided for flow target value calculation.

The invention relates to the technical field of power distribution networks, and discloses a power distribution network fault self-recovery method and system based on machine learning, and the method comprises the steps: collecting the multi-source fault feature data of a power distribution network in real time, including the voltage and current waveform distortion feature, the load sudden change feature and the equipment temperature anomaly feature; and inputting the multi-source fault feature data into a multi-stage classification model for processing, and by setting a pseudo fault filtering module, establishing a typical interference feature library and setting dynamic filtering thresholds for different working conditions during real-time fault detection of the power distribution network, so that the recognition accuracy of various interference signals is ensured, and the fault detection accuracy of the power distribution network is improved. Meanwhile, similarity comparison is carried out on real-time collected data and pseudo fault features, whether the problems of signal distortion and noise pollution occur at the fault positioning position of the power distribution network or not can be detected in real time, the accuracy of fault type recognition is ensured, the misjudgment risk is reduced, and when strategy adaptation is abnormal, the matching degree of the self-healing strategy and the actual state of the power grid is ensured.

The invention provides an electrical equipment remote maintenance guidance method and system. The method comprises the following steps: capturing an aperiodic torque waveform and a magnetic field gradient abnormal signal by deploying a torque fluctuation sensor and a magnetoresistive sensor; performing multi-scale frequency band division on the non-periodic torque waveform, screening out a transient high-frequency component in a start-stop stage of equipment, and separating out a magnetic field polarity reversal characteristic from a magnetic field gradient abnormal signal; performing cross-domain matching on the occurrence time of the transient high-frequency component and the spatial orientation of the magnetic field polarity reversal feature to generate a mixed feature mark; calculating a frequency band overlapping degree based on the time-frequency energy distribution marked by the mixed features and generating a coherence map; and matching a fault historical case library according to the coherence map, and outputting a maintenance strategy set aiming at the rotating shaft dynamic unbalance and electromagnetic interference superposition fault. According to the invention, through fusion of torque fluctuation and magnetic field distortion collaborative analysis, the precision of mechanical and electromagnetic composite fault diagnosis of the rotating shaft is improved.

The invention relates to the technical field of crane line fault diagnosis, in particular to a crane line fault diagnosis system and method based on multi-source data fusion, which comprises a data acquisition and processing unit, a mechanical and electrical coupling characteristic unit and a characteristic fusion and fault quantification unit, the three-axis vibration acceleration and the three-phase current waveform of the track are obtained through the data collecting and processing unit, the mechanical and electrical coupling characteristic unit conducts three-dimensional vector synthesis and wavelet packet decomposition on vibration data, and a time-space incidence matrix of harmonic distortion and vibration is constructed. And the feature fusion and fault quantification unit outputs coupling factors by using a bidirectional long-short-term memory network and an attention mechanism, and outputs a fault probability value through a dynamic time warping matching algorithm after time-frequency domain analysis and sample entropy judgment, so that time-space correlation modeling and dynamic fault matching of multi-source data are realized. And the fault positioning precision and the diagnosis accuracy are improved.

The invention discloses a wavefront reconstruction method for improving the dynamic range of a Shack-Hartmann wavefront sensor. Belongs to the technical field of wavefront detection. According to the method, a new Shack-Hartmann wavefront detection method is needed, the effective dynamic range of a Shack-Hartmann sensor can be expanded on the premise that the hardware complexity is not remarkably increased, local mismatching accumulation can be avoided through a reasonable matching strategy, and the detection accuracy is improved. Therefore, high-precision and high-reliability wavefront reconstruction can be realized in a large-amplitude wavefront distortion scene. Comprising the following steps: S1, detecting by a Shack-Hartmann wavefront sensor to obtain a light spot distribution diagram H (x, y); s2, extracting a light spot centroid pixel-level position through a matched filtering algorithm; s3, calculating the sub-pixel-level position of the mass center of the light spot through Gaussian interpolation; s4, a mass center-subaperture matching relation is established through a Kuhn-Munkres algorithm; and S5, calculating the wavefront slope according to the corresponding relationship between the centroid and the sub-aperture, and then recovering the wavefront according to the wavefront slope.

The invention relates to the technical field of earphone noise reduction processing, and discloses a motorcycle riding earphone noise reduction method combining different noise reduction algorithms, comprising the following steps: acquiring an original audio signal, and distributing the original audio signal to each processing module; a preprocessing signal is generated, voice activity information is determined, and environmental noise energy information is calculated; according to the environmental noise energy or the auxiliary information, adaptively adjusting a high-low noise energy threshold value; the original signals are input into the traditional and AI noise reduction module in parallel to generate two paths of noise reduction signals; based on the environment noise, the voice information and the threshold value, performing weighted fusion to generate an output signal; and carrying out equalization and compression processing on the output signal, and driving the loudspeaker to output. According to the invention, comprehensive judgment on environmental noise energy information, voice activity information and riding speed is introduced, an output signal of a traditional noise reduction module is set to be zero in a high-speed voice-free environment, and AI noise reduction is combined, so that tone quality distortion of a traditional noise reduction algorithm in a noise environment is effectively avoided.

The invention discloses a slant path atmospheric turbulence phase screen generation and light field transmission simulation method. Belongs to the technical field of satellite-ground laser communication. The method comprises the following steps: firstly, establishing a three-layer height spectrum model in a slant-range atmospheric turbulence environment, then generating an initial field suitable for vacuum and turbulence environments by using an angular spectrum method, and generating n corresponding random dynamic phase screens according to atmospheric turbulence characteristics of different heights on a slant-range path and distribution characteristics of atmospheric wind speed. Superposing the initial field and the first phase screen, performing two-dimensional Fourier transform, and performing inverse Fourier transform on the transform field by using an angular spectrum method to obtain field distribution in front of the next phase screen; and repeating the process to pass through n phase screens in sequence, and finally obtaining the output field distribution of the uplink and the downlink. The method can effectively simulate the effects of refractive index fluctuation, wavefront distortion, light intensity flicker and the like caused by oblique-range atmospheric turbulence, and provides important theoretical support and application value for researching oblique-range laser transmission characteristics.

The invention is suitable for the field of digital watermarking, and provides an anti-compression coding robust video watermark generation method based on an adversarial neural network, and the method comprises the steps: constructing an MSCA-GAN model; the model comprises an encoder, a decoder, a distortion layer, a discriminator network and an opponent network, and the specific steps are as follows: step S1, the encoder extracts different scale features of a video frame by using a multi-scale convolution attention mechanism, calculates attention weights, efficiently hides and embeds binary watermark information into the video, generates a watermark-containing video, and transmits the watermark-containing video to the decoder; performing confrontation optimization on an embedding strategy with a discriminator in training; according to the method, for H.264 compression layer special training, the multi-scale convolution attention mechanism and the depth separable convolution are combined, and the anti-compression robustness of the watermark under the H.264 standard is effectively improved; through common attack training such as noise layer simulation cutting and zooming, the watermark can still keep high extraction accuracy and robustness in a complex environment.

The invention discloses a multivariate monitoring data fusion method and system for a slope tunnel model test, particularly relates to the technical field of geotechnical engineering physical model test, and aims to solve the problem that dynamic stress waves in an existing model test integrating static and dynamic measurement cause static monitoring signal distortion and further influence the model state evaluation accuracy. Coupling interference in static signals is identified by synchronously collecting dynamic excitation and static response signals; obtaining signal samples before and after a model state sudden change event to perform frequency domain comparative analysis, identifying characteristic frequency components related to sudden change, and evaluating a coupling interference dominant frequency band; separating an effective static response component from the original static signal based on the frequency band; and finally, fusing the effective component with a soil dynamic parameter derived from dynamic excitation to generate comprehensive stability evaluation data. Dynamic interference is effectively suppressed, the authenticity of static signals is improved, and the reliability of model stability state evaluation is improved.

The invention provides a signal decoding method based on a PSI5 interface, and relates to the technical field of signal decoding, and the decoding method comprises the following steps: processing and adjusting a received PSI5 signal to obtain an accurate identification signal; and extracting a clock signal from the PSI5 signal, designing a clock compensation algorithm according to the quantum neural network, and dynamically adjusting the clock signal to obtain clock synchronization data. And determining a data frame boundary, and decoding the accurate identification signal to obtain original data. And performing comparative analysis on the original data and the PSI5 signal to obtain comparative difference data, judging whether the comparative difference data accords with a preset error type or not, and performing corresponding processing. According to the invention, fractional calculus processing is carried out on the received signal, then signal distortion is corrected by using a channel equalization method, and the quantum neural network is constructed to dynamically adjust the clock signal, so that clock synchronization is realized, a reliable time reference is provided for accurate processing of the signal, and the accuracy of signal decoding is improved.

The invention belongs to the technical field of electrical equipment fault monitoring, and discloses a fault monitoring system for electromechanical installation engineering, which comprises a high-impedance fault identification module, extracts nonlinear harmonic features through current signals, constructs a frequency domain-time domain joint feature set in combination with space-time magnetic distortion in an electromechanical installation process, and performs fault identification on the nonlinear harmonic features through the high-impedance fault identification module. Non-linear characteristic response identification of the high-impedance fault is carried out, and a high-impedance fault characterization result is output; the transient fault capturing module is used for positioning a risk time window according to a high-impedance fault characterization result, and identifying the starting and ending boundaries of an electrical disturbance behavior in combination with a double-threshold mutation mechanism; synchronously extracting corresponding operation condition parameters, constructing a short-time process behavior model taking electrical disturbance as a source, and outputting a transient disturbance sequence; and the sensitivity of fault identification, the accuracy of positioning and the real-time performance of diagnosis are integrally improved.

The invention relates to the technical field of signal processing, and provides an intelligent sensing device electromagnetic interference suppression method and system based on AI identification, and the method comprises the steps: obtaining a multi-source electromagnetic signal set of a target intelligent sensing device in a preset monitoring period, and carrying out the electromagnetic interference feature extraction processing of the multi-source electromagnetic signal set, performing interference mode matching processing on the electromagnetic interference characteristic set based on a preset interference suppression model to generate an electromagnetic interference suppression strategy of the intelligent sensing equipment; the electromagnetic interference suppression strategy comprises a frequency band adjustment direction corresponding to an interference frequency band distribution characteristic, a signal gain compensation direction corresponding to an interference intensity fluctuation characteristic and an anti-interference filtering direction corresponding to an interference source correlation characteristic; and performing interference suppression operation on a signal acquisition module of the intelligent sensing equipment according to the electromagnetic interference suppression strategy so as to reduce the electromagnetic signal distortion rate of the intelligent sensing equipment.

The invention relates to the technical field of intelligent decision making, can be applied to business system platforms of financial science and technology, medical health and the like, and discloses an equipment adaptive control method and device, equipment and a medium, and the method comprises the following steps: obtaining a multi-modal signal of an equipment detection target, and constructing a dynamic reference system according to the multi-modal signal; performing space-time alignment optimization on the multi-modal signal according to the dynamic reference system to obtain a space-time alignment signal, and performing dynamic calibration on the space-time alignment signal to obtain a calibration signal; performing transient waveform distortion feature extraction on the calibration signal to obtain a signal distortion feature; performing feature space mapping on the signal distortion features to obtain a feature mapping result; and generating an equipment early warning grade parameter according to the feature mapping result and a preset safety boundary distance, and dynamically adjusting a preset equipment control parameter according to the equipment early warning grade parameter. By analyzing the multi-mode signal, the dynamic adjustment of the equipment control parameters is realized, and the equipment detection precision is improved.

The invention discloses a cable accessory aging assessment early warning method based on space charge characteristics. The method comprises the following steps: S1, collecting a non-alternating space charge signal, an environment temperature and an operation electric field intensity; s2, extracting multi-dimensional space charge characteristic parameters; s3, outputting an aging evaluation index, and determining an aging stage; s4, calculating a residual life prediction value; according to the method, the characteristics of multiple aspects such as charge accumulation, charge type proportion and electric field change of the cable accessory in the aging process can be comprehensively reflected, and the one-sidedness possibly existing in single parameter evaluation is avoided; space charge signal processing is optimized, alternating charge interference and attenuation and distortion influences in the signal propagation process are effectively eliminated, and the reliability of signal processing is improved. By triggering fault early warning and calculating the residual life prediction value, potential faults of the cable terminal can be prevented, and safe and stable operation of a power system is guaranteed.

The invention provides an exoskeleton mountaineering intention recognition method and system and a storage medium, and belongs to the technical field of exoskeleton robot control, and the method comprises the steps of signal preprocessing and compensation, hierarchical feature extraction, multi-modal fusion recognition, control output, safety protection and the like. The method comprises the following steps: performing 50Hz power frequency filtering and 20-450Hz band-pass filtering on an electromyographic signal, and compensating signal distortion caused by muscle deformation by combining IMU (Inertial Measurement Unit) acceleration data; a dynamic four-dimensional channel is adopted to preferably extract myoelectricity features, and an improved attention mechanism model is utilized to extract multi-scale features; fusing multi-modal information such as myoelectricity and terrains based on a Bayesian fusion framework to realize intention recognition; meanwhile, triple safety protection strategies of joint angle hard limiting, falling detection and protection and signal loss fault-tolerant processing are set; the accuracy and control speed of motion intention recognition are improved, good safety performance is achieved, and the auxiliary effect and reliability of the exoskeleton in the mountaineering motion are effectively improved.

The invention discloses a Bluetooth hearing-aid earphone optimization method and system for adaptive hearing compensation. The method comprises the following steps: S1, acquiring a personalized hearing curve of a user and background audio data of left and right ears in each typical scene, and respectively preprocessing the background audio data; s2, extracting time-frequency fusion features of each typical scene, generating scene feature vectors, and constructing a scene feature vector library; s3, calculating a scene perception conversion vector, an abrupt change risk vector and a smooth gain vector; s4, calculating a binaural gain change vector, a binaural synchronous entropy vector, a phase alignment factor vector and a left and right ear cooperative gain vector; and S5, according to the left and right ear cooperative gain vectors, processing the background audio data after left and right ear preprocessing in the current scene, and outputting the processed background audio data to the Bluetooth hearing-aid earphone. According to the invention, the problem of gain abrupt change generated during scene switching of the existing Bluetooth hearing-aid earphone and the problem of spatial perception distortion caused by binaural coordination imbalance can be solved.

The invention relates to the technical field of wireless communication, and discloses a compensation method for electronic radio frequency communication. According to the compensation method for the electronic radio frequency communication, the radio frequency signal and the channel state information are acquired, the original data set is generated, and the preprocessing steps of denoising, signal amplitude correction, phase correction and the like are performed, so that the data quality is improved, accurate parameter evaluation is performed by adopting the minimum mean square error, the accuracy of channel characteristic parameters is ensured, and the communication quality is improved. A mathematical model constructed based on the parameters enables calculation of compensation parameter gain and phase deviation to be more accurate, so that attenuation and distortion caused by signal propagation in a channel are effectively compensated, and finally, quality evaluation is carried out on the bit error rate and the signal-to-noise ratio of the compensated signal, so that the compensation effectiveness is ensured, and the signal quality is improved. And if the compensation is invalid, the calculation can be returned in real time for recalculation, so that the quality of the whole signal is improved.

The invention discloses a multi-channel parallel sampling high-dynamic response analog-to-digital conversion method, system and equipment and a storage medium, and belongs to the technical field of power electronics and signal processing, and the method comprises the steps: configuring a high-speed analog-to-digital converter channel to form a parallel sampling module, carrying out the alternate sampling of an input power grid analog signal, and generating a discrete sampling sequence group; inputting to a control unit to extract feature data, and calculating to obtain a fluctuation feature value; constructing a channel clock control vector, sending the channel clock control vector to each high-speed analog-to-digital converter channel, adjusting a sampling trigger moment, and re-executing analog signal sampling to obtain a sampling sequence after phase compensation processing; performing waveform reconstruction processing to obtain continuous reconstruction waveform data; and performing electric energy integral operation, and outputting a dynamic metering result. According to the invention, the problems of slow response, sampling distortion and large metering error of the analog-to-digital conversion system under the conditions of frequency fluctuation, unsteady disturbance and bidirectional power in the prior art are solved.

The invention relates to the technical field of audio encoding and decoding, in particular to a fast encoding and decoding method and system for real-time audio. The method comprises the following steps: acquiring real-time sampling data of an input audio stream, and performing multi-time-point sliding window division and coding preprocessing to generate a coding preprocessing enhanced audio; carrying out adaptive quantization strategy analysis on the coding preprocessing enhanced audio, carrying out multi-level residual quantization modeling, and constructing a real-time increment coding mapping table; performing multi-module decomposition execution based on the real-time incremental coding mapping table, performing multi-thread parallel coding optimization, and constructing a real-time audio parallel coding strategy; and carrying out real-time coding processing according to a real-time audio parallel coding strategy, and carrying out task-by-task code rate distortion optimization to obtain an optimal coding parameter of each coding task. According to the invention, high-fidelity and low-delay audio coding and decoding are realized, and the auditory experience of a user is improved.

The invention relates to the technical field of three-dimensional measurement, and discloses a coating thickness measurement method and system based on a multi-source sensor, and the method comprises the steps: obtaining and fusing point cloud data of the multi-source sensor, and constructing a three-dimensional curved surface model of a component through curvature analysis and normal vector estimation; calculating an optimal incident angle of the sensor relative to each area of the curved surface based on the model, and generating a dynamic attitude adjustment parameter; according to the parameters, the three-axis attitude of the sensor is adjusted in real time for signal acquisition, and original measurement data are obtained; frequency domain analysis is carried out on the original data to diagnose reflection distortion, and correction is carried out in combination with time domain filtering and spatial domain smoothing; and finally, calculating a thickness value in combination with the three-dimensional model, detecting and repairing a data missing region by using Fourier transform and an interpolation algorithm, and generating a complete thickness distribution diagram. According to the invention, high-precision and automatic measurement of the thickness of the complex curved surface coating is realized.

The invention relates to the technical field of audio and video transmission, in particular to an internal and external network audio and video secure transmission method and system based on a cloud platform. By combining the load balancing technology with the real-time load state and the audio and video stream characteristics of the cloud platform, the encrypted traffic can be dynamically distributed to a plurality of back-end servers, and the calculation overhead in the encryption process can be effectively reduced through selection of the lightweight asymmetric encryption algorithm and the optimized key exchange process; in a handshake stage, by optimizing a key negotiation process and adjusting a key exchange process according to segmentation characteristics, the execution efficiency of a protocol is further improved, and by dynamically adjusting the execution opportunity of encryption operation, it is ensured that the encryption operation is executed at a proper opportunity, and the encryption efficiency is improved. By monitoring and adjusting the load distribution strategy and the encryption parameters in real time, the system operation mode can be dynamically adjusted according to the distortion degree and the transmission state of the audio and video streams, and the distortion degree of the audio and video streams is effectively reduced.

The invention provides an accurate calculation method and system for the axial pretightening force of an ultrasonic bolt, and the method combines a high-order statistic theory with a nonlinear filtering technology, and solves the problem that the measurement precision of a conventional method is insufficient under the conditions of strong noise and nonlinearity. Particle filtering and Kalman filtering are combined, so that the problem that a traditional Kalman filtering method easily causes sensitivity of an initial value of filtering divergence is solved; a double-Gaussian attenuation model is adopted to fit an echo envelope, the problem that a single Gaussian or single index model cannot adapt to envelope distortion caused by stress change is solved, and a nonlinear state space model is established to adapt to nonlinear echo signal characteristics under dynamic stress; gaussian noise is effectively suppressed by using a third-order cumulant cross-correlation algorithm, the time difference resolution in a low signal-to-noise ratio environment is remarkably improved, and the Gaussian noise and asymmetric interference are effectively suppressed.

The invention relates to the technical field of elevator operation and maintenance, and discloses a multi-source data fusion method and system for elevator fault localization, and the method comprises the steps: carrying out the noise filtering and data alignment of multi-source monitoring data of an elevator during operation, and obtaining a monitoring data set; performing time-frequency analysis on acceleration sensor data in the monitoring data set to obtain vibration mode characteristics; performing harmonic analysis on the motor current data to obtain current distortion characteristics; performing space-time correlation on the vibration mode characteristics, the current distortion characteristics and the safety loop state in the monitoring data set to obtain a comprehensive fault characteristic vector; according to the comprehensive fault feature vector, specific components and types when the elevator breaks down are determined, so that fault positioning information is obtained; the fault positioning information is transmitted to an elevator monitoring terminal, and the elevator is maintained according to the fault positioning information; according to the invention, the fault positioning efficiency can be improved.

The invention discloses a nonlinear correction method, device and equipment for excitation characteristics of a mutual inductor, and particularly relates to the technical field of mutual inductors. The method comprises the following steps: acquiring original data corresponding to a mutual inductor, wherein the original data comprises an original current signal, historical magnetic flux and distributed temperature data; performing noise reduction processing on the original current signal to obtain a purified current signal, and determining a magnetic conductivity correction coefficient and a temperature gradient according to the distributed temperature data; inputting the purification current signal and the magnetic conductivity correction coefficient into a hysteresis model to obtain a real-time magnetic flux, and inputting the purification current signal, the distributed temperature data, the temperature gradient and the historical magnetic flux into a magnetic flux correction network to obtain a magnetic flux correction value; and compensating the real-time magnetic flux according to the magnetic flux correction value to obtain a corrected magnetic flux result of the mutual inductor. According to the invention, multi-physical field fusion input can be realized, transient response can be improved, harmonic distortion compensation can be carried out, and high precision of data can be maintained.

The disclosure deals with system and method for discerning the radius maximizing reliability for binary modulation on conjugate-reciprocal zeros (BMOCZ) implemented with both a maximum likelihood (ML) and direct zero-testing (DiZeT) decoder. The optimal radius for BMOCZ is disclosed to be a function of the employed decoder. The radius maximizing the minimum distance between polynomial zeros does not maximize the minimum distance of the final code. While maximizing zero separation offers an almost optimal solution for the DiZeT decoder, the ML decoder outperforms the DiZeT decoder in both additive white Gaussian noise (AWGN) and fading channels when the radius is chosen to maximize codeword separation. Different sequence-to-subcarrier mappings for BMOCZ-based orthogonal frequency division multiplexing (OFDM) are analyzed to highlight a flexible time-frequency mapping approach that avoids distortion introduced by a frequency-selective channel at the expense of higher peak-to-average power ratio (PAPR).

The invention relates to the technical field of on-line monitoring, in particular to an insulation fault on-line monitoring method and system for a medical IT system control cabinet. The method comprises the following steps: selecting a non-integer frequency multiplication detection frequency according to equivalent ground distributed capacitance in a previous monitoring period, and superposing the non-integer frequency multiplication detection frequency with a fundamental frequency to form a composite signal injection system; collecting signals to calculate a voltage instantaneous harmonic distortion rate change gradient, and selecting a time window to split the leakage current according to the change gradient; on the basis of dispersion estimation signal-to-noise ratio weighted fusion current vectors, insulation resistance and distributed capacitance are calculated; constructing a four-dimensional original feature vector composed of the insulation parameter, the phase difference and the intermodulation component energy; constructing a diagonal weighting matrix based on the resistance-capacitance ratio and the gradient to transform a feature vector, and determining the fault attribution through the Mahalanobis distance calculation with the fault template library. According to the scheme, harmonic interference can be avoided, calculation stability can be improved, insulation instantaneous sudden change can be quickly responded, and different fault types can be accurately distinguished to guide maintenance.

The invention discloses a Beidou and UWB dual-mode cooperative rail transit positioning method, and particularly relates to the technical field of fusion positioning, and the method comprises the following steps: constructing a cross-modal distortion discrimination array based on the space coverage state of two types of signals in a train path, recognizing a track mutation region, and dynamically adjusting the signal fusion weight; abrupt change points are corrected through a constraint backtracking trajectory fitting algorithm, and pseudo trajectory points are eliminated in combination with a positioning base station space topological structure; performing time sequence analysis on the signal fusion weight change, and if a frequent signal hopping trend exists, lowering the related fusion weight to the lowest tolerance threshold value to improve the track continuity and the positioning robustness; according to the method, the cross-modal distortion discrimination array is constructed, accurate identification of a track mutation region is realized, abnormal track points are effectively corrected in combination with fusion weight dynamic adjustment and a constraint backtracking track fitting algorithm, a signal jump trend is suppressed through a time sequence analysis mechanism, and the stability and positioning precision of track fusion are improved.