427 results about "Signal mapping" patented technology

The invention provides a display panel defect detection method and system based on multi-modal data fusion, and the method comprises the steps: obtaining multi-type representation data generated in a detection process of a display panel, and carrying out the feature mapping of the multi-type representation data; respectively mapping the panel appearance characterization data, the panel signal characterization data and the panel interlayer characterization data to a preset feature space to generate a cross-type mapping feature set, and performing feature association enhancement on the cross-type mapping feature set to obtain a cross-type mapping feature set; establishing an association relationship among the appearance mapping features, the signal mapping features and the interlayer mapping features, generating an association enhanced feature set, performing defect feature reasoning on the association enhanced feature set, extracting a feature combination conforming to a defect feature mode, and generating a defect feature reasoning result; and outputting a defect detection result of the display panel. According to the invention, the accuracy and reliability of the defect detection result of the display panel can be improved.

The invention provides an automatic operation process management method and device based on multi-sensor fusion, and relates to the technical field of automatic processes, and the method comprises the steps: constructing an instrument pose flow and operation field geometric model under a unified coordinate system through unified timestamp alignment and spatial geometry solution of multi-source sensor data; semantic segmentation and three-dimensional reprojection are combined to generate a shielding probability graph, cross-channel compensation reconstruction is carried out, and the image integrity is improved. And forming a conflict risk set through voxel field discretization and short-time prediction, and performing combined solution with standardized operation process constraints to generate a scheduling instruction and a safety time window. And finally, mapping the image, the pose and the physiological signal to a knowledge graph, and outputting consistency judgment and deviation correction suggestions in combination with a time sequence attention recognition process node. According to the method, the problem that the operation process management is not accurate enough due to the problems of view overlapping and the like of multi-source sensor data can be solved.

The invention discloses a real-time fatigue monitoring system based on an EEG signal, and relates to the technical field of neural regulation and control, and the system comprises a chaos reconstruction module which collects an original EEG signal, carries out the phase-space reconstruction of the original EEG signal through a chaos attractor processor, generates a chaos trajectory tensor, and carries out the phase-space reconstruction of the original EEG signal when the Lyapunov index of the chaos trajectory tensor exceeds a preset index threshold value, outputting a low-speed frequency band oscillation component and a high-speed frequency band oscillation component; and the closed-loop termination module is used for terminating the physical light field projection when the continuous detection periods of the updated alertness drop probability value, cognitive overload probability value and physiological fatigue probability value are all lower than a preset safety threshold value. Through multi-scale recursion phase space reconstruction, an original EEG signal is mapped to a three-dimensional chaotic trajectory tensor space, and dynamic frequency band decoupling is triggered by using a Lyapunov exponent threshold.

The invention relates to the field of chip testing, in particular to a chip signal integrity test analysis method, device and equipment and a storage medium. The method comprises the following steps: extracting a chip performance index based on a chip design requirement document; performing saturation frequency excitation setting based on the chip performance index to generate an excitation test signal; performing a multi-port signal excitation test and parallel signal sampling based on the excitation test signal to generate a high signal-to-noise ratio response data set; obtaining a chip layout design file; performing chip communication link analysis on the chip layout design file, and constructing communication line layout data; performing signal mapping and waveform quality evaluation on the communication line layout data based on the high signal-to-noise ratio response data set to obtain a node signal distortion rate; and performing signal integrity quantization and theoretical signal integrity score comparison based on the node signal distortion rate, and marking a fault node. According to the invention, the chip testing efficiency is improved, and the signal abnormal part of the chip is accurately and efficiently detected.

The invention relates to the technical field of medical treatment, in particular to a multi-parameter collaborative infusion process intelligent monitoring and priority calling method, which comprises the following steps of: acquiring four-dimensional monitoring data through a liquid level pressure sensor array, an infrared dripping speed detection module, a flexible temperature patch and a photoelectric heart rate sensor, and combining an LSTM (Long Short Term Memory) anomaly prediction model, and outputting the pipeline state score, the allergy risk index and the infusion progress prediction value in real time. And generating a real-time risk value through a weight configuration mechanism and stage identification logic, judging a risk level according to a dynamic threshold value, and outputting a corresponding early warning level signal. And the system further maps the early warning level signals into common, emergency and critical call instructions, and distributes the common, emergency and critical call instructions to a multi-channel execution terminal to construct a multi-level linkage response mechanism of closed-loop feedback. According to the invention, the accuracy and response efficiency of infusion risk identification can be significantly improved, and the method is suitable for intelligent reconstruction and automatic early warning response scenes of a clinical nursing information system.

The invention provides a multi-channel one-core multi-detection integrated detection method, which is applied to the technical field of in-vitro diagnosis and comprises the following steps: acquiring time sequence original signals of blood routine, liver function and kidney function channels; obtaining a baseline stable primary signal through cross-channel baseline trend coupling and adaptive correction; adopting a machine learning model to identify interference components and performing component offset to obtain a decoupling signal; mapping the decoupling signal into a physiological parameter value and carrying out rationality test; when the low credible parameter exists, a rechecking mechanism is triggered; performing weighted fusion on the basis of the rationality test result and the recheck signal to obtain a comprehensive parameter set; and finally generating a comprehensive detection report containing the credibility score. Cooperative processing and fusion analysis of multi-channel detection signals are realized, and the accuracy and reliability of a detection result are remarkably improved through interference identification and a dynamic recheck mechanism.

The invention provides a helicopter cable fault detection system and method, and belongs to the technical field of helicopter electrical system detection. The system comprises a positioning and matching device and a multi-modal signal analysis device, the positioning and matching device determines the relative position with a to-be-detected aviation plug through a dual-spectrum camera, generates a contact coordinate matrix and a contact and probe mapping table, injects a test signal to identify the contact material so as to obtain a topology result, and detects the contact pressure; and the multi-modal signal analysis device is used for matching parameters based on the topology result and the mapping table, setting a detection signal, positioning the contact, applying a signal in combination with pressure, acquiring a response signal, establishing a mapping table, and analyzing the response signal to generate a contact and fault result mapping table. According to the invention, the whole process automation from aviation plug positioning, signal detection to fault analysis is realized, the system can complete the core links of contact coordinate generation, signal mapping, fault determination and the like without manual intervention, and the detection efficiency is greatly improved.

The invention belongs to the technical field of communication, and particularly relates to a high-robustness multi-channel frequency shift Chirp modulation signal generation method and system for a time-frequency doubly selective channel. The method comprises the following steps of: 1, calculating robust code digits based on statistical characteristics of time delay and Doppler frequency shift of an ionized layer channel; 2, based on the number of robust code bits in the step 1, setting an address code, and realizing RO-MFSCM signal mapping of binary information bits; 3, modulating and transmitting the RO-MFSCM signal based on the information mapping in the step 2, thereby realizing the transmitting process of the RO-MFSCM signal; step 4, based on the emission signal in the step 3 and the robust code digit in the step 1, the receiver carries out robust domain energy aggregation on the RO-MFSCM signal; and step 5, based on the multi-channel robust domain energy aggregation signal in the step 4, adopting a multi-channel parallel demodulation algorithm and de-mapping to realize the receiving process of the RO-MFSCM signal under the time-frequency doubly selective channel. The method aims at the transmission fading problem of the FSCM signal in the ionosphere time-frequency doubly selective channel.

The invention relates to the technical field of thunder and lightning signal sampling, and discloses a GAN-based thunder and lightning very-low-frequency electromagnetic wave signal up-sampling method, a terminal and a medium. The method comprises the following steps: preprocessing a lightning very-low-frequency low-sampling signal and a real high-sampling signal; constructing a generative adversarial network; the generator is used for extracting initial features from the low-sampling signals and performing residual enhancement, then mapping low-sampling features after residual enhancement to a high-sampling dimension through a feature-guided dynamic interpolation mechanism, and performing correction and signal mapping on intermediate features after interpolation to obtain reconstructed signals matched with a target high-sampling rate; the discriminator is used for reconstructing the authenticity probability of the signal; after a generator and a discriminator are jointly trained by adopting an alternative updating mode of discriminator loss and generator loss, a newly input low sampling signal is preprocessed, and a corresponding reconstruction signal is output through the generator. According to the invention, accurate reconstruction from a lightning very-low-frequency low-sampling signal to a high-sampling signal is realized.

The invention relates to the technical field of radar signal processing, and discloses a complex ground reflection environment-oriented dual-path target detection method, which comprises the following steps of: performing quantile truncation and discretization processing on original range profile data, mapping a processed signal to a D-channel discrete feature space and generating a D-dimensional discrete feature matrix; the D-dimensional discrete feature matrix is input into a dual-channel parallel processing architecture, a CFAR adaptive detection module is adopted in a first path to suppress strong clutters to generate a first response matrix, and a false attention mechanism is adopted in a second path to enhance weak targets to generate a second response matrix; performing spatial alignment and weighting processing on the first response matrix and the second response matrix, and performing cross-domain confidence fusion to output a comprehensive response matrix; and carrying out fixed threshold binarization processing on the comprehensive response matrix based on a global threshold to obtain a target detection result. The method has both local gain compensation and global adaptive suppression, and can realize more robust detection of a weak target under a complex background.

The invention discloses a spiral line three-dimensional positioning method for buried tap water pipeline distributed optical fiber temperature measurement. The method comprises the following steps: firstly, winding a sensing optical fiber on the outer wall of a pipeline in a cylindrical spiral line form; then, the temperature of the pipeline is monitored in real time through a distributed optical fiber Raman temperature measurement system; when the pipeline leaks to cause temperature abnormity, the system accurately positions the one-dimensional arc length L of an abnormal point along the optical fiber by using the optical time domain reflection principle; finally, the geometric parameters of the cylindrical spiral line and the measured arc length L of the optical fiber are creatively combined, and the coordinates of the leakage point in the three-dimensional space are calculated through a parameter equation. According to the method, one-dimensional temperature measurement signals are successfully mapped into three-dimensional space coordinates, the axial position of the leakage point along the pipeline and the radial direction of the leakage point on the cross section of the pipeline can be accurately determined at the same time, and the problem that accurate three-dimensional positioning cannot be carried out on the leakage point of the buried pipeline in the prior art is solved. The maintenance efficiency is greatly improved; and the maintenance cost is reduced.

A wearable electroencephalography device includes an ear cuff around an auricle of an ear comprising a curved structure conforming to contours of the ear, an electroencephalography electrode positioned on the ear cuff and contacting skin for detecting brain activity signals, a wireless controller integrated with the ear cuff and processing the brain activity signals from the electroencephalography electrode, and a wireless communication module transmitting the processed brain activity signals to an external device. The wearable electroencephalography device includes a mobile application receiving the transmitted brain activity signals from the wireless communication module, analyzing the brain activity signals using machine learning algorithms to determine emotional states of a user, and providing real-time feedback regarding the emotional states through a user interface. The mobile application comprises a self-report interface allowing the user to input subjective state data and a live-feed interface displaying real-time subjective state data derived from the brain activity signals.

The invention relates to an analog quantity selection method and system based on a Boolean switch, in particular to the field of industrial automation, and aims to directly realize signal mapping by adopting a pure hardware combinational logic circuit and thoroughly eliminate instruction execution time, so that the state change of a Boolean switch signal can be instantaneously reflected on analog quantity output; according to the method, real zero-delay switching is achieved, meanwhile, program adjusting algorithms in any form are avoided, disturbance phenomena such as overshoot or undershoot are completely eradicated from the principle, and high stability and accuracy of output signals are ensured. Finally, according to the technology, the control instruction can be accurately and synchronously issued without delay, and the response speed and the synchronization precision of the whole control system in a high dynamic response industrial scene are remarkably improved.

The invention discloses an automatic configuration method for dispatching access of plant station equipment, and the method comprises the steps: A, obtaining communication data from the plant station equipment, and enabling the communication data to comprise a frame structure field; b, based on the frame structure field, identifying a communication protocol type by comparing an initial identifier, a function code field and a frame length field; c, in combination with the communication protocol type and the equipment attribute field, an access configuration strategy template is matched, and the template comprises a communication parameter set, an interface adaptation rule and a signal mapping relation; d, generating a structured configuration data file according to the configuration strategy template; and E, deploying the configuration data file to a scheduling system to complete equipment communication registration and data interaction initialization.

The invention provides a radar signal anti-interference processing method and system based on a space-time attention mechanism. The method comprises the following steps: mapping an original horizontal polarization channel signal and an original vertical polarization channel signal into an interference suppression space, and generating a three-dimensional feature tensor comprising an amplitude component, a polarization phase difference component and an interference suppression residual component; according to the amplitude component, dividing a radar observation area into multiple layers of target blocks in a spatial dimension, and calculating a space-time association weight between adjacent layers of target blocks through a space-time attention mechanism; and according to the space-time correlation weight, screening out a plurality of target blocks meeting a preset continuous motion condition, and decoding a motion mode of the plurality of target blocks by using a long short-term memory network to generate an anti-interference target trajectory coordinate and a velocity vector. According to the method, the polarization characteristics and the space-time attention mechanism are fused, the anti-interference effect of radar signal processing in a strong interference environment is improved, and then the detection precision of the multi-target motion trail is improved.

The invention provides a method and a device for transmitting data, which can be applied to an OTN (Optical Transport Network) system, reduce the processing cost during service data mapping and achieve the purpose of improving the system performance. The method comprises the steps that firstly, i paths of first optical transport network (OTN) signals are mapped to second OTN signals, and the second OTN signals comprise n paths of third OTN signals; and then generating a fourth OTN signal from the second OTN signal based on the X-byte interleaving granularity, and sending the fourth OTN signal. Wherein the mapping granularity adopted for mapping the jth path of first OTN signal in the i paths of first OTN signals to the second OTN signal is nj * X bytes, the rate of the jth path of first OTN signal is nj times of the reference rate, i is an integer greater than or equal to 1, j is equal to 1, 2, 3... i, nj is an integer greater than or equal to 1, and n and X are integers greater than 1.

The invention discloses a method and an apparatus in a node for wireless communication. A node receives a first information block indicating a plurality of PRACH opportunities; the node receives a second information block indicating a target sub-band and at least one full duplex symbol; the first PRACH opportunity is one of the plurality of PRACH opportunities indicated by the first information block, and the first PRACH opportunity is overlapped between a time domain and at least one full duplex symbol indicated by the second information block; a synchronous broadcast signal is mapped to a valid PRACH opportunity of the plurality of PRACH opportunities, the validity of the first PRACH opportunity depending on a relationship of the first PRACH opportunity between the frequency domain and the target sub-band. The random access capacity is improved.

The invention discloses a blade flutter monitoring method and device, a monitoring system, a storage medium and a computer program product, and the method comprises the steps: carrying out the modal feature analysis of a blade to determine a flutter monitoring region, laying a flexible sensing element in the flutter monitoring region, and enabling the flexible sensing element to be used for collecting the strain signal of the blade; in the running process of the blade, real-time running parameters of the blade and real-time strain signals collected by the flexible sensing element are obtained; determining a reference strain signal corresponding to the inertial centrifugal force of the blade according to the real-time operation parameters and a preset mapping relation; the mapping relation is the mapping relation between the operation parameters of the blade and the reference strain signal; deducting the reference strain signal from the real-time strain signal to obtain a target strain signal corresponding to the aerodynamic force; and according to the target strain signal and a preset formula, calculating pneumatic work of the blade in a set vibration period, and according to the pneumatic work, judging whether the blade flutters or not. According to the scheme, the accuracy and the real-time performance of flutter judgment are improved.

A method may obtain a failure propagation model, wherein the failure propagation model comprises: a model representation of a plurality of hardware components, a set of hardware failure probabilities; and a logic that maps signals to the hardware components. A method may receive an alert signal from the aircraft. A method may map the alert signal to the plurality of hardware components. A method may perform a root-cause diagnosis of the alert signal that has been mapped to the plurality of hardware components comprising: determining via the failure propagation model, one or more combinations of hardware failures associated with the alert signal; and determining a probability of occurrence associated with the combinations of hardware failures. A method may display a report that includes combinations of hardware failures associated with the alert signal and the probability of occurrence associated with the combinations of hardware failures.

The invention relates to the field of virtual debugging, and particularly discloses a control program and a virtual debugging method of a cold roll forming machine shearing system, and the method comprises the steps: S1, building a virtual model comprising a feeding mechanism, a shearing mechanism, a servo driver and a photoelectric sensor in an NX MCD environment, outputting an accumulated feeding length and a sensor signal by the model, and receiving the position setting of a cutter; s2, a trimming procedure is written for an S7-1200 PLC (programmable logic controller) in a TIA Portal (TIA Portal); s3, two-way communication between the NX MCD and the PLC is established through OPC, the accumulated feeding length and a sensor signal are mapped into PLC input, and the cutter position set output by the PLC is mapped into NX MCD servo input; and S4, the two are simulated synchronously, control logic and parameters are optimized based on model feedback, and the target is to minimize fixed length error and motion instability. According to the invention, the problems of long field debugging period, high cost, inaccurate shearing triggering and unstable return in the prior art are solved, and the shearing precision and the operation reliability are improved.

The invention provides a reference signal transmission method and device, relates to the technical field of communication, and is used for improving the reliability and efficiency of information transmission. The method comprises: for a channel measurement reference signal to be sent on a time domain symbol of a wireless frame in a time domain, mapping the channel measurement reference signal to X subcarriers of a corresponding carrier in a frequency domain, the carrier being composed of continuous 157 subcarriers, and the X being less than or equal to 157; and sending the channel measurement reference signal on the X subcarriers through a target antenna port.

Disclosed are methods, systems, and computer-readable medium to perform operations including: generating a mapping pattern that comprises a length-4 frequency division orthogonal cover code (FD-OCC4), the mapping pattern for mapping demodulation reference signals (DMRS) in frequency to a plurality of resource elements in at least one orthogonal frequency-division multiplexing (OFDM) symbol, wherein the DMRS are associated with a plurality of DMRS ports; mapping, using the FD-OCC4, the DMRS to the plurality of resource elements in the at least one OFDM symbol; and transmitting a transmission comprising the at least one OFDM symbol.

The invention provides a digital human question-answering system, and the system comprises a voice receiving and processing module which is used for receiving the voice input of a user in real time, splitting the input voice, extracting the acoustic features of each frame of voice in real time, and caching the acoustic features of continuous frames to form a streaming data queue; the voice feature reasoning module is used for inputting the streaming data queue into a pre-training question and answer model and outputting a question and answer text result and a voice synthesis instruction in real time; and the digital human synchronous driving module is used for generating a synchronous voice signal based on the question and answer text result and the voice synthesis instruction, mapping the synchronous voice signal to a mouth shape mapping library and an action template library, generating a mouth shape sequence and a limb action sequence matched with the voice time sequence, and completing digital human broadcasting. According to the method, user text or voice input is received, the question and answer result is returned after model reasoning, and the digital person is driven to complete voice broadcasting.

The embodiment of the invention discloses a plasma operation electrode precise control method and system based on multi-dimensional signal mapping. The method comprises the steps that multi-dimensional signals in the working process of a plasma operation electrode are obtained; performing phase-space reconstruction on the multi-dimensional signal to obtain a state vector sequence representing the working state of the electrode; constructing a joint recursion plot based on the state vector sequence; joint recursion quantitative analysis is carried out on the joint recursion plot, joint recursion quantitative indexes used for representing multi-dimensional signal collaborative dynamic characteristics are extracted, and the joint recursion quantitative indexes at least comprise joint certainty, joint laminar flow, joint recursion rate and joint entropy; according to the corresponding relation between the joint recursion quantitative index and the plasma energy output stability, control parameters of a plasma generator are generated according to a preset mapping rule, and energy output of the plasma operation electrode is adjusted in real time according to the control parameters. The control precision is remarkably improved, thermal damage is reduced, and the operation safety is improved.

The present invention discloses a low-complex, reliable multidimensional orthogonal time-frequency space (ND-OTFS) modulation-based communication system for uplink and downlink wireless communication between resource-constrained Internet of Things (IoT) and machine-to-machine (M2M) devices comprising at least one transmitter configured to transmit bit stream involving N-Dimensional signal mapper and OTFS frame and at least one receiver configured to be integrated into said IoT or M2M devices, featuring a low-complexity detector for receiving the transmitted bit stream.

The invention relates to the technical field of micro-plastic detection, and discloses a quick micro-plastic detection method based on image recognition, which comprises the following steps: acquiring three-dimensional time domain fluorescence lifetime data under multi-wavelength excitation by tuning a pulse laser source and a time-dependent single photon counting (TCSPC) technology; then, dynamic harmonic Fourier transform is adopted to process the fluorescence attenuation signal, the harmonic order is adjusted according to the signal-to-noise ratio, and the frequency domain characteristics of the data are optimized; then, mapping a fluorescence attenuation signal to a quantum state space, extracting an intrinsic parameter of fluorescence lifetime through a variable component sub-algorithm, and further combining a high-order tensor decomposition model and a quantum optimization algorithm to optimize a tensor factor combination; and finally, reconstructing a fluorescence lifetime intrinsic parameter based on the combination of the matrix product state and the optimal tensor factor, extracting a feature vector, and applying the feature vector to classification and detection of micro-plastic types. According to the invention, through combination of quantum calculation and a classical algorithm, the precision and efficiency of micro-plastic type identification are improved.

The invention provides a hanger CAN signal processing method and device, equipment and an upper system. The hanger CAN signal processing method comprises the following steps: acquiring an original CAN message of a hanger CAN bus; according to a preset data frame structure, packaging the original CAN message to obtain a standardized data frame; analyzing the standardized data frame according to a preset frame description template and the frame identifier of the standardized data frame to obtain a CAN signal mapping relation; verifying the CAN signal mapping relation to obtain a verification result; when the verification result represents that the CAN signal mapping relation meets the preset verification requirement, the CAN signal mapping relation is stored in the data cache pool, processing of the CAN signals of the lifting appliance is completed, multi-protocol compatibility of CAN messages is achieved, redundant transmission of data is reduced, and the CAN signal transmission efficiency of the lifting appliance communication system is improved.

Described is a Neuromorphic Adaptive Core (NeurACore) cognitive signal processor (CSP). The NeurACore CSP includes a NeurACore local learning layer block that is operable for receiving as an input a mixture of in-phase and quadrature (I / Q) signals and mapping the I / Q signals onto a neural network to determine complex-valued output weights of neural states of the neural network. A global learning layer is included that is operable for adapting the complex-valued output weights to predict a most likely next value of the input I / Q signal. Further, a neural combiner is included that operable for combining a set of delayed neural state vectors with weights of the global learning layer to compute an output signal, the output signal being separate in-phase and quadrature signals.

A system and method of tracking vessel movers within a liquid handler system using sparse sensor assemblies. The method includes mapping received sensor signals to pre-characterized functions and determining the positions of the vessel movers with respect to a single sensor from the sensor assembly accordingly. The sensors in the sparse sensor assembly can be positioned to have no or minimal overlap between their sensing ranges.

The invention provides a magnetotelluric signal denoising method and system based on a multi-path fusion network. The method comprises the following steps: constructing and training a noise identification model and a signal mapping model based on the multi-path fusion network; inputting a noisy signal segment identified based on the noise identification model into the signal mapping model to obtain a pure signal segment or a noise contour; and finally, splicing the pure signal segments in sequence to obtain the magnetotelluric signal after noise reduction. According to the multi-path fusion network provided by the invention, three convolution layers with convolution kernels of different sizes and a convolution path of an activation function are arranged in a multi-path convolution module, and the multi-path fusion network is used for multi-scale signal feature extraction; and in an attention-enhanced multi-path feature fusion module, outputs of different paths are respectively input into channel attention, space attention and a convolutional layer, and the corresponding outputs are spliced in a channel dimension, so that fusion of multi-path features is realized. In addition, physical constraints are further introduced, and deep optimization is carried out on the two models.