12 results about "Nonlinear modulation" patented technology

This invention provides a production monitoring system for mirror cabinet processing equipment based on multi-source data, relating to the field of process control. The system acquires multi-source data from the mirror cabinet through an acquisition module and constructs a discrete mesh model; a deviation topology construction module generates directional selective edge weights and a nonlinear modulation function; a propagation control coupling module achieves synchronous iterative convergence of deviation states and control components; a topology constraint module identifies structural boundaries and divides control sub-regions; a region control module generates region control vectors, which are then decomposed into processing adjustment quantities and coupled in by the instruction module; and a feedback reconstruction module optimizes parameters based on the processing results. This invention enables deviation propagation to match the processing path, achieving bidirectional coupling of state and control, thus improving accuracy and control stability in the processing of complex curved surfaces and multi-material mirror cabinets.

This invention discloses a method, system, equipment, and medium for predicting the wear of sliding liners in wind turbine generators. The invention discretizes the continuous yaw process and calculates the dynamic equivalent contact pressure of the liner using real-time aerodynamic overturning moment to characterize the nonlinear modulation effect of wind load fluctuations on the normal pressure of the liner. Simultaneously, it combines a frictional heat generation model to calculate a transient thermal correction factor, quantifying the degradation of material wear resistance caused by temperature rise. Based on this, the actual physical yaw angle is corrected to a wear equivalent angle and historical data is accumulated. By comparing this with the material's ultimate wear threshold, the remaining life prediction result of the sliding liner is output. This invention overcomes the shortcomings of traditional linear estimation methods, significantly improving the physical realism and accuracy of liner wear prediction under complex variable operating conditions, and can effectively guide condition-based maintenance and proactive health management of the generator unit.

Provided in the present invention is an all-optical nonlinear activator based on dual-light-beam cavity field modulation, which can be applied to the technical field of optical computing. The activator comprises: an input end, an optical microcavity and an output end, wherein the input end is used for providing an input light beam; the optical microcavity is used for generating resonance, so as to excite and enhance an optical nonlinear effect; and the output end is used for outputting a nonlinearly modulated optical signal. Nonlinear modulation is performed on an optical field in the optical microcavity or on a transmission spectrum of the optical field in the optical microcavity by means of two coherent light beams having a phase difference, thereby forming nonlinear mapping between the light intensity of input light and the light intensity of output light, i.e., an all‑optical self-modulation process. An effective nonlinear operator is provided for all-optical computing, thereby accelerating the convergence of network training and inference, and improving the recognition accuracy of a model in different applications. Further provided in the present invention is an implementation method for the all-optical nonlinear activator based on dual-light-beam cavity field modulation.

The application discloses a kind of complex terrain area air pollution multi-source heterogeneous data fusion and space-time alignment method.For the problem that multi-source data is inconsistent in time scale, spatial scale is not matched and alignment error is large under complex terrain, first, the application obtains multi-source data and pre-processes;Then realize time alignment by using the method based on time distance and double weight of data quality;In spatial alignment, introduce the terrain factor of elevation, slope, aspect for nonlinear modulation;Then get collaborative expression by terrain constraint fusion and multi-source feature fusion;Finally, construct ensemble learning error correction model to correct space-time deviation, output unified dataset.The application significantly improves the spatial alignment accuracy of complex terrain area, reduces space-time alignment error, and provides reliable data basis for air pollution mechanism analysis and prediction.

This invention relates to the field of fault diagnosis and monitoring technology, and particularly to a method and system for diagnosing equipment faults. The method includes: acquiring electrical signals from both high-voltage and low-voltage sides of a transformer, extracting the fundamental frequency, instantaneous phase, and amplitude envelope; real-time monitoring of phase fluctuation variance, and when exceeding a preset threshold, extracting a complete sequence containing the steady-state segment before the disturbance and the attenuation segment after the disturbance; constructing a virtual zero-phase reference and performing differential preprocessing on the sequence; performing second-order rate-of-change operation on the processed sequence to obtain phase acceleration characteristics, and combining this with the amplitude envelope for nonlinear modulation mapping to construct instantaneous phase-change energy flow characteristics; classifying internal winding deformation faults and external power grid disturbances by calculating the time-frequency correlation index of the energy flow characteristics on both sides; extracting the sub-band energy distribution components of the internal fault signal, and using a fault fingerprint database to match and identify winding deformation patterns. This invention significantly improves the sensitivity of transformer winding micro-deformation diagnosis and the anti-interference capability of online monitoring.

This invention discloses a method and system for providing cold chain traceability data for chilled meat. By deploying IoT nodes within refrigerated trucks to collect environmental and image data in real time, and preprocessing the collected data to obtain standard cold chain traceability data, the system extracts time-cumulative features using GRU gated recurrent units. It then extracts spatial fluctuation features using a GCN graph convolutional network. A cross-attention mechanism is used to calculate the nonlinear modulation effect of the time-cumulative features on the spatial fluctuation features, and weight adjustments are made. The fused feature vector is input into a physical information neural network, combined with biochemical dynamics equations for prediction and correction, outputting the current comprehensive quality index of the chilled meat, which is then mapped and displayed on the user's end. This enables differentiated display across multiple user terminals, meeting the service needs of multiple stakeholders, including operators, regulators, and consumers.

This invention discloses an optical quantum neural network computing system based on an optical non-Hermitian evolutionary system architecture, belonging to the field of optical quantum neural network computing technology. It includes an optical quantum processing chip system and a control circuit. The optical quantum processing chip system comprises a quantum light source, an integrated optical quantum computing chip, and a photoelectric processing system. An optical non-Hermitian evolutionary system architecture is integrated on the integrated optical quantum computing chip. This architecture includes a linear unitary transform region, a linear non-unitary transform region, and a nonlinear modulation region. The quantum light source generates quantum state light signals and inputs them to the integrated optical quantum computing chip. The signals are sequentially processed through the linear unitary transform region, the linear non-unitary transform region, and the nonlinear modulation region. The output light signal is read by the photoelectric processing system and returned to the control circuit. This invention achieves a highly efficient optical quantum neural network chip architecture, overcoming the bottleneck of traditional optical quantum neural networks' difficulty in cascading probabilistic gate circuits and nonlinear functions, and possesses the computational advantages of large-scale and deep networks.

The application discloses a human body kinetic energy collection device based on nonlinear magnetic response and belongs to the technical field of energy collection and wearable devices. The human body kinetic energy collection device comprises an upper stator disc, a lower stator disc, a rotor magnet disc, an eccentric mass block and a nonlinear modulation magnet. The upper stator disc, the rotor magnet disc and the lower stator disc are coaxially stacked to form a containing cavity for the rotation of the rotor. The eccentric mass block is fixed to the outer edge of the rotor magnet disc and provides an eccentric driving torque by using the gravity component when the human body arm swings. The nonlinear modulation magnet is fixed to the gap of the trapezoidal coil on the stator disc, and the periodic interference between the alternating magnetic poles of the rotor magnet disc and the rotor magnet disc is generated when the rotor rotates, thereby constructing a single-dual stable nonlinear potential energy field. The nonlinear electromagnetic micro energy capture device is used for efficiently collecting the low-frequency and random arm swing kinetic energy of the human body, and the limitation of the narrow resonant frequency band and high starting threshold of the conventional single stable linear system is broken through.

The application discloses a building concrete internal defect ultrasonic detection signal processing method and system, belongs to the material nondestructive testing technical field, and the method comprises the following steps: configuring a full matrix capture array to collect multi-channel original time domain data; performing a time domain flip operation on the data and mapping to the full matrix capture array to perform a synchronous retransmission algorithm; extracting sum frequency and difference frequency amplitudes of specific frequency components in the matrix, and constructing a nonlinear amplitude coordinate mapping table; performing statistical analysis on a full-field energy focusing distribution matrix, performing a difference operation with the sum frequency component amplitudes to generate a defect response coordinate set; and feeding back the coordinate set to the full matrix capture array to trigger supplementary scanning and update the matrix. The application adopts dual-frequency nonlinear modulation and time reversal focusing technology, can effectively suppress aggregate scattering noise interference, and improves the three-dimensional imaging precision and detection signal-to-noise ratio of concrete micro defects.

This application provides a digital management system for metabolic diseases based on the fusion of multi-source data from integrated traditional Chinese and Western medicine (TCM) and relates to the field of medical and health information processing technology. It first preprocesses the multi-source heterogeneous raw data according to sampling frequency characteristics, and then maps both to a unified feature space through a dual-stream coding network. In the fusion stage, TCM macroscopic constitution characteristics are used as query conditions to apply cross-modal attention modulation to Western medicine microscopic fluctuation characteristics, achieving deep fusion at the temporal and semantic levels. The fused features are simultaneously output as metabolic trend predictions and syndrome evolution inferences via a dual-path decoding network. Furthermore, a dynamic modulation mechanism for syndrome sensitivity is introduced in the intervention decision-making stage, using the syndrome probability distribution to nonlinearly modulate the risk penalty parameter in real time. This solves the problems of static threshold models failing to reflect the concept of treating different diseases with the same method and the break in the TCM-Western medicine synergy link at the decision-making level, realizing end-to-end TCM-Western medicine synergistic management from data collection to closed-loop intervention.

This invention discloses a recurrent neural network physical architecture based on artificial surface plasmon supercells, relating to the interdisciplinary fields of metamaterials, surface plasmons, and brain-like computing. The architecture consists of multiple identical planar network layers stacked sequentially in the vertical direction. Each layer includes a dielectric substrate (1), an SSPP supercell array (2), a bi-line divider (3), and a combiner (4). The SSPP supercell array is connected to inter-layer feedback links via vias. Its output is divided into an output path and a feedback path by a bi-line divider. The feedback path integrates an RF amplifier (5) for gain compensation and transmits the signal across layers to the combiner in the next layer for vector superposition with the new input signal. This architecture integrates temporal feature extraction, nonlinear modulation, and recursive computation, possessing ultra-high-speed parallel processing capabilities, and can effectively realize deep fusion and associative decision-making of multimodal information based on the nonlinear coherence effect of SSPP waves.

The application discloses a building concrete internal defect ultrasonic detection signal processing method and system, belongs to the material nondestructive testing technical field, and the method comprises the following steps: configuring a full matrix capture array to collect multi-channel original time domain data; performing a time domain flip operation on the data and mapping to the full matrix capture array to perform a synchronous retransmission algorithm; extracting sum frequency and difference frequency amplitudes of specific frequency components in the matrix, and constructing a nonlinear amplitude coordinate mapping table; performing statistical analysis on a full-field energy focusing distribution matrix, performing a difference operation with the sum frequency component amplitudes to generate a defect response coordinate set; and feeding back the coordinate set to the full matrix capture array to trigger supplementary scanning and update the matrix. The application adopts dual-frequency nonlinear modulation and time reversal focusing technology, can effectively suppress aggregate scattering noise interference, and improves the three-dimensional imaging precision and detection signal-to-noise ratio of concrete micro defects.