19 results about "Signal compression" patented technology

This invention discloses a sleep stage identification method, comprising: a multimodal data acquisition step; a preprocessing step, which normalizes the acquired physiological signals and segments them according to a set duration to obtain several original signal segments; a Williams RGB compression step, which maps the original signals to an RGB image to obtain a Williams RGB energy map; a feature extraction step, which inputs the Williams RGB energy map into a neural network model for feature extraction; and a comparison and classification step, which compares the feature values ​​with RGB standard thresholds to determine the corresponding sleep stage. This sleep stage identification method avoids directly processing the complex frequency domain features of physiological signals, thus reducing computational complexity. Three physiological signals within a certain time period only need to be represented by a single pixel in the image, achieving physiological signal compression and dimensionality reduction, further reducing computational load. This invention also effectively utilizes medical knowledge graphs to provide interpretable evidence for the sleep stage identification decision-making process.

This invention discloses a method for extracting transformer vibration features based on multi-point collaborative sampling and time-frequency matrix reconstruction, comprising the following steps: S1. Establishing a finite element simulation model based on the transformer structure and acquiring original vibration signals from multiple locations on the surface of the tank; S2. Performing normalization preprocessing on the original vibration signals and dividing them into multiple data samples through sliding window sampling; S3. Multiplying each data sample by a window function, calculating the Fourier transform of each window, and constructing the short-time Fourier transform time-frequency matrix of the vibration signal by spectral splicing; S4. Based on the short-time Fourier transform time-frequency matrix, calculating the instantaneous frequency after signal compression, and mapping pseudo-frequency components within a set width to the instantaneous frequency according to the mapping relationship, thereby obtaining a high-resolution time-frequency matrix reconstructed by synchronous Fourier compression transform. This invention has the advantages of high feature extraction accuracy and high reliability.

A power spectrum estimation method for compressed sampling of a generalized stationary HDR signal is disclosed. This method is used for processing aero-engine blade tip vibration monitoring signals. The method involves determining the threshold of a self-recovering analog-to-digital converter and the delay scheme for multi-channel compressed sampling based on prior information about the signal amplitude and frequency; compressing the signal using a multi-channel dual-threshold cooperative sampling method; recovering the correct amplitude information from the acquired signal using the dual-threshold information; constructing an indicator sequence and a data sequence based on the sampling delay scheme; and performing Fourier transform, element-square operation, inverse Fourier transform, and element-product calculation sequentially on the indicator sequence and data sequence to obtain the power spectrum estimate of the signal.

This invention discloses a microprocessor-based electrophysiological signal acquisition and wireless transmission system and method, including the following steps: converting the acquired electrophysiological analog signal into an electrophysiological digital signal; compressing the electrophysiological digital signal using a dynamic reference value compression algorithm via a zero-copy DMA transmission architecture to obtain a compressed electrophysiological digital signal; encapsulating the compressed electrophysiological digital signal through protocol transparency to generate a layered data packet; and transmitting the data packet to a host computer via a dual-mode data transmission module, providing the host computer with a data packet containing the electrophysiological signal. This invention avoids crosstalk and coherence distortion caused by phase misalignment in multi-channel signal analysis, eliminates MCU core data transfer overhead, and achieves strictly synchronous sampling across multiple channels.

Embodiments of the present application relate to the field of digital signal processing, and disclose a radar digital signal compression and decompression method and circuit, an electrical device and a terminal. In the present application, a plurality of pulse sequences from a plurality of channels are obtained, a periodic binary modulation sequence corresponding to each channel is adopted, and the pulse sequences of the corresponding channels are digitally modulated and accumulated to obtain compressed radar digital signals. The period of the binary modulation sequence corresponding to each channel is a divisor of the total number of pulses in a frame. There are at least two binary modulation sequences satisfying the following constraint conditions: the periods of the binary modulation sequences corresponding to any two channels are different and are in a factor relationship, and are orthogonal within the least common multiple of each other's period, so that the storage overhead of the radar system is reduced without losing signal accuracy, reducing signal quality, or increasing additional cost.

The application discloses a method and system for detecting weak signals and harmonics based on compression-enhanced stochastic resonance, comprising a vacuum system, a trapped field, a laser system, a fluorescence collection system and an external signal; the vacuum system comprises a vacuum cavity, an ion pump and a suction pump, a calcium atom furnace and a surface electrode ion trap for trapping calcium ions are arranged in the vacuum cavity; the trapped field comprises a radio frequency trapped field and a direct current trapped field, the radio frequency trapped field is composed of a radio frequency signal source, a power amplifier and a spiral resonant cavity; the direct current trapped field comprises a direct current high-voltage power supply, a 6733 board card and an amplification chip; the fluorescence collection system comprises an imaging mirror, a CCD camera and a photomultiplier tube; the external signal comprises a driving signal, a compression signal and a signal to be detected. The application uses the compression signal to replace the external random noise, triggers the ion to have periodic phase change with the signal to be detected, changes the intensity of the compression signal, makes the signal to be detected and the bistable system reach the best matching, and maximizes the signal-to-noise ratio and the detection of harmonics.

Techniques described herein relate to systems and methods for parallel DNA molecules sequencing. A preprocessor can receive raw data frames from a sensor chip including 100,000 or more cells, where each raw data frame can include detection signals from the 100,000 or more cells at a given time during the formation of the 100,000 or more cells or during the DNA molecules sequencing using the 100,000 or more cells. The preprocessor can then extract relevant information for determining states of the cells from the raw data frames, generate one or more digested frames that includes the extracted information, and send the digested frames to a processor for processing, such as base determination. Because the number of digested frames sent to the processor is less than a number of the raw data frames and the digested frames include preprocessed data, the amount of data being transferred to the processor and the amount of data processing by the processor can be reduced.

This invention provides a condition monitoring method and system for a high-pressure fan-type shaftless external rotor motor, relating to the field of motor condition monitoring and fault diagnosis technology. Specific steps include: First, uniformly arranging four sensors on each of the upper and lower guide rails of the shaftless external rotor motor to construct a 360° circular monitoring array; second, acquiring eight channels of vibration data, and improving the signal-to-noise ratio through adaptive multi-scale filtering and wavelet envelope analysis; then, using a spatial vector decomposition and fusion algorithm to compress the eight-dimensional signal into a three-dimensional equivalent vector, and constructing a five-dimensional feature vector by combining speed normalization and temperature compensation; next, inputting the data into a lightweight Lite-CNN model for fault identification and severity quantification, and achieving fault location through confidence weighting; finally, triggering online incremental learning and updating the model using knowledge distillation. This invention has significant advantages in terms of recognition rate, positioning accuracy, and power consumption.

The present disclosure provides a data compression method, device, apparatus and storage medium, the method comprising: obtaining a target signal, removing the sign bits of the target signal to obtain a first signal comprising data bits; determining a quantization range corresponding to each segment based on the bit width of the data bits of the first signal and the number of segments of the normalization processing; each segment and its corresponding quantization range form a broken line segment; determining a target broken line segment corresponding to the first signal according to the amplitude of the first signal, and processing the first signal according to the target quantization range corresponding to the target broken line segment, so that the processed first signal is closer to the starting broken line segment than the first signal before processing; performing data bit truncation processing on the processed first signal to obtain a compressed signal; the bit width of the data bits of the compressed signal is smaller than the bit width of the data bits of the first signal. In this way, the signal compression quality can be improved and the compression process can be simplified.

This invention discloses a method for rapid transmission and distribution of video data between a public network and a secure intranet, belonging to the field of data communication technology. Specifically, it involves: identifying a video terminal deployed on the public network, used to acquire raw video data; deploying a video encoder, connecting its HDMI capture interface to the video terminal, and compressing and encoding the HDMI signal converted from the raw video data into a standard video stream; identifying a video platform deployed on the secure intranet, connecting the video platform to the standard video interface of the video encoder, and directly accessing the standard video stream encoded by the video encoder through a standard video access and transmission protocol; storing the standard video stream in a database on the video platform, allowing only authorized entities to retrieve it; and providing a standard API interface, allowing authorized third-party business platforms to obtain the standard video stream as needed by calling the standard API interface.

The application discloses a low-repetition-frequency pulse sequence super-resolution sampling and data compression method, and relates to the field of digital signal processing.The method comprises the following steps: inputting an external pulse signal P(t) and a sampling clock signal T(t) into D TDC sampling modules to perform sub-picosecond time-to-digital conversion and obtain a state sampling matrix S; comparing the sampling clock signal, performing D-phase oversampling on the state sampling matrix S output by the TDC sampling module within one clock cycle and latching, obtaining original sampling data stream P(ts) of the input signal through a TDC calculation unit; analyzing the original sampling data stream P(ts), calculating the absolute time of arrival TOA of the first pulse in the time segment in real time as a reference time point in the time segment, and performing signal compression on subsequent pulses by using a differential-entropy coding method; and storing the compressed code stream into a local storage unit and realizing data uploading through an external communication interface.The application realizes sub-picosecond super-resolution recording and hard real-time data compression of a low-repetition-frequency pulse sequence.

The application relates to a multi-channel neural signal compression circuit device, a control method and a storage device, and relates to the technical field of neural signal processing. The device comprises an analog-digital front-end group, a data packer and a data transmission baseband module. The analog-digital front-end group comprises N channel processing units arranged in parallel. Each channel processing unit is integrated with an analog conditioning circuit, an analog-digital converter and an adaptive differential compression module. The adaptive differential compression module is directly coupled to the digital output end of the corresponding analog-digital converter of the channel, and compression processing is completed in the local data path of the channel. By integrating the adaptive differential compression module in the channel processing unit, efficient compression is realized by utilizing the time domain correlation of neural signals. Meanwhile, the data transmission is optimized by adopting a three-state bus structure, the data transmission load and system power consumption are significantly reduced, and low-power wireless transmission of high-throughput neural signals is realized.

A compressor for compressing a control signal includes residual compression circuitry configured to sequentially receive a first control signal and a second control signal and perform compression based on a difference between the first control signal and the second control signal, coding mode determination circuitry configured to determine a coding mode based on a type of control signal, analog signal compression circuitry configured to perform compression based on indexing, and control signal compression circuitry configured to perform compression based on run-length encoding (RLE).

This invention relates to the field of vibration damping device control technology, and more particularly to a composite buffer vibration damping device, comprising a device body and a control center. The device body includes a damping base, a support plate, a buffer foam pad, and an adjustable damping component. The control center synchronously acquires process status information, vibration signals, compression displacement, and penetration strain data through a data acquisition module. A decoupling calculation module constructs a dynamic model using a built-in fractional-order dynamic decoupling algorithm and calculates the target damping force based on viscoelastic memory decay characteristics. A feedforward compensation module predicts transient loads based on process characteristics and generates a feedforward compensation force. An adjustment output module integrates two mechanical commands to generate a total damping command, dynamically changing the damping characteristics of the adjustable damping component. This invention uses adaptive adjustment to counteract dynamic hardening and operating condition impacts, enabling the support plate to maintain high-precision coplanar stability under conditions of variable center of gravity and high-frequency interference coupling.

The application discloses a dust removal equipment remote intelligent operation and maintenance early warning system based on an industrial Internet of Things, relates to the technical field of industrial Internet of Things operation and maintenance, and comprises the following steps: an edge gateway synchronously collects bag leak monitoring signals, ash removal trigger signals, compressed air main pipe pressure, dust remover pressure difference and temperature and humidity, identifies ash removal events, and aligns and slices ash removal signature windows to form ash removal event records and stability and effectiveness labels; ash removal signature features are extracted based on the event records, a template library is established according to chambers or valve groups and working condition clusters, and the template library is controlled and updated through a trusted update access control; the features are compared with the templates to obtain a deviation degree score, and an alarm type, a level and a suspected chamber are classified and output in combination with time continuity and spatial distribution patterns; when the alarm is uncertain, a diagnosis pulse sequence is triggered, and re-measurement is performed after a maintenance action, and an evidence package is generated. The application can inhibit false alarms caused by ash removal transients and wet interference, improve leakage positioning accuracy and remote closed-loop disposal efficiency.

The application discloses a power grid super-harmonic efficient and accurate detection method and device based on compressed sensing and LSTM reconstruction, and relates to the technical field of power system power quality monitoring and signal processing. The method comprises the following steps: constructing a power grid super-harmonic data set; preprocessing the power grid super-harmonic data set and dividing the power grid super-harmonic data set into a training set and a verification set according to a certain proportion; constructing a power grid super-harmonic sparse coefficient vector prediction model based on an LSTM network; training the model through the training set data; verifying the trained model through the verification set data; compressively sampling real-time signals of power grid voltage or current; predicting the predicted sparse coefficient at the current time; obtaining the optimal sparse coefficient through an optimization solver; restoring the original super-harmonic signal and extracting the frequency and amplitude characteristics. The application reduces the sampling rate and hardware cost, improves the reconstruction accuracy and noise immunity by using the time series prediction capability of the LSTM, and realizes efficient, accurate and real-time detection of the power grid super-harmonic.

The application discloses a lightning VLF electromagnetic wave signal compression method based on importance perception and belongs to the technical field of signal processing. The method comprises the following steps: firstly, acquiring an original lightning VLF electromagnetic wave time sequence signal and performing normalization processing; then, inputting the normalized signal into an importance prediction model, the model comprising a shared feature encoder, a time sequence-frequency domain double-channel attention module and a double-branch decoding structure, and outputting an importance score of each time slice; finally, according to the score, adopting an adaptive hierarchical compression strategy, performing non-uniform weighted sampling on key slices, uniform sampling on transition slices and sparse sampling on redundant slices, and obtaining a compressed signal. The application can adaptively distinguish lightning pulses from noises, accurately retains key waveform details such as rising edges, peak values and falling edges of the pulses under a high compression ratio, has small pulse peak value and arrival time error, has high waveform correlation coefficient, and is highly compatible with existing lightning monitoring and fault positioning processes.

A computer-implemented method is provided for compressing a signal. The method includes acquiring the signal; sampling a plurality of values from the signal; assigning to an event each value that exceeds an event threshold, and removing each value in response to equivalence within a tolerance to previous and subsequent adjacent values. Each value is associated with a time stamp and separated from an adjacent value by an interval gap.

The application discloses a power quality disturbance data detection method and device based on compressed sensing. The method comprises the following steps: acquiring an original sampling signal, obtaining an observation vector through a measurement matrix to realize signal compression; separating a fundamental component and a harmonic component of the original signal according to the fundamental wave filtering principle; reconstructing the original signal according to the proportion of the harmonic component, arranging the inner product of a sensing matrix and a harmonic component observation vector in descending order when the harmonic component is more than a set condition, calculating a slope curve, estimating the signal sparsity according to the pole distribution of the slope curve, taking the sparsity estimation value as an initial step of a SAMP algorithm, and iteratively calculating a residual ratio threshold and a growth curve function to obtain a sparse vector estimation value of the harmonic component; and performing power quality disturbance data detection.