30 results about "Signal processing algorithms" patented technology

Disclosed is a method for anomaly detection, health index classification, and remaining useful life (RUL) prediction of circuit breakers, including the steps of: capturing and collecting real-time trip coil waveform signals from each of circuit breakers; transmitting the collected trip coil waveform signals to a circuit breaker health monitoring system; processing the collected signals data; analyzing the processed data using artificial intelligence and signal processing algorithms for anomaly detection, health index classification, and remaining useful life (RUL) prediction; storing data; performing trend analysis on data; and predicting remaining useful life (RUL).

This invention relates to a method for testing twin defects in pre-oxidized wafers using a particle testing machine, belonging to the field of semiconductor wafer defect detection technology. The method includes the following steps: Step 1: Thermal oxidation preparation; the grown oxide film is obtained through wet oxidation in an oxidation furnace, and the wafer is cleaned using a final cleaning machine. Step 2: Particle testing method optimization and film establishment. Step 3: Result comparison and verification; by establishing an Oxide Film model, the signal processing algorithm of the particle testing machine can distinguish between particle signals and twin signals, thereby achieving synchronous capture. Step 4: By optimizing the particle testing machine method, twin defect detection of the pre-oxidized wafer is successfully completed simultaneously during particle testing. By optimizing the particle testing machine method, synchronous detection of particle testing and twin defects is achieved, thereby improving detection efficiency, shortening the process, and maintaining the integrity of the sample.

This invention relates to the field of new energy power generation and energy storage, and in particular to a method and system for limiting power distribution, comprising: setting a total power distribution capacity limit value, wherein the total power distribution capacity limit value is an unsigned value representing the maximum absolute value of power allowed at the grid connection point; calculating in real time the total active power at the connection point between the new energy grid-connected equipment and the power distribution facilities; dynamically calculating the power output limit value of the new energy grid-connected equipment based on the total power distribution capacity limit value and the total active power through a closed-loop control algorithm, wherein the power output limit value includes a positive power limit value and a negative power limit value; and controlling the output power of the new energy grid-connected equipment using the positive power limit value and the negative power limit value as boundaries. This invention, through detailed parameter settings, signal processing, algorithm calculation, and hardware control procedures, fully realizes bidirectional power distribution limitation, effectively protecting the safety of user-side power distribution facilities.

This invention discloses a finite element method and apparatus for a refined distributed projectile-guided system. The method constructs simulation models of the projectile body and target plate. The projectile model consists of three propellant charges, two propellant separators positioned between adjacent charges, a fuze holder mounted at the bottom of the projectile, and an outer shell. A sensor is installed in each of the two propellant separators, and a sensor is installed in each base fuze within the fuze holder. Finite element simulation of the penetration process is performed, and acceleration time history curves from sensors located at the projectile tip, mid-projectile, and base are collected. The signals from the three sensors are cross-correlated and filtered to obtain acceleration time history curves decoupled from stress wave aliasing. This invention can reproduce the actual projectile-guided system structure, supports distributed sensor arrangement, and, with the aid of signal processing algorithms, can solve signal aliasing and noise interference problems, achieving high-precision overload signal acquisition.

This invention relates to a method, unit, and apparatus for anomaly simulation in a large-scale signal processing algorithm business chain, comprising the following steps: Step 1: Based on the testing requirements of the signal processing business chain, identify the signal processing algorithm software that needs to be embedded with the anomaly simulation unit and the business chain links that need to run the anomaly simulation unit independently; Step 2: Configure the anomaly simulation unit, enable the corresponding sub-units, and initialize the behavior mode, utilization rate, and quantity parameters of each sub-unit. This invention supports the simulation of anomalies in various hardware resources such as CPU, GPU, memory, video memory, and network, and can quantitatively assess the propagation impact of anomalies in the business chain.

This invention discloses an algorithm for removing high-power noise interference based on vortex waves, belonging to the field of signal processing technology. In this invention, the transmitted signal is a vortex wave signal. At the receiving end, an antenna array (number of array elements N≥2) receives the signal containing high-power noise interference. The received mixed signal is then subjected to vortex wave-based noise reduction processing. The vortex wave noise reduction principle is as follows: The average amplitude or the average of the maximum and minimum amplitude values ​​and the average phase of the electric field of N echo signals are taken. Then, the average amplitude and phase values ​​are combined to form a noise reduction electric field. Alternatively, one echo signal from the N echo signals can be arbitrarily selected, and the noise reduction electric field is subtracted from that echo signal. Compared with existing plane wave-based signal processing algorithms, this invention can extract vortex wave signals under low signal-to-noise ratio conditions, which is beneficial for improving the anti-interference capability in the field of signal processing and has significant practical application value.

This invention discloses a simulation and evaluation system for array signal processing in underwater sonar systems, belonging to the field of underwater sonar technology. The system includes: an underwater acoustic channel simulation module, used to generate an underwater channel model including ray bending and multipath effects and the channel response of each array element based on input marine environmental parameters using a ray tracing algorithm; a signal synthesis module, used to synthesize simulated multi-channel received signals of the array based on array parameters, target parameters, and channel responses; an algorithm processing module, integrating multiple underwater acoustic signal processing algorithms to process the received signals and output beamforming or spatial spectrum estimation results; and a performance evaluation module, which visualizes the processing results and calculates multi-dimensional performance indicators. This invention significantly improves the realism of the simulation, the completeness of the test scenario, and the guiding nature of the evaluation conclusions through high-fidelity physical modeling and closed-loop evaluation, effectively supporting sonar system design, algorithm verification, and performance prediction.

This invention discloses a respiratory rate detection method and device based on airflow sensing and Kalman filtering. The method includes the following steps: Step S1, a flexible trachea is installed at the waist of the human body, and an airflow velocity sensor is installed at one end of the flexible trachea. The airflow velocity sensor collects the airflow velocity signal inside the flexible trachea in real time, and the airflow velocity signal is preprocessed to obtain gas flow rate change data; Step S2, an abdominal volume change model is established based on the gas flow rate change data, and the abdominal volume change is estimated by the relationship between gas flow rate and abdominal deformation to obtain the deformation curve of the human abdomen over time. This invention provides a respiratory rate detection method and device based on airflow sensing and Kalman filtering, which converts the human abdominal respiratory movement into airflow changes and combines signal processing algorithms to obtain a stable respiratory waveform, thereby achieving accurate detection of human respiratory rate.

A novel LPWAN system and method of operating such a system is disclosed. The network deploys a plurality of endpoints communicating with at least one radio. Each radio in the system communicates, in turn, with a single basestation. The single basestation enables simplified network management (e.g. —endpoint admission, etc.) and basestation maintenance (e.g. —software updates, etc.) and reduces network deployment costs, as the single basestation device serves multiple radios over multiple coverage areas. The single basestation can be a software network core executed on a service device / server, such as a cloud SaaS service, allowing the computational capacity of the basestation to be scaled, as necessary, to service the network. The single basestation can also execute network cores for two or more network standards By having multiple radios provide their received signals to the single basestation, signal processing algorithms which can process multiple received versions of a signal to enhance the signal's effective SNR can also be employed.

This invention relates to the fields of medical device technology and signal processing algorithm technology. Specifically, it relates to an in vitro cardiac contractility dynamic enhancement system and method based on R-wave peak dual-modal sensing. The problem addressed by this invention is the technical issues of poor safety, high oxygen consumption, insufficient precision, and lack of automated closed-loop control in isolated cardiac mechanical perfusion methods. To solve these problems, this invention provides an in vitro cardiac contractility dynamic enhancement method based on R-wave peak dual-modal sensing, comprising: obtaining an initial threshold and an initial R-wave template library based on real-time cardiac physiological signals within an initial target time period; obtaining the true R-wave peak based on waveform verification of candidate R-wave peaks within the target time period and the initial threshold; calculating the stimulation delay based on species-preset parameters and real-time cardiac physiological signals; and selecting the stimulation mode and adjusting the energy parameters based on changes in the real-time cardiac physiological signals.

This application provides a method and system for detecting arm shoot-through faults in a three-level converter. By directly monitoring core operating data closely related to arm shoot-through faults (current change rate, temperature change rate, and secondary voltage), it eliminates the need for complex signal processing algorithms. The detection logic is simple, enabling rapid capture of fault characteristics and judgment, thus allowing time for the timely activation of subsequent fault protection measures. This effectively reduces component damage and economic losses caused by fault escalation. Furthermore, it allows for selection of single-dimensional or combined detection based on the actual operating scenario. Multi-dimensional detection data are all directly related to the core characteristics of arm shoot-through faults, comprehensively capturing fault signals and effectively avoiding misjudgments and omissions caused by electromagnetic interference and other factors in single-dimensional detection. This significantly improves the accuracy and reliability of fault detection.

The present application relates to the technical field of automation testing, in particular to a kind of special power dynamic response characteristic automatic testing method and system, comprising: obtaining target test point containing multiple working condition parameters, the target test point is any test point constructed by different working condition parameters, and the test result of target test point is obtained using digital signal processing algorithm;Using Gaussian process regression model, the predicted mean and predicted uncertainty of any target test point are obtained based on the target test point and its test result;The fluctuation degree and abnormal degree of target test point are calculated, and the global worst test point is obtained using improved bayesian optimization algorithm.The present application solves the problems of existing bayesian optimization algorithm in test efficiency, worst condition coverage ability and stability.

The application discloses an external wall external thermal insulation layer defect detection signal processing device, and relates to computer and data processing technology, which comprises a sampling and preprocessing board, wherein FPGA is used as a main controller, the FPGA controls a DDS chip to generate baseband waveform output through SPI and I / O_UPDATA signal lines, the FPGA controls a receiving and transmitting module to generate transmitting and receiving radio frequency signals through a parallel bus interface, the FPGA controls communication with an upper computer, the FPGA controls parameter configuration of an ADC chip through SPI, controls an ADC circuit to collect intermediate frequency signals input by the receiving module, and the FPGA is also used for realizing digital down-conversion and other signal processing functions; and the upper computer realizes phase correlation accumulation, direct current bias removal, band pass filtering and other signal processing functions. The application adopts FPGA to realize logic interface control functions and inverse Fourier transform algorithm, ensures that the device is small in size and low in power consumption, realizes part of signal processing algorithms on a general upper computer, and greatly reduces programming difficulty and device cost.

The application discloses a new energy track locomotive brake air pressure precise control device, which comprises a main control module used as a core control unit of the whole device, responsible for signal processing, algorithm operation, instruction output and communication interaction; a pressure collection module used for collecting air pressure data of a brake pipeline in real time and uploading the data to the main control module through an RS485 bus; a pressure regulating execution module used for receiving control signals of the main control module and realizing continuous and precise regulation of brake air pressure; an air path switching module used for precisely switching three states of air charging, air exhausting and pressure maintaining under the driving of the main control module; an execution terminal used for completing locomotive brake action; and a communication module used for realizing instruction interaction and state feedback of the main control module and a new energy track locomotive whole vehicle controller. The application is suitable for brake systems of new energy traction locomotives, industrial and mining track locomotives and other track transportation equipment.

The application discloses a millimeter wave vital sign phase-amplitude decoupling method and system, and the method comprises the following steps: generating two local oscillator signals with the same frequency and orthogonal phase; mixing the received millimeter wave radio frequency echo signal with the two local oscillator signals and performing low-pass filtering processing to obtain two baseband analog signals; regarding the two baseband analog signals as the real part and the imaginary part of a complex signal, and combining the two baseband analog signals into a complex baseband signal; and digitizing the complex baseband signal and extracting phase information to calculate vital sign parameters. The application solves the problem that the amplitude fluctuation caused by vital sign micro-motion phase and environment multipath in the existing millimeter wave vital sign monitoring technology is deeply mixed and difficult to separate at the receiving end, and the signal processing algorithm at the back end is complex, and the performance sharply decreases under low signal-to-noise ratio.

The application relates to the technical field of medical health, in particular to an epilepsy auxiliary evaluation method and device based on heart rate variability, equipment and a medium. The method comprises the following steps: acquiring at least two target physiological states in a current acquisition combination, including a resting state and one or two stimulation states; collecting electrocardio signals of a subject based on the target physiological states; performing heart rate variability analysis on each group of electrocardio signals based on a preset signal processing algorithm, obtaining a corresponding resting state HRV feature set and at least one stimulation state HRV feature set, and the HRV feature set comprises multiple feature items; determining a group of target feature items suitable for the current acquisition combination according to independent discrimination efficiency, correlation discrimination efficiency and / or global discrimination efficiency of each feature item on epilepsy; and generating a screening report for assisting in epilepsy risk evaluation based on the target feature items. While ensuring evaluation accuracy, operation efficiency is improved.

A method and system for abnormality detection, health index classification, and remaining useful life prediction of circuit breakers includes the steps of capturing and collecting real-time trip coil waveform signals from each circuit breaker; transmitting the collected trip coil waveform signals to a circuit breaker health monitoring system; processing the collected signal data; analyzing the processed data using artificial intelligence and signal processing algorithms for abnormality detection, health index classification, and remaining useful life (RUL) prediction; and storing the data; performing trend analysis on the data; and predicting the remaining useful life (RUL).

An audio processing system may include at least one memory configured to maintain a plurality of audio signal processing algorithms and audio components, and a server having a processor. The processor may be configured to present an interface displaying at least a portion of the signal processing algorithms and audio components, receive user selection of at least one of the audio components, present the at least one selected audio component via the interface, receive user selection of at least one of signal processing algorithms to apply to the at least one selected audio component, apply the at least one selected algorithm to the at least one selected audio component, and provide a measurement of the at least one selected algorithm and the at least one selected audio component via the interface.

The application provides an inner ear voice enhancement method and system based on a feedback microphone in an ANC earphone, and relates to the field of mobile voice communication, and the method comprises the following steps: using a feedback microphone in an active noise reduction ANC earphone as an uplink voice communication pickup device to pick up a voice signal conducted to air vibration in an ear canal via a human body; using a human body tissue to filter external high-frequency noise, using air in the ear canal as a medium, and using an in-ear air conduction microphone to pick up a low-frequency voice signal; performing frequency band expansion on the low-frequency voice signal picked up by the in-ear air conduction microphone based on an LDNN, and using acoustic correlation of low-frequency information to non-linearly infer and restore missing high-frequency spectral components. The application realizes strong anti-noise communication effect comparable to special bone conduction equipment by signal processing algorithm to excavate the potential of existing hardware without changing the existing TWS earphone bill of materials, increasing cost, and occupying additional space.

The application provides a signal classification method for sub-surface damage mechanism of hard and brittle materials based on acoustic emission technology. Firstly, the original acoustic emission signals and surface topography of the hard and brittle materials are obtained through grinding tests at multiple grinding speeds. Then, the wavelet packet signal processing algorithm and the short-time Fourier transform are used to pre-process the acoustic emission signals and extract time-frequency domain features. Finally, the micro-crack signals, radial crack signals and transverse crack signals are distinguished from the characteristic space by combining the damage characteristics of the hard and brittle materials with the acoustic emission characteristic parameters, and the characteristic frequency band range corresponding to each crack damage mode is obtained. A signal classification model for the sub-surface damage mechanism of the hard and brittle materials is constructed, which provides a theoretical basis for realizing the sub-surface damage monitoring of the hard and brittle materials under complex working conditions. The method can quickly identify the damage mechanism of the hard and brittle materials, realize the online evaluation of the subsequent sub-surface damage of the hard and brittle materials, and solve the technical problem of non-destructive and accurate monitoring in the grinding process.

This invention provides a method, device, and hearing aid for detecting and analyzing static acoustic feedback in behind-the-ear (BTE) hearing aids, belonging to the field of hearing aid technology. The method combines silencing testing fixtures and automated testing methods, using microphone arrays in each chamber to capture the sound signals emitted by various parts of the hearing aid during the testing process. Signal processing algorithms are then used to accurately identify the characteristic parameters of the acoustic feedback signal, ensuring the accuracy of the test results and providing a scientific basis for optimizing and adjusting the hearing aid. In particular, the method allows for quantitative analysis of the various factors constituting the acoustic feedback loop, helping to accurately locate and prevent static acoustic feedback, thereby improving user experience and hearing aid performance.

The application discloses a sleep state recording device based on a millimeter wave radar, which comprises a millimeter wave radar module, a signal conditioning circuit, a microprocessor and an output module. The millimeter wave radar module is used for emitting millimeter wave signals to a human chest cavity area and receiving reflected echo signals. The signal conditioning circuit is connected with the millimeter wave radar module and is used for amplifying, filtering and analog-digital conversion processing of the echo signals. The microprocessor is connected with the signal conditioning circuit and is internally provided with a signal processing algorithm. The signal processing algorithm comprises a respiratory signal extraction module, a heart rate signal extraction module and a motion compensation module. The respiratory signal extraction module is used for extracting a respiratory signal caused by chest cavity fluctuation from the echo signals through low-frequency filtering. The heart rate signal extraction module is used for extracting a micro-motion signal caused by heartbeat from the echo signals through high-frequency filtering and phase analysis. The motion compensation module is used for identifying and eliminating motion interference introduced by body displacement and trembling. The output module is used for outputting the extracted heart rate and respiratory data to a terminal device.

The application relates to the field of radio ranging technology and discloses an intelligent alarm method and system based on millimeter wave radar ranging. The method comprises the following steps: scanning a safety area around a medical device by using a frequency-modulated continuous wave millimeter wave radar to obtain reflection signal data of a layered detection area; performing coherent superposition processing on the reflection signal data by using a medical safety ranging signal processing algorithm to obtain a device safety frequency domain signal; performing distance calculation on the frequency domain signal by using a medical device ranging frequency estimation algorithm to obtain distance measurement results and approaching speed data between a person and the device; performing threat prediction on the distance measurement results according to a medical safety trajectory tracking algorithm to obtain a person motion trajectory and an alarm triggering condition; and performing intelligent judgment on the person motion trajectory and a safety threshold to obtain a hierarchical alarm output signal. The application improves the accuracy of person approaching detection and the intelligent level of alarm response in a medical environment.

The present application relates to wood processing and quality detection technical field, disclose a kind of printing wood crack detection method based on acoustic emission and digital image correlation method, comprising the following steps: step 1: detection preparation, and the detection equipment is debugged, and printing wood sample is pretreated;Step 2: acoustic emission signal acquisition, using acoustic emission signal acquisition system to collect the acoustic emission signal generated in the detection process of printing wood;Step 3: acoustic emission signal processing, using signal processing algorithm to process the acoustic emission signal collected, extract and crack related characteristic parameters;Step 4: digital image acquisition.By acoustic emission signal acquisition processing, the characteristic parameters generated by the crack in wood are obtained, and the suspected crack area on the surface of wood is identified with the aid of digital image correlation algorithm, and then crack determination is realized by multi-modal data fusion.Compared with single detection method, the limitation that single method can only detect surface or internal crack is effectively made up.

This invention discloses a high-speed motor speed detection method based on MEMS microcoils, relating to the field of high-speed motor speed detection. The method includes: non-contactly placing at least one MEMS microcoil sensor at a key electromagnetic field coupling position on the high-speed motor body or drive circuit; the MEMS microcoil sensor outputting a raw induced voltage signal; conditioning the raw induced voltage signal; using an analog-to-digital converter to perform high-speed synchronous sampling of the conditioned signal to obtain a digital signal sequence; extracting the speed characteristic frequency; calculating the real-time motor speed based on the speed characteristic frequency and preset motor parameters through a preset mapping relationship, and outputting the calculation result. This invention employs a miniaturized coil sensor based on MEMS technology, combined with intelligent signal processing algorithms, to achieve high-precision, high-response speed measurement in ultra-high-speed scenarios.