12 results about "Signal Detection Analyses" patented technology

The invention belongs to the field of food quality evaluation, and provides a delicate flavor synergistic effect evaluation method based on an electroencephalogram monitoring technology. Psychological or physiological factors such as subjective judgment, forced selection or scoring, individual umami cognition and umami sensitivity difference of sensory officers may affect the accuracy of sensory experiment results; the invention discloses methods such as umami sample selection and strength evaluation, electroencephalogram signal acquisition experiment normal form, quantitative evaluation and statistical analysis, feature extraction and response difference analysis, and the like, and the response mechanism of typical umami compounds in the human brain is explored by taking the response of people to umami signals as a research object and taking electroencephalogram signal detection analysis as a main method. A new theoretical basis is provided for quantitative evaluation based on the human palatable taste intensity, and the method is worthy of wide popularization.

The invention discloses a signal detection and analysis method, a server and a domestic terrestrial broadcast / digital television signal detection and analysis platform, and the method comprises the steps: constructing a data exchange bus based on a five-stage pipeline; acquiring detection data and streaming media data; distributing the data to corresponding pipelines; constructing a multi-stage field programmable gate array cascade structure; obtaining a processing load parameter; when the processing load parameter is smaller than a preset load threshold value, the processor is controlled to send corresponding data to all levels of pipelines according to a preset time sequence; sequentially collecting all levels of pipeline data; performing parallel processing on the to-be-processed data of the fourth-stage pipeline and the fifth-stage pipeline; when it is detected that any processing load parameter exceeds a preset load threshold value, migrating part of the to-be-processed data to other programmable gate arrays; and sending the processed data to a processor, and generating a signal detection analysis report comprising a signal quality analysis result and an equipment state analysis result. According to the invention, the real-time performance and accuracy of signal detection and analysis are improved.

The invention discloses a complex signal detection analysis method and system based on a hybrid convolution window, and the method comprises the steps: carrying out the discrete sampling of a signal containing multiple complex harmonics in a power grid, and obtaining an original discrete sequence signal; processing the original discrete sequence signal by adding a mixed window to obtain a windowed discrete sequence signal; performing discrete Fourier transform on the windowed discrete sequence signal to obtain a discrete harmonic signal frequency spectrum value; obtaining a plurality of spectral lines which are at a preset distance from each harmonic frequency point in the discrete harmonic signal frequency spectrum value; according to a plurality of spectral lines having a preset distance from each harmonic frequency point, establishing a relationship between the spectral lines and a frequency spectrum value; obtaining an offset between the spectral line and a theoretical value through the relationship between the spectral line and the spectral value; and modifying the harmonic signal by using the offset to obtain a modified harmonic signal. And the civil harmonic detection precision is effectively improved.

The invention discloses a method for separating hidden weak signals from single-carrier background signals based on constellation reconstruction, and belongs to the technical field of wireless communication signal detection. The method solves the problem that a non-partner is difficult to reconnoiter a hidden transmission weak power signal by using a traditional signal detection method. According to the method, a constellation diagram of a single-carrier conventional modulation signal playing a shielding role is reconstructed in a clustering mode, complete reduction of a shielding signal waveform is guaranteed, interference of a conventional communication signal with large power on a hidden weak signal is effectively separated and weakened, and after the preprocessing step, the interference of the conventional communication signal with large power on the hidden weak signal is reduced. And multi-stage signal detection analysis is carried out on the residual signals, so that the recognition capability of hidden weak signals in a complex signal environment is improved, and the detection capability of hidden weak power signals in a shielded scene is improved. The method can be applied to separation of hidden weak signals in single-carrier background signals.

The embodiment of the present invention discloses a railway high-speed bearing operation monitoring system, which includes: multiple data acquisition units for periodically acquiring bearing operation status data; a first data communication unit for periodically sending first communication data to a local vehicle-mounted terminal; the local vehicle-mounted terminal configures an independent simulation operation environment for each received first communication data, and performs signal detection and analysis processing on the bearing operation status data based on a given operation strategy to determine whether a fault occurs; synchronously communicates with a remote analysis center; the remote analysis center can continuously perform fault prediction analysis on the first communication data from the same identity identification information, and issue the fault prediction results after forming them. The present invention can perform simulation in batches and effectively improve the monitoring efficiency; and the preliminary fault analysis is placed in the local simulation operation, and the complex prediction analysis process is predicted and analyzed through the remote center, further reducing the performance requirements for the local terminal.

The invention discloses a semiconductor product detection, transmission and positioning method and device, and the method comprises the steps: S1, feeding: feeding a semiconductor product from an inlet of a transmission mechanism; s2, transmission positioning is carried out, and when the moving material tray passes through a speed reduction sensor, the speed reduction sensor detects a material tray signal; s3, detection analysis: detecting the semiconductor product in a double-sided detection mode; s4, positioning is relieved, and the downward pressure of the pressing plate on the material disc is relieved; and S5, discharging, through the transmission mechanism, a belt line is controlled to run in a decelerating mode when a speed reduction sensor senses a material box, the productivity is improved, meanwhile, the transmission positioning precision is guaranteed, a side edge positioning mechanism is combined to conduct transmission positioning on a material disc, the transmission positioning precision is further improved, and the production efficiency is improved. The reset sensor is additionally arranged in the positioning transmission method, and the next process can be started under the condition that the current process is not finished, so that the time of the whole process flow is saved.

The invention relates to the technical field of signal detection and analysis, and discloses a method for enhancing the generalization of an atrial fibrillation detection algorithm in combination with a GPT model, and the method comprises the following steps: S1, feature extraction: carrying out the multi-scale frequency domain decomposition of an input ECG signal through wavelet transform; a multi-head attention mechanism fused with Gaussian distribution is introduced, subspace feature expression is constructed, and multi-scale time-frequency features are obtained; s2, generalization enhancement is carried out, an atrial fibrillation model is constructed, dynamic sequence modeling and feature enhancement are carried out through a transfer learning mode and multi-scale time-frequency features, capturing of long-range dependence and tiny anomalies is achieved, fine tuning training is carried out in combination with atrial fibrillation detection task features, and a trained atrial fibrillation model is obtained; and S3, outputting a result, and outputting an atrial fibrillation detection result through the trained atrial fibrillation model. According to the electrocardiosignal atrial fibrillation detection strategy combining the large language model pre-training technology and the time sequence feature modeling method, the generalization ability and the detection precision of the model in diversified real scenes are improved.

The present invention discloses a multi-channel BCG signal detection and analysis method, comprising the following steps: (1) collecting at least four juxtaposed BCG signals; (2) selecting one of the optimal signal data for processing as the basis for subsequent heart rate detection. The present invention also provides corresponding heart rate detection methods and devices respectively. Among them, the heart rate detection method comprises the following steps: (a) performing EMD decomposition on the optimal signal to obtain a plurality of intrinsic mode components; (b) obtaining the spectrum of each independent component; (c) calculating the signal power ratio of 1-10 Hz based on the spectrum; (d) taking the signal greater than the signal power ratio threshold as the starting point, and simultaneously taking the amplitude value corresponding to the starting point as the threshold; (e) collecting the starting point positions of S1 and S2; (f) determining S1; (g) obtaining heart rate data based on S1. The present invention has well improved and enhanced the acquisition and calculation accuracy of heart sound and heart rate, providing an effective means and guarantee for non-contact and long-term heart sound signal monitoring.

The invention relates to a brain signal analysis method based on cross-frequency information fusion. The method is technically characterized by comprising the steps that a measurement normal form based on a magnetoencephalogram is established, and brain magnetic signals are collected; preprocessing the brain magnetic signals; calculating a weighted phase lag index between different channel signals in the preprocessed data, and constructing intra-layer connection of the cross-frequency multi-layer network; phase-amplitude coupling between channel signals under different frequency bands is calculated by adopting a modulation index measurement method, and interlayer connection of a frequency-crossing multi-layer network is constructed; and constructing a cross-frequency multi-layer brain function network according to the intra-layer connection and the inter-layer connection, and performing multi-dimensional feature extraction on the cross-frequency multi-layer brain function network. According to the method, the same-frequency and different-frequency connection characteristics are simultaneously integrated in the cross-frequency domain, so that the hierarchical organization structure of the brain function network can be more comprehensively described, the important topological characteristics of the multi-layer network can be stably extracted, the utilization efficiency of the cross-frequency coupling information in the brain magnetic signal is effectively improved, and the method can be widely applied to brain signal detection and analysis.

The invention discloses a portable precise hearing detection system based on adaptive sound field compensation, and relates to the field of hearing detection, and the system comprises an environment monitoring module which is used for obtaining an environment noise signal; the hearing monitoring module is used for acquiring an audio test signal and user feedback information; the data transmission module is used for setting an environment transmission channel protocol and a test transmission channel protocol corresponding to the data processing end for the environment end and the test detection end respectively, and transmitting corresponding data information; the environment compensation module is used for performing adaptive sound field compensation according to the environment noise signal to obtain an initial audio test signal; the test compensation module is used for performing adaptive compensation according to a comparison result corresponding to the initial audio test signal and the audio test signal to obtain a comprehensive audio test signal; the detection analysis module is used for performing analysis processing according to the user feedback information and the comprehensive audio test signal to obtain corresponding hearing detection data; the accuracy of the hearing detection process is improved.

The application discloses a sensor signal detection analysis platform and application thereof in a rotating machine. The sensor signal detection analysis platform comprises a time domain analysis acquisition processing module, a frequency domain analysis acquisition processing module and a data analysis display module. The time domain analysis acquisition processing module is used for acquisition and time domain algorithm processing of a sensor signal; the frequency domain analysis acquisition processing module is used for acquisition and frequency domain algorithm processing of the sensor signal; and the data analysis display module is used for data analysis, visual processing and display of acquired original data and time domain / frequency domain processed data. In the above sensor signal detection analysis platform, synchronous acquisition of various sensor type signals of the rotating machine is realized, multi-channel synchronous time / frequency domain data processing is realized, and multi-data chart contrast display is realized.

The utility model relates to the field of embedded application technology discloses a kind of multi-channel logic signal detection analyzer system, comprising: multi-channel logic signal detection analyzer, multi-channel logic signal detection analysis work station and interface module;Multi-channel logic signal detection analyzer, interface module and multi-channel logic signal detection analysis work station are connected by integrated bus, and multi-channel logic signal detection analyzer is also connected to be detected equipment;Among them, the logic signal that the multi-channel logic signal detection analyzer is detected to equipment output is compressed to data, and the logic signal after processing is detected to obtain detection result, and detection result is sent to multi-channel logic signal detection analysis work station by integrated bus;Multi-channel logic signal detection analysis work station is used to display detection result. To solve the problem that channel expansibility is insufficient, and data storage and processing capacity are insufficient, and continuous long time signal analysis cannot be carried out.