8 results about "Power spectral analysis" patented technology

The application relates to the technical field of non-ideal surface generation of machined parts, and particularly discloses a construction method of an assembly joint surface considering wavelet and fractals, which comprises the following steps: S1, according to an ideal numerical model of the assembly joint surface; S2, comparing calculation methods of different fractal parameters; S3, aiming at the assembly joint surface of parts under different machining modes; S4, regarding the assembly joint surface as a structure formed by superposition of different scale contours; S5, introducing a power spectrum analysis method to analyze the surface contour curve characteristics of the assembly joint surface; S6, according to the isotropic or anisotropic properties of the assembly joint surface under different machining modes, introducing the statistical distribution characteristic parameters determined in step S3 into the representation of the assembly joint surface; and S7, associating the contour curve characteristic parameters extracted in step S4 with the fractal parameters determined in step S2. Through multi-scale decomposition of the assembly joint surface by wavelet transform, the specific information of the roughness contour, the waviness contour and the shape error contour can be effectively extracted.

The application discloses a kind of multi-camera-based animal vital sign monitoring method, medium, equipment, it is related to animal vital sign monitoring technical field, method includes: using DLC posture estimation network to train animal multi-view video, obtain key point information;According to the key point information of main visual angle, the centroid motion of animal is analyzed and compared with motion threshold, determine animal state, in the continuous image sequence of relative static state time period, according to key point information, obtain region of interest;Corner point is detected in region of interest, and corresponding motion signal is acquired by tracking corner point;Correlation analysis is carried out to motion signal, and sorting is carried out based on information gain, and vital sign signal is obtained by fusing motion signal higher than set threshold;Power spectrum is used to analyze vital sign signal, obtain the energy distribution of vital sign signal, and the value of respiratory rate and heart rate is calculated.The application can effectively reduce artificial intervention, and has the role of promoting to animal experiment method innovation and data analysis.

This invention discloses a remote, non-contact heart rate estimation method, system, and device based on sparse structure representation, belonging to the field of physiological sign research applications. It addresses the problem of inaccurate heart rate signal detection in existing methods, including: Step 1: Inputting a face video and segmenting the face into multiple sub-regions; Step 2: Constructing the average RGB pulse signal for each sub-region, performing motion compensation, and calculating the chromaticity signal S using linear combinations of different RGB channels, and calculating the signal-to-noise ratio; Step 3: Solving for the coefficient matrix using a structure dictionary composed of cosine bases of different frequencies and wavelet bases of different scales, and reconstructing the heart rate signal using the structure dictionary and coefficient matrix; Step 4: Averaging the reconstructed sub-region heart rate signals and performing power spectral analysis to calculate the heart rate HR. Finding the optimal sparse representation based on the dictionary, reconstructing the heart rate signal using the dictionary and sparse coding, and representing the most realistic heart rate signal with as few dictionary atoms as possible helps improve the accuracy of the algorithm.

The modulation spectrum adaptive feature purification method based on feature energy entropy reconstruction belongs to the field of underwater acoustic target recognition. The method is used for solving the problem that the existing modulation spectrum feature extraction method cannot solve the influence of harmonic interference on the final estimation result. The method comprises the following processes: in step one, the cavitation noise in the ship radiated noise is demodulated through a plurality of preset demodulation frequency bands, a plurality of demoded signals are obtained, and the optimal demodulation frequency band is selected from the demodulation frequency bands corresponding to the demoded signals by adopting the minimum entropy criterion; in step two, the demoded signal obtained under the optimal demodulation frequency band is decomposed through the VMD algorithm, and the signals of the intrinsic mode functions of all orders are obtained; in step three, the feature energy entropy of the signals of the intrinsic mode functions of all orders is calculated, the feature energy entropy is reconstructed by using the FEER algorithm, and the reconstructed signal is obtained; in step four, the power spectrum analysis is carried out on the reconstructed signal, and the purified modulation spectrum is obtained. The method is mainly used for purifying the modulation spectrum.

1. The name of the design product: the myoelectric power spectrum analysis graphical user interface of electronic equipment. 2. The use of the design product: for displaying interface content. 3. The design points of the design product: in the graphical user interface. 4. The picture or photo that best indicates the design points: front view. 5. The electronic equipment is of conventional design, and other views are omitted. 6. The use of the graphical user interface: for the myoelectric power spectrum analysis graphical user interface. The human-computer interaction mode: human-computer interaction can be realized through mouse dragging, sliding, placing, and clicking. The front view is the main interface of the myoelectric power spectrum analysis operation interface, interface change state figure 1 is the power spectrum analysis interface displayed after clicking the PSD option in the front view state, interface change state figure 2 is the power spectrum start analysis interface displayed after clicking the Run option in the interface change state figure 1 state, and interface change state figure 3 is the export analysis result interface displayed after clicking the Export option in the interface change state figure 2 state.

According to the heart rate interference self-adaptive suppression method and system, the brain blood oxygen signals and the heart rate signals are collected, the heart rate signals in the brain blood oxygen signals are deducted through the self-adaptive regression deduction method, the dynamic change of the heart rate is effectively tracked, accurate deduction of heart rate interference is achieved, and the accuracy of heart rate interference suppression is improved. Then the processed signals are subjected to power spectrum analysis so as to judge whether deduction processing is thorough or not, center jump interference of the brain blood oxygen signals can be effectively filtered out, meanwhile, other signal frequencies except heartbeat interference signals are reserved, the collected brain blood oxygen signals are more accurate, and through a dual judgment mechanism of power spectrum analysis and physiological feature verification, the accuracy of the brain blood oxygen signals is improved. It is ensured that heart rate interference is fully suppressed, the accuracy and reliability of output signals are higher, and scientific research and clinical application requirements are met.

This application discloses a method, apparatus, device, and storage medium for extracting axle loads in passenger vehicles, relating to the field of vehicle testing technology. The method includes: acquiring vibration acceleration signals from multiple measuring points on the steering knuckles of each wheel of the passenger vehicle during operation; performing multi-reference cross-power spectrum analysis and singular value decomposition on the vibration acceleration signals to obtain a reference spectral response matrix; acquiring excitation test data and calculating a frequency response relationship based on the excitation test data, wherein the excitation test data is obtained by using a rigid mass block instead of tires for excitation testing; and calculating the axle load based on the reference spectral response matrix and the frequency response relationship. This application improves the accuracy of axle load extraction.

The application discloses a dynamic laser Doppler spectrum correction method, and the traditional laser Doppler spectrum correction method only suppresses fixed position noise of a spectrum, the position of Doppler spectrum noise corresponding to different laser velocimeter systems is not necessarily the same, therefore, the method is not universal, the suppression effect of the method is poor, and the spectrum noise is still unstable, thereby causing interference to spectrum resolution of the velocimeter system, and therefore, the application provides a laser Doppler spectrum correction method based on power spectrum analysis.The application performs signal suppression based on power spectrum analysis, has good universality, the spectrum noise suppression effect is obvious, the spectrum noise is stable, and the application lays a foundation for accurately extracting a Doppler signal in subsequent spectrum resolution.