9results about How to "Reduce boundary effects" patented technology

This utility model relates to the field of civil engineering technology, specifically a pile foundation shaking table test device. It includes a shaking table body, a container on top of which holds soil and a pile foundation model. The container includes a coaxially arranged rigid inner frame and a rigid outer frame. A flexible sidewall structure is provided between the rigid inner frame and the rigid outer frame. The flexible sidewall structure consists of circumferentially spliced ​​flexible plates and multiple sets of micro-springs connecting the inner surface of the flexible plates to the outer surface of the rigid inner frame. The top and bottom of the flexible plates are connected to the rigid inner and outer frames via sliding guide components to allow radial displacement of the flexible plates in the horizontal plane. This pile foundation shaking table test device, by improving the boundary structure, effectively reduces the soil boundary effect, more realistically simulates the interaction between the pile and soil system under seismic loading, and improves the accuracy of the test.

This invention discloses a baseline removal method for multi-channel magnetocardiogram (MCC) signals based on wavelet low-frequency reconstruction and morphological secondary smoothing. The invention includes: acquiring multi-channel MCC signal data; performing power frequency notch filtering on each channel to suppress the power frequency fundamental frequency and at least one harmonic component; performing configurable IIR low-pass filtering on the notched signal; setting a discrete wavelet transform extension mode and performing discrete wavelet decomposition on the filtered signal; selectively retaining decomposition coefficients based on the retention layer set and setting the remaining coefficients to zero, then performing inverse wavelet reconstruction to obtain an initial baseline estimate; performing morphological secondary smoothing on the median-smoothed baseline signal to obtain a corrected baseline signal; subtracting the corrected baseline signal from the filtered signal to obtain the baseline-corrected channel signals; and assembling and outputting a multi-channel baseline-corrected signal matrix. This invention can improve the stability and cross-channel consistency of baseline estimation for multi-channel MCC signals, reduce the risk of over-correction and under-correction, and is applicable to multi-channel batch processing scenarios.

This utility model relates to a microscopic observation device for soil particles in shaking table tests, belonging to the technical field of civil engineering experimental equipment. It includes a vibrating base that supports the entire device and provides controlled vibration power; a fully transparent model box is mounted on the vibrating base to hold the soil particle sample to be observed, and the bottom layer of the fully transparent model box has symmetrically arranged wave-absorbing sponge layers on its left and right sides; a miniature camera assembly is mounted on the vibrating base, vibrating synchronously with the fully transparent model box; the miniature camera assembly includes a camera with high-speed continuous shooting capability, and the frame rate of the miniature camera assembly is not less than 300fps; a horizontal electric guide rail is mounted on the vibrating base; and a vertical electric lifting column is mounted on the horizontal electric guide rail. This utility model effectively eliminates the relative displacement problem caused by the asynchronous movement of the camera equipment and the model box in shaking table tests.

The present invention relates to a differential pair noise suppression structure. A circuit board includes at least one substrate having opposite first and second surfaces. A pair of plated vias are disposed along a z-axis. The first surface of the substrate is provided with a first metal line, a second metal line, a first plated via opening, and a second plated via opening to form a differential pair circuit structure. A metal ground is provided on the second surface of the substrate, the metal ground having a blank area. From a projection perspective, the metal ground area encompasses both signal lines to eliminate reflection noise caused by a boundary between the blank area and the metal ground so that the differential pair signal lines have a uniform characteristic impedance.

The invention discloses an electric energy quality transaction monitoring method and system based on window function optimization multi-dimensional characteristics, and the method comprises the steps: segmenting obtained historical electric energy quality signal data, carrying out the weighting processing through employing a Bartlett triangular window function, calculating the five statistical characteristics of a data segment, i.e., the variance, skewness, kurtosis, a normalized energy characteristic, and a zero-crossing rate characteristic, and carrying out the calculation of the variance, skewness, kurtosis, normalized energy characteristic, and zero-crossing rate characteristic of the data segment; combining the five statistics to construct five pairs of two-dimensional feature planes, and stacking the five pairs of two-dimensional features into a feature matrix; a power quality transaction depth monitoring model is constructed and trained, and power quality transaction monitoring is performed by using the trained model; according to the method, high-precision automatic identification of seven typical disturbances such as normal disturbance, voltage sag disturbance, voltage rise disturbance, harmonic disturbance, flicker disturbance, voltage interruption disturbance and transient oscillation disturbance is realized, and timely and accurate disturbance alarm and decision support are provided for operation and maintenance personnel of a power system.

The invention provides an urban and rural community life circle public service facility data processing and configuration optimization method, and belongs to the technical field of urban and rural planning and urban and rural simulation. The method comprises the following steps: dividing a city into standard grids, and screening a core area and a buffer area; building a graph retrieval enhancement generation knowledge base on the basis of an unstructured text, and realizing filtering and tracing of planning knowledge according to streets; instantiating a plan agent cluster, generating a resident demand, available resource and facility coverage list, and fusing to form a current situation baseline; mutually overlapped negotiation units are generated through a convolution moving window, and global continuous coverage is realized; constructing multi-dimensional stratified sampling based on mobile phone signaling and population census data, and generating a heterogeneous resident agent cluster; and driving multi-stage co-simulation and consensus evaluation of the planning agent and the resident agent, and outputting an optimization demand list and an action blueprint. According to the method, space continuous coverage, professional knowledge traceability and public participation process quantifiable convergence are realized, and the scientificity and the performability of community facility configuration are improved.

The invention belongs to the field of seismic data processing, and particularly discloses a CRP gather optimization method, system and device and a medium, and the method comprises the steps: S1, carrying out the statistics of the offset information of all gathers; s2, grouping all gathers according to offset of the gathers; s3, counting the coverage times of each gather in each offset group; s4, fitting a relation function of the compensation coefficient of each gather and the offset grouping to obtain a compensation function of the full offset of each gather; s5, solving a relation function of the ray density changing along with time to optimize the compensation function, and obtaining compensation function curves corresponding to different times; and S6, applying the compensation coefficients in the compensation function curve corresponding to different times to the CRP gather for compensation to obtain an optimized CRP gather. According to the method, the problem that the amplitude relation of the CRP gather is spindle-shaped can be effectively solved, and the precision and the reliability of pre-stack inversion are improved. The method is suitable for CRP gather optimization.

The invention discloses a seismic data processing method for eliminating a window effect, electronic equipment, a storage medium and a device. The method comprises the following steps: inputting to-be-processed seismic data; performing window division on the to-be-processed seismic data based on the first time window length, the first space window length and the overlapping length to obtain a plurality of first windows and corresponding first window seismic data; adjusting each first window based on the second time window length and the second space window length to obtain a plurality of second windows and corresponding second window seismic data; performing interpolation or denoising processing on the second window seismic data to obtain third window seismic data; extracting the third window seismic data based on the first window to obtain fourth window seismic data; and combining all the fourth window seismic data, and carrying out linear weighted transition on the overlapped region to obtain the seismic data without the boundary effect. The method can effectively eliminate the boundary effect of the window, and ensures the stability and rationality of the calculation result.

The application discloses a multi-scale feature fusion neural network phase unwrapping method and system based on De Bruijn stripe coding, first constructs a wavelength-De Bruijn element mapping table; then, the wrapped phase and the background intensity are obtained by using the collected deformation stripes and the background reference map, and the nonlinear cosine component and the phase gradient feature are calculated according to the wrapped phase and the background intensity, so that a multi-channel physical feature input tensor is constructed. Then, the tensor is input into a multi-scale feature fusion neural network with multiple parallel branches. In the training stage, a loss function based on symbol physical wavelength weighting is introduced for constraint. The application directly realizes high-precision prediction of phase order by a deep learning network, does not need additional auxiliary decoding sequence, effectively avoids the complex mathematical principle process and the tedious logic retrieval in the traditional phase unwrapping algorithm, and significantly improves the efficiency of three-dimensional measurement and the robustness to complex environment.