6results about How to "Same characteristics" patented technology

An MIMO array sparse rapid design method of a fuzzy function generator based on deep learning comprises the following steps: firstly, directly learning a fuzzy function mapping relation corresponding to virtual array configuration and an incident angle by using a deep learning model so as to replace a traditional analysis fuzzy function calculation process depending on a manifold matrix; and then performing efficient performance evaluation on the candidate sparse array based on the fuzzy function generator, and obtaining a sparse array structure meeting the requirements of high resolution and low sidelobe in combination with an optimization strategy. By means of the technology, acceleration of more than 35 times can be achieved on the premise of not explicitly calculating the fuzzy function, the fuzzy function prediction root mean square error (RMSE) lower than 0.1 is kept, and therefore the sparse array design time is greatly shortened. Experiments on a 2T4R K-band MIMO radar prove that the designed array achieves 10 dB sidelobe level in a 100-degree field of view, the angular resolution is improved by about 32.8%, and the effectiveness and engineering application value of the method in high-resolution MIMO sparse array design are proved.

The invention relates to the technical field of millimeter wave power measurement, and provides an integrated calorimetric load based on a thin film technology and a power measurement method. The integrated calorimetric load comprises a waveguide tube and a chip absorber arranged outside the waveguide tube, the chip absorber comprises a silicon-based thin film layer and a functional thin film layer located on the silicon-based thin film layer, and the functional thin film layer comprises a first resistive thin film layer used as a direct-current heating source and a second resistive thin film layer used for measuring temperature. According to the technical scheme, the technical problem that an absorber with good matching characteristics and high replacement efficiency is difficult to design according to a traditional design thought when the signal frequency rises to a millimeter wave frequency band and even a terahertz frequency band in the prior art is solved.

The application relates to the technical field of performance evaluation of a biological aerosol sampler, and provides a biological aerosol sampler performance evaluation method, which comprises the following steps: environment construction: adjusting and maintaining the temperature, humidity, air pressure and air cleanliness in a calibration cabin to a preset target range; aerosol generation and homogenization: generating standard aerosols containing a target tracer in the calibration cabin, and mixing the air in the cabin to form a test aerosol environment with uniform spatial concentration distribution in a sampling area; dynamic sampling: making the detected sampler and a comparative sampler sample at multiple different spatial points in the calibration cabin; data comparison and analysis: performing performance calibration on the detected sampler according to the sampling data of the detected sampler and the comparative sampler. The environment conditions highly close to actual application scenarios are constructed, and the comprehensive performance of the biological aerosol sampler can be scientifically, systematically and quantitatively evaluated and calibrated.

This invention belongs to the technical field of bearing fault diagnosis. To address the inaccuracy of existing bearing fault diagnosis methods, this invention proposes a fault diagnosis method and system for press bearings based on conditional generative adversarial networks (GANs). A generator is trained using operating condition vectors and Gaussian noise. A discriminator is trained using the health state features generated by the generator and the actual health state features. The generator and discriminator are then subjected to adversarial training to prevent the discriminator from distinguishing between the health state features generated by the generator and the actual health state features, as well as from distinguishing the matching between the health state features generated by the generator and the corresponding operating condition vectors. This results in a well-trained health state model. The health state model is then used to generate a dynamic health baseline for the press shaft to be diagnosed, thereby obtaining the fault diagnosis result for the press shaft and achieving high-precision fault diagnosis and early warning.

The utility model relates to the technical field of electronic device potting, and discloses a volume resistivity detection device of organic silica gel for electronic device potting, a storage box is arranged on the front side of the top of a fixing table, a clamping mechanism is arranged at the bottom of the fixing table, a rotation detection mechanism is arranged at the back end of the top of the fixing table, and the rotation detection mechanism is connected with the storage box. A detector is arranged on the front face of the rotation detection mechanism, the rotation detection mechanism comprises a rotation assembly and a detection assembly, the rotation assembly is arranged at the back end of the top of the fixed table, the detection assembly is arranged on the right side of the bottom of the rotation assembly, the rotation assembly comprises a supporting frame, and the supporting frame is fixedly connected to the back end of the bottom of the fixed table. According to the utility model, an organic silicon gel sample can be stirred before detection, so that the problems that the components of the organic silicon gel are possibly non-uniform and bubbles appear in the organic gel are effectively solved, the consistency of the characteristics of the sample is ensured when the volume resistivity is measured, and the accuracy of a measurement result is improved.

The invention provides a feature extraction and fusion reconstruction method, an electronic device, a medium and a product, the feature extraction and fusion reconstruction method comprises the following steps: obtaining channel time sequence data, and carrying out dimension standardization and time sequence arrangement on the channel time sequence data to obtain preprocessed data; pCA dimension reduction processing is carried out on the preprocessed data, and static features are extracted; sampling the preprocessed data by adopting a sliding window, and constructing a time sequence sample; extracting dynamic characteristics of the time sequence samples; performing full-connection mapping on the static features; performing feature splicing and regression output on the static features and the dynamic features; and training, testing, evaluating and visualizing the output result. According to the feature extraction and fusion reconstruction method, the static space feature and the dynamic time-varying feature of the channel can be precisely restored, high-precision channel modeling and reconstruction of a millimeter wave communication system in a dynamic environment are achieved, robustness, stability and channel estimation performance are good, delay is short, and generalization ability is high.