8results about How to "Improve analysis results" patented technology

The present invention discloses a method and system for evaluating the power generation performance of a wind farm, which relates to the technical field of power generation performance evaluation. Representative aerosol monitoring points of a wind farm are selected; based on the changes in aerosol collection data of each representative aerosol monitoring point and the changes in the corresponding wind farm power generation data, the changes are analyzed, and the degree of influence of the aerosol collection data of each representative aerosol monitoring point on the changes in the wind farm power generation data is respectively identified; the aerosol collection data of each representative aerosol monitoring point of the wind farm is monitored in real time, and then the aerosol collection data of each representative aerosol monitoring point is used to analyze the degree of influence of the changes in the wind farm power generation data, and the power generation performance of the wind farm is evaluated in real time. Through accurate monitoring and real-time analysis, it is helpful to improve the power generation performance of the wind farm, optimize the operation strategy, and improve the power generation efficiency.

The invention relates to the technical field of data processing, and discloses a data processing method and system for soil detection, and the system comprises an acquisition module which comprises a sensor network and a node control unit which are arranged in a detection area; a preprocessing module configured to determine whether there is a missing value; the data complementation module is configured to obtain the position of the missing value when the missing value is judged to exist, and determine an initial missing value according to the weighted average of the soil information on the two adjacent sides of the position of the missing value; the data correction module is configured to correct the initial missing value; and the storage module is configured to store the humidity value, the temperature value, the rainfall data, the plant coverage data, the terrain data and the corrected final missing value and establish a corresponding database. By improving a data processing flow and a correction mechanism, the accuracy and reliability of soil detection data are improved, and powerful technical support is provided for agricultural production and soil management.

The invention belongs to the technical field of time-frequency analysis, and particularly relates to a rolling bearing fault method and system based on Riesz atlas sparse decomposition, which utilizes a new time-frequency analysis method-Riesz four-parameter spectrum time-frequency analysis method to obtain four-parameter information of amplitude, frequency, phase and direction of a vibration signal in a time-frequency domain. The time-frequency aggregation and the anti-noise performance of an analysis result are improved; in order to screen out an optimal parameter spectrum and expand the symbol dynamics entropy to a two-dimensional scale, a new entropy calculation method, namely cosine symbol dynamics entropy, is provided; and reconstructing components of the parameter spectrum obtained by entropy screening, and constructing a sparse filter parameter optimization component amplitude, so that a decomposition result has physical significance. The bearing vibration signal under the variable speed working condition and the bearing vibration signal under the constant speed are analyzed, the RSSD method is provided on the basis, and feature extraction and diagnosis of rolling bearing faults under the constant rotating speed working condition and the variable rotating speed working condition are achieved.

The invention relates to the technical field of machine learning, in particular to a time series data analysis system and method based on deep learning, and the system comprises an input preprocessing module which is used for carrying out the standardization processing and segmentation processing of input time series data; the sliding window recurrent neural network module is used for processing the input time sequence data in each sliding window of eight thousand time steps to generate a short-term time sequence feature vector; the dynamic updating recurrent neural network module is used for processing long-term time sequence data; the meta-learning optimization module is used for dynamically updating initialization parameters of the recurrent neural network module through outer loop optimization; and the output fusion module is used for fusing the feature vectors and generating a final time sequence analysis result. According to the method, a weight updating mechanism which only updates the last quarter layer of the recurrent neural network is innovatively designed, the calculation complexity is remarkably reduced, and the contradiction between the calculation efficiency and the model adaptability in long-sequence time sequence analysis is effectively solved while high precision is kept.

The invention discloses a digital twinborn space vision field auditing analysis method, which belongs to the field of digital twinborn space analysis, and comprises the following steps: obtaining a to-be-audited building contour, carrying out gridding splitting on the surface of the building contour, and constructing an optimized triangular mesh model; obtaining a grid center point which is split to the optimal granularity from the optimized triangular grid model, recording coordinates of point locations, and generating point cloud data; delimiting a digital twinborn area for vision field auditing analysis, and obtaining boundary information of a target area; transmitting a ray to the target area according to the point cloud data, and performing special color rendering on a target area of the ray; and calculating and analyzing the target area of the ray, checking personnel data in the area and the vision field condition of each building, and outputting an auditing report. According to the invention, a digital twin space laser technology is adopted, vision field auditing analysis of a special building or a building group is mainly solved, and the method is suitable for multi-scene requirements of building design optimization, urban planning, public safety management and the like.

This invention discloses a device for detecting down composition and residual fat content, comprising a controller, a composition detection mechanism, and a sample dispersion mechanism, a microwave extraction mechanism, and a drying and weighing mechanism connected in sequence. The sample dispersion mechanism includes a sample chamber and a dispersion cavity. A miniature electromagnetic vibrator is installed at the bottom of the sample chamber, with its top surface inclined to the dispersion cavity. The dispersion cavity is a transparent cavity with an air outlet, an air inlet, and a telescopic rod A. A mesh sieve plate is fixed to the top of the telescopic rod A, and a sample recovery port is located above the sieve plate. The composition detection mechanism is connected to the dispersion cavity. The controller connects to each component. This invention achieves integrated automatic detection of down composition and residual fat content by integrating composition detection, microwave extraction, and drying and weighing. It replaces Soxhlet extraction with microwave extraction, significantly shortening the residual fat detection time and reducing the amount of organic solvent used. Through automatic dispersion, sieving, and optical analysis, it reduces manual intervention and improves the efficiency, objectivity, and repeatability of composition analysis results.

The invention belongs to the technical field of analytical chemistry, and particularly relates to a method for detecting related substances in alfacalcidol soft capsules, which comprises the following steps of: determining by adopting high performance liquid chromatography under the chromatographic conditions that: a chromatographic column adopts octadecylsilane chemically bonded silica as a packed column; acetonitrile is used as a mobile phase A, water is used as a mobile phase B, and a gradient elution mode is adopted; the detection wavelength is full wavelength scanning of 263 to 267 nm or 200 to 400 nm; the flow velocity is 1.0 to 2.0 mL / min. The method is high in precision, the recovery rate can reach 90% or below, the detection time is only 70-80 minutes, and guarantees and technical supports are provided for the quality reliability, stability and safety of the alfacalcidol soft capsules.