8results about How to "Great industrial application value" patented technology

The application provides a SNP molecular marker and a breeding application method which are significantly related to the content of chicken meat flavor substance (E, E)-2,4-decadienal. The SNP molecular marker is rs316165567, contains a nucleotide sequence with a polymorphism of C / A at 2,519,798 bp of chicken chromosome 14, and when the genotype of the site is AA, the content of (E, E)-2,4-decadienal of the chicken meat sample is higher. The established molecular assisted breeding technology can early select the high-quality chicken flavor quality traits by determining the genotype of the SNP site of the measured chicken, can improve the content of (E, E)-2,4-decadienal of the chicken breast, and has great industrial application value and economic and scientific research value.

The application discloses a bearing fault diagnosis method and system based on a CS-SHAP model, bearing operation signals are collected through acceleration, temperature and acoustic emission multi-sensor, multi-dimensional fault features are extracted from time domain, frequency domain and time-frequency domain after wavelet transform or EMD algorithm denoising to complete preprocessing, feature data is divided into similar clusters by K-means clustering, SHAP values are calculated cluster by cluster and weighted according to cluster data density or diagnosis influence degree to obtain feature importance score, a SVM classifier based on RBF kernel function is trained with screened key features, model parameters are optimized through 5-fold cross validation, new collected data is preprocessed and input into the trained model to obtain diagnosis results, feature SHAP values are calculated and visualized by using the CS-SHAP model, and key factors of faults are analyzed. The application realizes accurate diagnosis of bearing faults and interpretability of diagnosis results, and provides technical support for intelligent operation and maintenance of industrial equipment.

This invention discloses a method and application for preparing amorphous hard carbon anode materials using waste PP separators. The method includes: obtaining waste PP separators from retired lithium-ion batteries and sulfonating them to obtain sulfonated PP separators; then subjecting the sulfonated PP separators to high-temperature carbonization to obtain amorphous hard carbon anode materials. This invention chemically modifies waste PP separators through sulfonation, controlling the structure and carbonization pathway of PP, suppressing severe chain breakage and volatilization during high-temperature carbonization, improving carbon yield, and ultimately obtaining amorphous hard carbon anode materials. When this amorphous hard carbon anode material is applied to sodium-ion batteries, the sodium-ion batteries exhibit excellent cycle performance and rate performance. This achieves high-value recycling and reuse of waste PP separators from retired lithium-ion batteries, solving the environmental pollution and resource waste problems caused by incineration or low-value recycling of waste PP separators.

A tracked external rotor magnetic motor utilizing axial closed-circuit and open-circuit magnetic fields is disclosed. An axially magnetized annular planetary permanent magnet attracts the inner edge of a pressure-bearing elliptical steel track, creating two radial magnetic potential angles on the upper and lower sides of the track's inner edge. At the lower angle, the side poles of the annular permanent magnet are attracted by opposite-pole permanent magnets, resulting in a closed magnetic field that eliminates the magnetic force on the track, causing it to follow the magnet's movement. At the upper angle, the side poles of the annular permanent magnet have an open magnetic field, causing the permanent magnet roller to rotate under the radial magnetic potential, driving the output gear ring wheel. This closed-circuit magnetic effect forms the rotational cycle. This device not only increases the output power density but also compensates for the high friction, power loss, and noise associated with planetary rotation mechanisms. It can be widely applied in transportation, energy construction, energy conservation, and environmental protection. Its simple mechanical structure and manufacturing process make it valuable for broad industrial and commercial applications.

The invention relates to the technical field of identification, and discloses an intelligent identification method based on dynamic display, which comprises the following steps: S1, a data acquisition step: acquiring scene environment data and user state data in real time through a deployed environment sensor and a user positioning module; according to the invention, through an environment sensor and a multimode positioning module, multi-dimensional data such as illumination, temperature and humidity, a user position and a moving track are collected in real time, and in combination with a demand classification model driven by deep learning, user demands are accurately divided into three core scenes of navigation guidance, information query and activity reminding. And meanwhile, the priority of the identification content is determined by matching the scene state through the priority ranking model, so that irrelevant information interference of the user can be effectively avoided, the core demand matching accuracy is improved by more than 40%, the method is particularly suitable for complex scenes such as shopping malls and transportation hubs, the user information acquisition cost is remarkably reduced, and the individuation and accuracy of the identification service are improved.

The invention discloses an air leakage positioning and quantifying method and system based on dynamic schlieren imaging and a space-time neural network, and the method comprises the steps: constructing a schlieren imaging system, introducing a local controllable heat source into a leakage region, and obtaining a schlieren image sequence of a leakage flow field and leakage source position information; preprocessing the schlieren image sequence to obtain a processed image sequence with unified resolution and normalized pixel values; the processed image sequence is input into a pre-trained CA-ResFpn-ConvLstm neural network model, and a leakage rate prediction value is obtained; and outputting a leakage rate prediction value, and synchronizing visual leakage source position information to complete air leakage detection. Through the integrated design of optical visualization and intelligent quantification, the technical problems that in existing industrial air leakage detection, sensitivity is insufficient, quantification is difficult, and real-time performance is poor are solved, an efficient and reliable technical scheme is provided for industrial safety monitoring, and the industrial application value is wide.

The invention provides a provincial domain atlas automatic generation method and system based on wind energy and solar energy resource data, and the method comprises the steps: firstly obtaining resource data with the resolution of 1 kilometer or 200 meters, the data containing key information of wind energy and / or solar energy resource evaluation; secondly, processing the boundary data by utilizing a vector map processing tool, generating a Shapefile of a target province, and ensuring the space matching between the Shapefile and resource data; next, loading and processing the data in the NetCDF format through a script language, and converting the coordinate system into a WGS84 longitude and latitude system which is widely applied globally; and then, the generated provincial Shapefile is adopted as a mask, and a resource variable value in a target province is cut out, so that the accuracy and correlation of data are ensured. And finally, drawing the processed resource data according to preset standardized graphical representation parameters, and outputting the processed resource data in a PDF, PNG or EPS format for subsequent analysis and display. According to the method, the efficiency and accuracy of resource evaluation and map making are greatly improved.

The invention discloses a bid invitation purchasing compliance and risk decision-making method based on a bipolar discussion theory. The method comprises the following steps: firstly, carrying out structuring and atomization processing on bid invitation documents and laws and regulations through a DeepOCR and a big language model; fusing the internal atomic arguments and external evidences, and constructing a bidirectional argument graph containing a support relationship and an attack relationship; and iteratively calculating the standing intensity score of each argument through an aggregation influence model to realize quantitative risk assessment. And finally generating a structured auditing opinion with a traceable evidence chain, and automatically distributing the structured auditing opinion to an expert review or automatic approval channel according to the risk level. Through a man-machine cooperation feedback mechanism, expert correction opinions are settled as new knowledge, and continuous self-evolution of the bidding knowledge ontology network is realized. According to the method, the accuracy, interpretability and adaptability of compliance judgment are remarkably improved, and the method is suitable for government purchase, project bid invitation, enterprise internal control and other scenes.