11results about How to "Realize visual analysis" patented technology

The invention belongs to the field of material plastic deformation, and particularly discloses a crystal grain progressive rotation visualization method and system based on a crystal plasticity finite element, and the method comprises the steps: constructing a crystal plasticity constitutive model, and employing an index method to describe the relation between a crystal grain Euler angle and a Miller index; a crystal plasticity finite element model is constructed, the crystal plasticity finite element model comprises a plurality of crystal grains with random orientation, and deformation of each crystal grain is controlled by a crystal plasticity constitutive model; performing contact constraint on the crystal plasticity finite element model through a mold in Abaqus; performing multidirectional compression simulation on the crystal plasticity finite element model to reflect a real multidirectional forging process; finite element grid node coordinates and Euler angle data of a concerned observation surface in the crystal plasticity finite element model are obtained, an EBSD interaction file is constructed, then an IPF graph is drawn, and grain progressive rotation visualization is achieved. According to the invention, dynamic simulation and visual analysis of crystal orientation in the multidirectional forging process are realized, and a grain progressive rotation mechanism is revealed from a microscopic scale.

This invention belongs to the field of engine turbocharger testing technology and discloses a method and system for evaluating the transient response of engine turbochargers. The method includes: test preparation, operating condition setting, transient excitation and data acquisition, calculation of speed increment time, calculation of intake pressure to establish efficiency indicators, and two-dimensional diagnostic evaluation. This invention effectively solves the technical problem that existing evaluation parameters cannot distinguish the root cause of response lag, and has advantages such as accurate positioning and strong guidance. It is particularly suitable for the research and optimization of turbocharger systems with stringent transient response requirements, such as hydrogen fuel cell internal combustion engines.

The application discloses a corn nitrogen reduction and biochar effect time sequence dynamic characteristic evaluation method, first, different combinations are set, chlorophyll fluorescence parameters, crown layer spectral reflectance and yield data of corn at key growth stages such as jointing stage and big bell mouth stage are collected; second, the spectral data is preprocessed, single time phase red edge characteristics are calculated, and time sequence dynamic characteristics are constructed, biochar sensitive wave bands are screened through reflectance difference percentage during growth, red edge index is designed, and fluorescence weight spectral index is constructed in combination with wide band vegetation index; then, the data is integrated to construct a multi-time phase spectral characteristic data set, a time sequence dynamic chlorophyll inversion model containing dynamic inversion, yield prediction and attribution branches is built, the former outputs chlorophyll and photosynthetic code vector at the grain filling stage, and the latter predicts yield and related parameter contribution; finally, the model is trained, the optimal matching is obtained based on the trained model, and support is provided for corn planting and fertilization decision-making.

The invention discloses a preparation method of a colorimetric sensor for gas chromatography, which comprises the following steps: dissolving dye by using a thin layer chromatography silica gel plate as a substrate and ethanol as a solvent to enable the dye to be attached to the substrate, and blow-drying. The invention also provides a gas analysis system which comprises a sample injection subsystem, a carrier gas subsystem, a capillary chromatographic separation column system, a colorimetric sensing subsystem and a data analysis subsystem. According to the invention, gas chromatography and a video data extraction program can be combined, the visual detection of a gas analyte sample can be conveniently realized, the miniaturization of a gas detection and analysis system is facilitated, and a new thought and direction are provided for the development of a miniature gas chromatograph detector.

The invention relates to an active spectral imaging system and method for insulator pollution degree grading, and the system comprises a parameter-adjustable halogen pulse light source, a power supply, a short-wave infrared imaging unit, a control unit, and an image processing unit, the control unit, the power supply, and the parameter-adjustable halogen pulse light source are connected in sequence, and the image processing unit is connected with the power supply. The short wave infrared imaging unit is connected with the image processing unit and the control unit. According to the invention, an active light source is used to irradiate and heat the insulator, and then the short wave infrared imaging technology is used to continuously photograph the surface of the irradiated insulator. Due to the fact that the thermal change rates of the insulators with different contamination degrees after irradiation are obviously different, the contamination degrees can be judged by analyzing the thermal change rates, and then visual analysis of the contamination degrees is achieved.

The application relates to the technical field of image detection, and discloses a combined template production quality detection method and system, wherein the method comprises the following steps: collecting a side surface image by adopting an RGB industrial camera in combination with multi-angle directional illumination and a signal-to-noise ratio self-feedback mechanism; performing channel selection, edge enhancement and dynamic narrowband ROI extraction; identifying interlayer boundary lines by adopting a direction angle filtering and line segment merging mechanism; establishing an offset vector function; and outputting offset and root mean square error results. Compared with the detection mode for judging the pressing quality of a multi-layer plywood in the prior art, which depends on manual visual inspection or a simple image threshold method, especially under actual production conditions that there is slight misalignment between the board layers and the edge texture contrast is insufficient, the technical problem that accurate identification and quantitative evaluation of the interlayer misalignment of the plywood side surface cannot be realized is solved; and due to the structured boundary extraction and quantitative vector modeling mechanism, the detection accuracy and the automation degree of slight misalignment defects are improved.

The present invention proposes an electrical impedance imaging method, storage medium, and device based on digital twin drive, which belongs to the field of medical imaging technology. The technical key points are: the WOVAE model is used to find the optimal potential features that match the read boundary voltage data set, and then the VAE model constructed by the virtual layer obtains the best conductivity image, and then the image output by the VAE model is interactively fed back through the communication layer. The whole method compensates for the invalid voltage data collected by the physical layer EIT device, and finally realizes highly robust lung EIT imaging. The use of the electrical impedance imaging method, storage medium, and device based on digital twin drive of the present application can effectively improve the robustness of imaging.

The application discloses a kind of approach and departure flight operation and flight plan multi-time scale deviation measurement method, belong to air traffic management technical field, including steps: constructing approach and departure flight flow time series;Coarse-grained approach and departure flight flow time series;Calculate the sequence mode distribution probability in coarse-grained time series;Calculate the permutation entropy PE value of sequence mode distribution;Calculate the IMPE value of approach and departure flight flow time series;Define and quantify the deviation of multi-scale approach and departure flight flow, draw multi-scale deviation curve;Quantitative analysis similarity relationship between the deviation of different airports;Single-airport deviation evolution analysis plane is constructed, and evolution relationship is analyzed;Define and calculate the trough characteristics of cross-day deviation;Analysis the similarity between the cross-day deviation of approach and departure flight flow of different airports.The application can solve the problems existing in the measurement of the deviation measurement, such as single measurement dimension, insufficient collaborative analysis capability, difficulty in completely covering special operation period, and incomplete description of deviation chain.

This invention discloses a method and system for energy efficiency optimization management of photovoltaic (PV) power plants, belonging to the field of PV power plant optimization management technology. It includes the following steps: S1, real-time acquisition of PV power plant operation data and data preprocessing; S2, identification of multi-feature mutations in equipment during PV power plant operation, identification of equipment operation anomalies, and generation of anomaly event records; S3, receiving anomaly event records, evaluating the coordinated fluctuation of various characteristic anomalies, identifying the anomaly type, and performing self-healing maintenance adjustments; S4, judging the effectiveness of self-healing maintenance adjustments, and optimizing the algorithm and self-healing strategy based on PV power plant operation data, anomaly event records, and the effectiveness of self-healing maintenance adjustments. This solves the problem that due to the increased data acquisition frequency at the station and string levels, the extremely short duration of anomaly events leads to diluted and missed anomaly signals, making timely manual response difficult.

The invention provides a platform operation and maintenance monitoring management method and system based on cluster management, and relates to the technical field of data processing, and the method comprises the steps: building a basic operation environment of a Kubernetes cluster; the method comprises the following steps of: deploying a Prometheus monitoring system and a Grafana monitoring system on a Kubernetes cluster; the method comprises the following steps: configuring a Java client library for a Kubernetes cluster; the method comprises the following steps of: writing a java program by using a Java client library, monitoring a Kubernetes cluster by using a Prometheus monitoring system to obtain cluster monitoring data, and outputting a cluster fault detection result through a cluster fault detection model based on a support vector machine; judging whether a fault occurs or not according to a fault detection result, if so, generating alarm information, and entering the next step, otherwise, continuing monitoring; and the alarm information is visually displayed through a Grafana monitoring system.