14results about How to "Reliable basis" patented technology

The invention discloses an underground structured light casing deformation video imaging detection device and method.The underground structured light casing deformation video imaging detection device comprises a detection device body, and the detection device body comprises a ground system, a logging cable, an underground video imaging detection probe, a structured light generation device and a structured light installation structure. A reference light path is arranged on the shaft wall in the image, and shaft corrosion and deformation problems are accurately identified through the change of the reference light path; the device improves the detection accuracy and efficiency of the inner wall of the shaft, obtains video images of the inner wall of the shaft, truly, visually and comprehensively displays the corrosion and deformation problems of the shaft wall, can reflect the geometric morphology of the inner wall of the shaft through a reference light path provided by the structured light even if the corrosion and the deformation are slight, achieves accurate recognition, and improves the detection accuracy and efficiency of the inner wall of the shaft. A reliable and comprehensive basis is provided for further processing of shaft corrosion and deformation problems, scientific decision making and fine operation are achieved, and the operation efficiency and the success rate of shaft problem processing are improved.

The application belongs to the technical field of fault identification, and discloses an equipment processing device fault identification method and system based on artificial intelligence. The method comprises the following steps: in a cloud data center, using an artificial intelligence algorithm, an equipment processing device fault identification engine is constructed, and a multi-modal data acquisition device is connected through an edge computing gateway; using the multi-modal data acquisition device, real-time monitoring multi-modal data of the equipment processing device is acquired, and is uploaded to the cloud data center through the edge computing gateway; in the cloud data center, according to the real-time monitoring multi-modal data, using the equipment processing device fault identification engine, fault identification is carried out, and real-time fault identification results and real-time fault maintenance strategies are obtained. The application solves the problems of single data dimension, limited model depth and precision, and lack of response mechanism in the prior art.

The invention discloses a novel gastrointestinal tract environment image enhancement and optimization method. The method comprises the following steps: receiving original image data of a gastrointestinal tract environment; performing real-time shooting by using special medical imaging equipment or obtaining the original image data in other legal modes; analyzing color and contrast information of the original image data on the basis of a preset algorithm: implementing by using multiple algorithms; adjusting image parameters according to the color and contrast information; generating an enhanced gastrointestinal tract environment optimization image; analyzing color and contrast information of the original image data based on a preset algorithm; dynamically adjusting exposure time of an image based on light sensor data of real-time image acquisition equipment so as to stabilize a light environment in gastrointestinal endoscopy. According to the scheme disclosed by the embodiment of the invention, the problem of non-uniform image brightness caused by unstable light environment in gastrointestinal endoscopy can be solved.

According to the dynamic threshold value method and system based on the median and absolute median deviation, the median is used for replacing the average value, and compared with the average value, the median is not sensitive to an extreme value, so that the influence of noise data on a result can be effectively reduced, and the set threshold value is more stable and reliable; the improved absolute median deviation is used for replacing the standard deviation, so that the insensitivity of the median to an abnormal value is kept, and for a data set in non-normal distribution, more stable dispersion estimation is provided; besides, a dynamically adjusted threshold value coefficient is designed, the threshold value is automatically adjusted according to the characteristics of a data set, it is ensured that the change trend of data can be more sensitively captured, and meanwhile the phenomenon of false alarm or missing alarm caused by improper setting of a fixed threshold value is avoided. After the method is adopted, the short-term fluctuation and the long-term trend of the data can be reflected more accurately, and a more reliable basis is provided for decision makers.

The invention discloses a multidisciplinary crossed natural fracture three-dimensional quantitative characterization method and system, and belongs to the technical field of petroleum and natural gas exploration and development. The method comprises the following steps: carrying out quantitative description and statistics on natural fractures according to geological data and coring data of a research area; calculating the crack strength by using coring data; analyzing the anisotropy of shear wave energy differentiation through logging data; calculating a b value by using the microseismic data; calculating a seismic curvature attribute according to the curvature of the curve; the number, strength and distribution condition of the natural fractures in the stratum are determined according to the results; from these analyses, geologic features and related geological activities are further interpreted and instructive suggestions are provided for engineering design and geological exploration. According to the method, the accuracy of an analysis result is improved, shale gas exploration and development benefits are improved, data errors and uncertainty are reduced, and more accurate engineering decisions are supported.

The present invention provides a tethered unmanned aerial vehicle tether cable traction tension vector measurement mechanism, which can measure and feedback the tether cable traction tension vector information in real time, so that the flight control system can effectively control the unmanned aerial vehicle, maintain a normal flight attitude at any time, and ensure the flight safety of the tethered unmanned aerial vehicle. The measurement mechanism includes: an adaptive follow-up tether cable connection mechanism and a sensor group; the adaptive follow-up tether cable connection mechanism includes: two semicircular pull rings and a sliding buckle connection assembly; the sensor group includes: angle sensors for measuring the two semicircular pull rings and a tension sensor arranged between the tether cable and the tethered unmanned aerial vehicle connection point; the direction indicated by the synthesis of the two semicircular pull rings is the traction tension vector direction, and the tension measured by the tension sensor is the size of the traction tension vector. The present invention provides a reliable basis and effect feedback for the tethered unmanned aerial vehicle flight control system to implement effective control, thereby ensuring flight safety.

The application relates to a tumor intraoperative evaluation method and system based on multi-wavelength photoacoustic mathematical statistics analysis, wherein the method comprises the following steps: irradiating a tumor tissue with a pulsed laser during operation, collecting photoacoustic signals at different wavelengths in time sequence according to a preset wavelength sequence, performing mathematical statistics spectrum analysis after pretreatment to obtain multi-wavelength statistical parameters reflecting the characteristics of the photoacoustic signals; performing parameter mapping on the multi-wavelength statistical parameters to obtain a parameter imaging graph reflecting the scattering characteristics and microstructure differences of the tissue, obtaining a parameter spectrum curve based on the parameter imaging graphs at different wavelengths, and extracting auxiliary features based on the parameter imaging graphs; performing visual analysis based on the parameter imaging graphs and the parameter spectrum curve, spatially positioning a lesion area, selecting a ROI and visually displaying the lesion area; and taking the multi-wavelength statistical parameters and the auxiliary features as inputs of a tumor benignity and malignancy evaluation model to output a tumor classification result. Compared with the prior art, the application has the advantages of being capable of realizing rapid and accurate intraoperative evaluation.

This invention relates to the field of organoids, and discloses a method for detecting the drug sensitivity of primary tumor organoids. The method includes: obtaining the major diameter L0 of each organ type in well D0. n Area S0 n Observation of transmittance T0 n Surface smoothness R0 n Morphological integrity C0 n Obtain the major diameter L4 of each organ in well D4. n Area S4 n Observation of transmittance T4 n Surface smoothness R4 n Morphological integrity C4 n And the average fluorescence intensity Fg within the area of ​​organoids determined by live and dead fluorescence staining. n and Fr n The normalized score change values ​​of the organoids corresponding to each well in D0 and D4 are calculated according to the formula. This invention overcomes the problems of limited dimensions and low confidence in previous organoid drug sensitivity interpretation methods. By combining light microscopy information with fluorescence information, it comprehensively provides important information such as the growth status and viability of each organoid in the field of view, which is a reliable new method for detecting organoid drug sensitivity.

The invention relates to the technical field of intelligent decision making, and discloses an aggregation question answering method, system and device based on embedded semantic indexing and hierarchical aggregation reasoning and a medium, comprising: performing automatic desensitization processing on an original dialogue log, the original dialogue log at least comprising a detachable semantic block; performing multi-layer semantic vectorization conversion on the desensitized semantic blocks; integrating the semantic vector and a question and answer engine, and performing semantic aggregation reasoning based on the semantic vector of the set level according to the question and answer engine to generate a semantic aggregation reasoning result; on the basis of the aggregation reasoning result of the question and answer engine, performing group difference analysis on the semantic vector to obtain an initial group difference analysis result; the method can be applied to development of business systems such as financial science and technology, medical health, old-age care and the like, general viewpoints are extracted from massive dialogues through semantic aggregation reasoning of a set level, and the problem that single analysis is scattered and has no global cognition is solved.

The present invention provides a method, medium and system for optimizing the surface smoothness ratio of civil engineering concrete of substation facilities, belonging to the technical field of concrete ratio, including: firstly, collecting the physical and chemical property data of raw materials such as cement, sandstone, admixture, etc., establishing a concrete surface smoothness evaluation model, and comprehensively considering parameters such as surface roughness, flatness, glossiness, etc. On this basis, designing a small-scale indoor test to simulate engineering conditions, using computer image analysis to obtain the measured surface smoothness index under different ratios, and fitting and optimizing the model. Using computer-aided ratio design software to generate multiple groups of optimized ratios, using orthogonal test method to carry out pilot experiments, and further optimizing the fitting model. Finally, field tests are carried out in actual engineering, and the ratio with the best smoothness index is selected as the final optimization result. The technical problem that it is difficult to obtain the optimized ratio of concrete surface smoothness due to relying on the subjective experience and trial and error of engineering personnel is solved.

The invention discloses a GIS-based photovoltaic power station intelligent arrangement design method and system, and relates to the technical field of photovoltaic power station design. The method comprises the following steps of mountain terrain initial modeling, mountain terrain shadow photovoltaic arrangement optimization and photovoltaic arrangement design scheme recommendation output. Geographic information data of a to-be-arranged mountain area is acquired based on a GIS to perform terrain modeling, and the to-be-arranged mountain area is divided to obtain photovoltaic design areas so as to preliminarily generate a photovoltaic arrangement design scheme. Then, surface shielding shadow continuity analysis is carried out on each photovoltaic design area in a shadow analysis period to determine adopted photovoltaic power station arrangement design optimization, and finally, the photovoltaic power station arrangement design schemes and the scheme recommendation priorities are synchronously output to a manual terminal, so that the generation efficiency of the photovoltaic power station arrangement design schemes is improved. The problems that in the prior art, due to mountain terrain shadow overlapping, photovoltaic power station arrangement is inaccurate, and the power generation efficiency is reduced are solved.

The invention discloses an annular blowout preventer rubber core failure prediction method and system based on a neural network, and relates to the field of oil and gas exploitation equipment monitoring, and the method comprises the following steps: obtaining multi-dimensional working data of an annular blowout preventer rubber core, comprising a use time sequence, a displacement sequence, a hydraulic pressure sequence and a corresponding failure degree label sequence; performing dynamic space-time normalization processing to generate a normalized sample set fused with time relevance; performing supervised heterogeneous neural network model training; and inputting the working data of the rubber core of the annular blowout preventer to be detected into the optimized supervised heterogeneous neural network model, outputting a corresponding failure probability sequence and triggering an early warning mechanism. According to the method, by integrating multi-dimensional data and carrying out dynamic space-time normalization processing and multi-modal heterogeneous neural network modeling, the failure prediction precision and real-time performance are remarkably improved, and full-period management of the rubber core of the annular blowout preventer is achieved in combination with a grading early warning mechanism and threshold value self-adaptive updating.

The invention relates to the technical field of project management evaluation, and particularly discloses a construction project management evaluation method and system based on big data analysis, and the method comprises the steps: S1, obtaining a construction period, dividing the construction period into a plurality of construction period nodes, and forming a construction period unit by each two adjacent construction period nodes; s2, historical construction information is obtained, the historical construction information comprises the laid length and the material consumption amount in each construction period unit, a material consumption curve is established through the data, and a correction coefficient is calculated; s3, acquiring weather data during construction, establishing a construction model, integrating the weather data into the construction model, simulating a construction process, and predicting laid length and material consumption in each construction period unit; s4, the actual laid length is obtained in real time, and the reference consumption and the use efficiency index are calculated according to the consumption influence coefficient so as to judge whether the material consumption in the current construction period is abnormal or not.

This invention relates to the field of unmanned aerial vehicle (UAV) simulation technology and discloses a method for simulating UAV flight status based on digital twins. The method involves constructing a digital twin system containing a physical UAV entity and a virtual simulation model, and collecting multi-source flight data streams, including the physical UAV's position information, motion parameters, and environmental perception data. Multi-dimensional feature fusion processing is performed on the multi-source data to generate a fused feature representation. Based on this fused feature, a probabilistic state modeling algorithm is used to determine the estimated flight status and related confidence information. The virtual simulation model is updated based on the estimated values ​​and confidence levels to simulate real-time flight status. Flight status clustering analysis is performed in the virtual model to detect abnormal patterns, and an adaptive simulation threshold set is generated based on historical flight data. By comparing the abnormal patterns with the adaptive threshold set, simulation control commands are output for UAV operation. This method can effectively support accurate simulation and anomaly control of UAV flight status.