18results about How to "Effectively eliminate interference" patented technology

The invention discloses a universal molecular beacon kit for various animal-derived components, and belongs to the technical field of molecular biological detection. Aiming at gene segments with specific structural characteristics in 11 common livestock and poultry animal genomes, the invention designs a composition of a universal primer and a molecular beacon fluorescent probe. The combination can be used for carrying out real-time fluorescent PCR detection and melting curve analysis by using the kit and the method by taking genome DNA of a sample to be detected as a template. By comparing the shape of a melting peak of a detected sample and the characteristic melting temperature (Tm value) of the detected sample, 11 animal-derived components of livestock and poultry can be quickly and accurately identified under the condition of single-tube detection. Technical innovation is achieved in the field of molecular biological detection, an efficient and reliable solution is provided for animal-derived component detection, and the method has important practical value and popularization potential.

The invention relates to the technical field of robot performance evaluation, in particular to a robot acceleration performance evaluation method and device, and the method comprises the steps: generating an acceleration mapping matrix of a robot according to a pre-constructed robot dynamic model; performing singular value decomposition on the acceleration mapping matrix to obtain at least one singular value representing the geometric features of the dynamic operable ellipsoid of the robot; and calculating at least one composite acceleration performance index of the robot according to the at least one singular value, and generating an acceleration performance evaluation result of the robot according to the at least one composite acceleration performance index. Therefore, the problem that the overall dynamic performance of the robot under the actual complex working condition cannot be accurately represented due to the fact that the evaluation result is easy to have one-sidedness due to the fact that a single acceleration related index is usually adopted as the evaluation basis in the related technology is solved.

The invention relates to the technical field of electronic information, and discloses a reference following anti-interference bidirectional current sampling method and system, and the method comprises the steps: carrying out the driving characteristic enhancement processing of a reference voltage signal, and obtaining an enhanced reference voltage signal; performing common-mode interference suppression processing on the original differential voltage signal to obtain a net differential voltage signal; performing linear amplitude adjustment on the net differential voltage signal to obtain an amplified voltage signal; mapping the amplified voltage signal into a unipolar voltage range by taking the strengthened reference voltage signal as a reference zero point to obtain a unipolar voltage signal; performing correlation coupling on the long-term characteristics and the short-term characteristics to obtain correction parameters, and performing signal reconstruction on the unipolar voltage signals based on the correction parameters to obtain optimized unipolar voltage signals; performing synchronous decoding on the optimized unipolar voltage signal based on the enhanced reference voltage signal to obtain an instantaneous current value and a flowing direction; according to the invention, the precision of bidirectional current sampling can be improved.

The invention discloses a medical image super-resolution reconstruction method and device, equipment, a medium and a product, and relates to the technical field of computer image processing, and the method comprises the steps: carrying out the preprocessing of the original data of brain nuclear magnetic resonance of a target object, and obtaining a high-resolution reference image and a low-resolution target image; respectively extracting multi-scale features of the target image and the reference image to obtain a multi-scale target feature map and a multi-scale reference feature map; based on the multi-scale target feature map and the multi-scale reference feature map, screening out key features and performing texture enhancement on the key features to obtain a multi-scale texture feature map; aligning and fusing the multi-scale texture feature map and the multi-scale target feature map to obtain a multi-scale fused feature map; and generating a high-resolution target image based on the multi-scale fusion feature map. According to the method, the core anatomical structure of the reconstructed image is clearer, the noise is lower, and the requirements for anatomical information of different scales in clinical diagnosis are met.

The application discloses a method for quickly solving a wind tunnel test pressure conduction delay correction parameter, and the method obtains various parameters in a test field through a measuring system, and synchronously corrects and processes test data to meet the requirement of the quasi-real-time analysis of test data in a blowing test. Meanwhile, a graphical display tool is used to distinguish the coupling effect of the pipeline delay effect and the self aerodynamic phenomenon in a pressure measuring point, accurately select the pressure measuring point suitable for the synchronous parameter calculation, and further use the graphical verification means of the correction effect, so that the correction parameter deviation caused by the improper selection of the pressure measuring point can be effectively solved, the accuracy of the synchronous correction parameter measurement is improved, and the interference quantity possibly caused by the nonlinear change pressure measuring point can be effectively removed, and the accuracy of the synchronous correction parameter measurement is improved.

The application provides a tunnel leakage water site rapid positioning and grouting effect real-time evaluation system, and belongs to the technical field of tunnel engineering monitoring. The system comprises: an intelligent inspection and accurate positioning subsystem, which is used for automatically collecting multi-source perception data on the lining surface and outputting three-dimensional coordinates of the leakage site through multi-modal data fusion; a grouting process dynamic monitoring and regulation subsystem, which is used for collecting grouting parameters and physical field response signals in real time, performing state analysis and intelligent early warning; a grouting effect multi-sequential quantitative evaluation subsystem, which is used for repeatedly collecting physical field information at different stages of slurry setting to generate quantitative evaluation indexes; and a central processing and decision platform, which is used for coordinating and scheduling the subsystems, processing and fusing whole-process data, and generating decision instructions. The application realizes whole-process closed-loop intelligent management of leakage diseases from accurate positioning, process controllability to effect verification, and significantly improves the accuracy, reliability and efficiency of treatment.

This invention relates to the field of printing defect detection technology, specifically a method for detecting printing defects in environmentally friendly art paper based on image recognition. The method includes: acquiring multispectral printing images of the environmentally friendly art paper sample to be tested, including images from three spectral channels: visible light, infrared reflection, and ultraviolet excitation; separating the printing area from the background substrate, extracting effective pixel regions, and constructing a benchmark library of printing defect features spanning the three spectral types; inputting the effective pixel regions into a pre-trained deep convolutional defect recognition network, performing multi-level feature matching with the benchmark library to generate preliminary defect recognition results; performing cross-spectral verification on the preliminary results, and confirming the final defects by combining the abnormal features of the three spectral types; marking the defect areas and generating a detection report. This method can improve the accuracy and comprehensiveness of printing defect detection on environmentally friendly art paper and is suitable for environmentally friendly art paper printing quality inspection scenarios.

The application is suitable for the technical field of intelligent devices, and provides a voice recognition method and device, an intelligent device and a storage medium. The method comprises the following steps: inputting a to-be-recognized voice into a trained voice recognition model, and obtaining a feature probability spectrum of the to-be-recognized voice; decoding and searching the feature probability spectrum to obtain a first search result; decoding and searching the feature probability spectrum based on a scene word graph model to obtain a second search result, wherein the scene word graph model is a language model used to provide a scene grammar rule; and determining and outputting a recognition result of the to-be-recognized voice according to a fusion result of the first search result and the second search result. The application can effectively exclude the interference of a non-scene high-probability path on a search result, improve the accuracy of voice recognition in a real-time voice recognition scene, improve the performance of voice recognition, and thus enhance the user experience.

This invention provides a method, apparatus, electronic device, and storage medium for detecting abnormalities in wind turbine bolts. The method includes: acquiring high-frequency stress wave signals, low-frequency vibration signals, and axial force detection signals of the wind turbine bolts during their service life; performing feature extraction based on the high-frequency stress wave signals to determine acoustic emission characteristics; performing feature extraction based on the low-frequency vibration signals to determine vibration characteristics; performing feature extraction based on the axial force detection signals to determine axial force characteristics; combining the acoustic emission characteristics, vibration characteristics, and axial force characteristics to determine a multidimensional time-series tensor; performing time-series correlation processing on the multidimensional time-series tensor to determine a health score and fault mode probability distribution information; and outputting bolt abnormality information based on the health score and the fault mode probability distribution information. This invention improves the timeliness and detection accuracy of wind turbine bolts.

This invention discloses an adaptive terrain-following flight control method and system for railway unmanned aerial vehicles (UAVs) that integrates multi-source terrain data and a data-driven model. The method utilizes an extended Kalman filter to estimate the change in rotational inertia online, dynamically correcting a preset initial dynamic model to obtain a dynamic baseline model. Simultaneously, it integrates multi-source terrain data to generate a terrain-following flight reference altitude surface that considers the track's geometric characteristics, using the track centerline as a constraint. Vertical and horizontal trajectories are planned based on the surface curvature, and dynamic yaw angles are calculated. A Gaussian process-enhanced prediction model is constructed, incorporating aerodynamic parameter perturbation learning and L1 adaptive laws into the nonlinear model predictive controller. An inner and outer loop cascaded architecture is used to solve for total lift and three-axis torque control quantities. Flight is driven by a pseudo-inverse assignment matrix mapped to rotor speed commands, and a safe distance is monitored in real time to trigger replanning. This method solves the problems of model mismatch and environmental adaptation in complex environments, improving flight safety and trajectory tracking accuracy.

The invention relates to the technical field of urban heat supply, and discloses a heat supply system multi-heat-source joint scheduling method and system based on an ant colony algorithm, and the method comprises the steps: obtaining real-time temperature data, carrying out the preprocessing, obtaining a temperature distribution map, calculating a deviation value between each node temperature and a preset expected temperature, carrying out the quantification of the deviation value, and carrying out the calculation of the real-time temperature data. Obtaining a temperature drift vector; calculating the contribution value of each heat source to each node, and generating a heat source contribution evaluation matrix; if the contribution value is lower than a preset contribution value threshold value, an output parameter of a heat source corresponding to the contribution value is adjusted, and a heat supply task distribution scheme is obtained; performing simulation operation according to the heat supply task distribution scheme, recording a test temperature drift response, and calculating a system stability index; and if the system stability index meets the system stability requirement, the heat supply task allocation scheme is applied to an actual heat supply network, and a multi-heat-source joint scheduling scheme is obtained. The method can solve the problem of uneven resource distribution of the heat supply system in a dynamic environment.

The invention discloses an expired gas collecting and detecting device which comprises an expiration cover, the expiration cover is connected with a filter, the filter is connected with a drying device, the drying device is connected with a gas collecting device, the gas collecting device is connected with a VOCs detecting system, and an automatic gas inlet switching device is arranged between the filter and the drying device. The automatic air inlet switching device comprises an electric switching valve, an air inlet, a first air outlet and a second air outlet are formed in the electric switching valve, a carbon dioxide concentration sensor is arranged in the air inlet, and the carbon dioxide concentration sensor is connected with the control center; the automatic air inlet switching device is arranged, and air inlet collection is started based on the carbon dioxide concentration, so that the situation that dead space air at the front section of expiration is collected, and collection is started after alveolar air with the high carbon dioxide concentration enters is avoided, interference of the dead space air can be effectively eliminated, and the detection result is more real and reliable.

This application discloses a distributed monitoring method and system for internal pressure of deep-sea hoses based on fiber Bragg gratings, relating to the field of intelligent sensor technology. In this method, firstly, the raw reflectance spectrum data of the fiber Bragg grating is acquired, the center wavelength is extracted, and the drift is calculated to obtain a composite wavelength drift sequence. Secondly, a refractive index distortion correction is calculated based on the external environmental pressure to correct the wavelength, and the temperature and external water pressure components are decoupled and removed to obtain the target wavelength drift sequence. Then, a compensation factor is calculated using peak optical power for amplitude compensation to obtain a second wavelength drift sequence. Finally, the wavelength drift sub-sequences of each node are intercepted according to a preset interval, and the internal fluid pressure of each node is calculated using a pre-calibrated pressure sensitivity coefficient, thereby obtaining the distributed monitoring result. Implementing the technical solution provided in this application can improve the accuracy of monitoring the internal fluid pressure of deep-sea hoses.

This invention discloses an adaptive control method and system for automotive grille spraying parameters, relating to the field of automated spraying process control technology for automotive parts. The method includes the following steps: during each clear coat spraying process for the automotive grille, ambient temperature and humidity, as well as spraying parameters and corresponding clear coat thickness, are collected to form clear coat spraying reference data; the ambient temperature and humidity are divided into step sizes to obtain temperature and humidity grid information; parameter analysis is performed based on the clear coat spraying reference data and the temperature and humidity grid information to obtain the optimal spraying parameters corresponding to each temperature and humidity grid, thus obtaining optimal parameter reference information; the spraying parameters are adaptively controlled based on the optimal parameter reference information. This invention addresses the problem that existing spraying parameter control technologies, when controlling the gun speed and electrostatic voltage during clear coat spraying to ensure film thickness, do not comprehensively consider the coupling effect of spray booth temperature and humidity.

The application provides a turbidity extraction method and device based on remote sensing data, and belongs to the field of satellite remote sensing water quality monitoring. The method comprises the following steps: obtaining the atmosphere-corrected remote sensing data of a target sea area and the to-be-fitted turbidity values of a plurality of sampling points; screening a plurality of target remote sensing bands according to the fitting result of the single-band remote sensing reflectance data in the atmosphere-corrected remote sensing data and the to-be-fitted turbidity values; determining turbidity prediction model samples according to the fitting result of the combination of any two target remote sensing bands and the to-be-fitted turbidity values; modifying the band composition in the turbidity prediction model samples, determining a target turbidity prediction model according to the fitting result of the modified instantiated turbidity prediction model and the to-be-fitted turbidity values; and predicting the real-time turbidity of the target sea area according to the real-time remote sensing data of the target sea area and the target turbidity prediction model. The method and device provided by the application can solve the problems of insufficient single-band inversion accuracy, great influence of interference factors such as aerosols, and limited adaptability of existing models in the near-shore sea area.

This application relates to the field of metallurgical engineering technology, and in particular to an error correction system and method for infrared imaging temperature measurement in a furnace. The system's edge computing nodes are configured to: generate infrared data sequences using infrared radiation intensity data within a first time window as first data frames according to a first preset frequency; the central control server is configured to: decompose each first data frame into K eigenmode components using a variational mode decomposition algorithm; reconstruct the signals of each first data frame using the eigenmode components to obtain first radiation intensity data; convert the first radiation intensity data into preliminary temperature field data using the inverse function of Planck's blackbody radiation law; and correct the preliminary temperature field data based on dynamic compensation parameters to obtain target temperature field data and generate combustion optimization control commands for the furnace. This application utilizes variational mode decomposition and deep learning models to effectively eliminate interference such as self-radiation from optical tubes, achieving accurate compensation.

The application discloses a kind of anti-prolactin protein monoclonal antibody and its preparation method and application, comprising: C58A / C174A double mutation and PEG epitope shielding are carried out to prolactin to obtain immunogen;Pre-injection chemical cross-linking macroprolactin induces mouse immunological tolerance;Using hierarchical immunization strategy, PEG modification and unmodified prolactin mutant are combined with different adjuvants to immunize mouse in turn;High specificity hybridoma is obtained by three-channel parallel negative screening;The variable region of screening antibody is transplanted to the human IgG3 skeleton of CH2 domain, and recombination antibody is obtained.The antibody prepared by the application does not recognize macroprolactin, and can effectively exclude the interference of rheumatoid factor and heterophilic antibody due to the deletion of Fc segment CH2 domain.The prolactin detection kit established based on the antibody has a sensitivity of 0.38 ng / mL, a cross-reaction rate with macroprolactin is less than 0.1%, a signal fluctuation under RF interference is less than 3%, and a batch variation coefficient is less than 6.8%, to provide a detection means with high accuracy and high reliability for hyperprolactinemia diagnosis.