18results about How to "Implement diagnostics" patented technology

This application relates to the field of pipeline network detection technology, and discloses a visual detection method and system for pipeline network node defects based on a detection robot. The method includes: acquiring node images of a sewer network using a detection robot, and performing circle detection and sector segmentation on the node images to obtain multiple sector region blocks; extracting the block feature vector of each sector region block; calculating angular attenuation weights and radial attenuation weights, and constructing a node connection relationship matrix based on the angular attenuation weights and radial attenuation weights; combining the block feature vectors and the node connection relationship matrix to perform feature aggregation and illumination compensation to obtain a global feature vector; calculating angular deviation index, radial mutation rate index, and leakage index, and generating defect visual detection results, thereby realizing comprehensive diagnosis and spatial positioning of pipeline network node connection defects, and improving the defect detection accuracy of sewer detection robots in complex node environments.

The application discloses a strategy for extracting fault features of electronic circuit systems, named as SSEST strategy, which is used for perceiving global information and paying attention to notable local information, and mining important local information means realizing expression of intermittent fault features of electronic circuit systems, specifically, first, S transformation is performed on a circuit output time sequence signal to acquire time-frequency domain features, then a squeeze and excitation network attention module is used to distribute channel weights, subsequently, input into a Swin Transformer framework, and pay attention to local information related to faults from global signals, and deep mining is performed on fault features, and two electronic circuits are taken as experimental circuits, the proposed diagnostic strategy realizes rapid and high-precision diagnosis, and shows that the proposed multiple attention mechanism is efficient for feature mining of intermittent faults of electronic circuit systems.

This invention discloses the application of MYDGF in the prevention and treatment of memory impairment and related diseases. This invention discloses that MYDGF shows significant differences in individuals with memory impairment. After administration of MYDGF, memory impairment can be prevented and memory impairment can be prevented and the death of newly generated neurons can be stopped.

This invention belongs to the field of image processing technology, specifically relating to an online monitoring method and system for the drying morphology of instant goat milk powder. The method includes: acquiring images of the fluidized bed interior to construct a spatiotemporal fluidized image tensor; obtaining fluidization confidence using eigenvalue decomposition of the local spatiotemporal structure tensor matrix to determine the effective fluidized region; performing morphological opening operations on the effective fluidized region using a sequence of structuring elements, statistically summing gray values ​​and constructing a morphological pattern spectrum to obtain the morphological pattern spectrum entropy; obtaining the pulsating velocity vector using an optical flow algorithm, thereby obtaining the average particle pseudo-temperature and coefficient of variation; and obtaining the fluidization steady-state potential energy index based on the morphological pattern spectrum entropy, average particle pseudo-temperature, and coefficient of variation, and generating control commands. This invention achieves monitoring of complex and abnormal conditions such as the initial stage of dead bed formation and channeling through the fluidization steady-state potential energy index.

The application relates to the technical field of detection of electrified railway contact network systems, and discloses a contact network system fluorescent fingerprint intelligent analysis system, which comprises a visual unit, an emitting unit, a deflection unit, a receiving unit, a detection unit and a main control unit. The visual unit calculates relative motion parameters of insulators, drives the deflection unit to perform reverse compensation motion, so that a laser landing point remains stationary relative to a target surface within an integration time. The detection unit respectively collects parallel and vertical polarization components of Rayleigh scattering light and Stokes luminescence after spectral separation. The main control unit calculates a surface roughness factor by using the Rayleigh scattering component, carries out numerical correction on a polarization anisotropy parameter of the Stokes luminescence, eliminates the influence of geometric depolarization, and extracts fluorescent lifetime and rotation-related time characteristics. The application solves the fluorescent detection distortion problem caused by rough surfaces in a dynamic environment, and realizes multi-dimensional diagnosis of the contamination type and the substrate aging degree of the insulator surface.

The invention discloses application of serum alpha-non-red blood cell ghost protein 1 in preparation of drugs for diagnosing heart light chain amyloidosis diseases, and belongs to the technical field of biological medicines. The serum SPTAN1 protein is used for preparing the medicine for diagnosing the heart light-chain amyloidosis disease, the medicine is limited to be an enzyme linked immunosorbent assay kit, and the kit comprises an antibody of the SPTAN1 protein and further comprises a pre-coated plate, a standard substance, a coating buffer solution, a sample diluent, a confining liquid, horse radish peroxidase, an eluent and a color developing agent. The concentration of the SPTAN1 protein in the serum is measured through an enzyme linked immunosorbent assay kit, and early diagnosis of the heart AL amyloidosis disease is carried out. The invention provides a novel, efficient and sensitive biomarker, namely the serum SPTAN1 protein, early diagnosis of heart AL amyloidosis is realized by detecting the concentration of the SPTAN1 protein in serum, and the serum SPTAN1 protein has an important clinical application prospect.

The application discloses a single-exposure compressed ultrafast coherent modulation imaging device. By combining coherent modulation imaging and compressed ultrafast imaging technology, a sample to be measured is illuminated by coherent light, after the sample diffracts the light wave, the phase modulation of a random phase modulation plate is carried out, the integral intensity distribution of the modulated wave front is recorded by deflection on a detection plane by using a slit fully opened stripe camera, a single compressed diffraction pattern is obtained, a spatial two-dimensional to space-time three-dimensional image reconstruction algorithm based on a plug-and-play framework and a depth image priori is developed, and data recovery is carried out on the collected image by using the algorithm. Compared with traditional ultrafast optical imaging and phase imaging technology, the application can quantitatively obtain complete intensity and phase information of a transient scene in a single measurement process, has the characteristics of picosecond time resolution and real-time quantitative intensity-phase imaging capacity in single-exposure phase imaging, and can be widely applied to various ultrafast phenomena requiring phase observation.

The application discloses a lung-targeted nanocomposite and a preparation method and application thereof, wherein the nanocomposite comprises carbon nitride two-dimensional nanosheets and AIE photosensitizers loaded on surfaces of the carbon nitride two-dimensional nanosheets. The nanocomposite has excellent aggregation-induced emission properties and active oxygen generation capacity, can play a diagnostic role of the photosensitizer, and can produce a better tumor elimination effect, so that the diagnosis and treatment of lung cancer can be simultaneously realized. In addition, the nanocomposite has a suitable size, can enhance the retention of drugs in the lung, prolong the treatment time, and reduce the administration frequency; the nanocomposite can also be administered through tracheal spray, has the advantages of rapid onset, high local drug concentration, small drug dosage, convenient use, less systemic adverse reactions, easy monitoring and adjustment of the dosage, and the like.

This invention discloses a multimodal gearbox fault diagnosis method based on deep transfer learning, addressing the problem of poor gearbox fault diagnosis capability under unlabeled sample conditions, belonging to the field of gearbox fault diagnosis technology. The method includes: collecting raw vibration signals under different operating conditions, defining them as source and target domains; fusing multimodal information in the time and frequency domains using a data-level fusion method and dividing the collected signals into samples; constructing a deep multimodal adversarial transfer network model, extracting fault information features from the source and target domains through iterative adversarial training to adapt to the joint probability distribution of the source and target domains, and utilizing the abundant fault label information in the source domain to ensure accurate fault category discrimination; finally, obtaining a trained transfer diagnosis model for the target domain. This method is applicable to gearbox fault diagnosis under different operating conditions, i.e., transfer diagnosis between different operating conditions or different fault types, exhibiting high accuracy and good generalization performance.

The application discloses a kind of optical current transformer key component state detection method and system, method includes: the CRS t Statistics and its statistical threshold value CRS c , carry out online self-detection;Establish the time series of the CRS t Statistics of representing the overall error state of three optical current transformers under the same node, calculate the fractal dimension of the time series, when the overall error state of three optical current transformers under the same node appears abnormal, according to the difference of fractal dimension, judge the degradation form of the overall error state of three optical current transformers under the same node;According to the degradation form, combine fault tree model, the abnormal influence source of optical current transformer measurement error is inversed, and the autonomous identification of optical current transformer fault position is realized;The application has the advantages that: method accurately deduces the abnormal influence source of optical current transformer measurement error, avoids security risks.

This invention provides a method for measuring the physical symmetry of an optical fiber sensing ring, belonging to the fields of optical measurement and optical fiber sensing technology. The method includes: using polarization-maintaining OFDR and multi-parameter decoupling technology to measure the temperature change and thermal strain of the optical fiber ring at different temperatures; calculating the asymmetric refractive index distribution under temperature changes, and then calculating the correlation coefficient of a single layer / turn unit to evaluate the physical symmetry of that unit; accumulating the correlation coefficients of all units to obtain the equivalent correlation coefficient, and calculating the full-temperature equivalent correlation coefficient distribution at all temperature points to achieve the evaluation of physical symmetry. This invention can achieve quantitative evaluation of physical symmetry. Combined with high spatial resolution data, it can provide in-depth evaluation of the physical symmetry between optical fiber layers and turns, diagnose physical symmetry faults in optical fiber rings, and plays an important role in optimizing the winding process, quality evaluation, and improving the yield of optical fiber rings.

The invention discloses a comprehensive leveling device and method applied to 3D printing, and relates to the technical field of 3D printing equipment. The comprehensive leveling device comprises a base plate and a printing platform assembled with the base plate; the high-precision leveling supporting legs are assembled between the printing platform and the base plate; and the multi-site sensing array assembly is arranged on one side of the substrate. A local, open-loop and experience-dependent leveling process is converted into a multi-site, closed-loop and data-driven automatic precision calibration process, in the process, a multi-site sensing array assembly provides a reliable data basis for precision calibration, and high-precision leveling supporting legs finely level a printing platform based on the data, so that the printing precision is greatly improved. And it is ensured that the distance from the 3D nozzle to the printing platform is highly consistent in the whole printing area, and uniform extrusion and firm adhesion of first-layer lines are guaranteed.

This invention discloses a time-series graph modeling method and apparatus that integrates multi-parameter data analysis. The method includes: acquiring multi-source information from a converter transformer, including operating condition data and multi-source sensor data; transforming the multi-source information into corresponding semantic feature vectors using a word vector model; performing linear transformations on each semantic feature vector and the concatenated feature vector obtained by splicing the semantic features to transform the multi-source information into a common feature space; processing the feature values ​​of each semantic feature vector after linear transformation using a knowledge graph technology based on the adaptive change of adjacency matrix weights with node features to obtain a knowledge graph corresponding to the multi-source information at different times; and processing the knowledge graph corresponding to the multi-source information at different times using a time-series graph attention neural network to analyze the changing patterns of the multi-source information.

The invention relates to the technical field of wide and thick plate rolling, in particular to a method for correcting the rigidity of a rolling mill and controlling the plate shape, which comprises the following steps of: acquiring rolling force values calculated in the last but one pass and the last but one pass, roll gap calculated values, actually measured rolling force values and actually measured roll gap values; calculating a pre-calculated rigidity value and an actually measured rigidity value; calculating a rolling mill rigidity deviation judgment coefficient; if the rolling mill rigidity deviation judgment coefficient exists, the rigidity compensation adjustment coefficient is corrected, and rolling force calculation is executed based on the corrected rigidity compensation adjustment coefficient; otherwise, calculation is executed according to the set rolling force. The method has the advantages that through real-time monitoring and deviation compensation of the rigidity of the rolling mill, plate shape fluctuation caused by equipment aging or working condition changes is effectively reduced; the rolling force deviation of the last pass is stably controlled within 60 tons, and the plate shape qualification rate is increased; and by introducing a rigidity fluctuation identification and compensation mechanism, instability factors in the rolling process are reduced.

The application provides an FAPI-CXCR4 compound and a preparation method and application thereof, and belongs to the technical field of medicines.The API-CXCR4 compound has the structure shown in the following formula.The FAPI-CXCR4 compound prepared in the application can be combined with different radionuclides, realizes integration of diagnosis and treatment, overcomes the problem that the effect of a traditional single-target imaging agent or treatment method can be limited due to insufficient target expression, and improves the accuracy and effectiveness of diagnosis and treatment.

The application screens a group of DNA aptamers capable of specifically recognizing mCRP through SELEX technology. Compared with RNA aptamers, the DNA aptamers have the advantages of low cost, in-vivo stability and difficulty in degradation, and are more suitable for in-vivo application. The DNA aptamers capable of specifically recognizing mCRP can be used for capturing mCRP from a complex system, realizing detection, purification, in-vivo imaging and diagnosis, drug delivery and the like of mCRP. Further, the DNA aptamers in the group can block the pathological function of mCRP, and are further used for treating CRP-related diseases.

The invention discloses a self-checking method and device for camera hardware of an automatic driving vehicle, and the method comprises the following steps: obtaining a plurality of pieces of synchronous image data collected by a plurality of cameras on the vehicle, the plurality of cameras on the vehicle at least comprising a vehicle front-view camera, a vehicle side-view camera and a vehicle rear-view camera; and preprocessing the plurality of pieces of synchronous image data. And inputting the plurality of pieces of preprocessed synchronous image data into a preset perception model to extract corresponding image features. And based on the synchronous image data and the image features, executing a hardware anomaly detection strategy to obtain a plurality of anomaly detection results. And outputting a self-inspection diagnosis result of the camera hardware according to the plurality of anomaly detection results. According to the invention, automatic, multi-type and combined self-check diagnosis of the abnormal state of the camera hardware is realized, and the problems of low manual detection efficiency, insufficient real-time performance and limited abnormal detection in the prior art are effectively solved.

This invention discloses a numerical simulation-driven method for deep migration fault diagnosis of inter-turn short circuits in motors, belonging to the field of fault diagnosis technology. The method includes the following steps: constructing a simulation model of inter-turn short circuit faults in the motor stator; constructing a parameter migration diagnostic network and a feature migration diagnostic network; obtaining fault classification results based on the simulation model and the parameter migration diagnostic model to complete fault diagnosis; and obtaining further fault classification results based on the simulation model and the feature migration diagnostic model to complete fault diagnosis. This invention introduces a simulation model of inter-turn short circuit faults in the motor stator and utilizes the simulation data generated by the simulation model, combined with the parameter migration diagnostic network and the feature migration diagnostic network, to achieve diagnosis of the degree of inter-turn short circuit faults in motors when there are few or no actual fault samples.