23results about How to "Improve guidance" patented technology

The embodiment of the present invention discloses a data processing method, device, equipment and storage medium based on sentiment analysis, the method comprising: obtaining financial field review text data of a target date; inputting the financial field review text data into a hybrid neural network to obtain sentiment analysis results of the financial field review text data of the target date; generating financial market trend data of a target associated date according to the sentiment analysis results of the financial field review text data of the target date. The technical solution of the embodiment of the present invention can realize the automatic analysis and processing of financial field sentiment data, improve the accuracy and efficiency of the analysis and processing of financial field sentiment data, and thus improve the guidance and applicability of financial field sentiment data.

The invention discloses an English teaching writing error diagnosis method based on artificial intelligence, and relates to the technical field of artificial intelligence, and the method comprises the following steps: obtaining an English composition text, and obtaining initial writing data; performing grammatical structure analysis according to the initial writing data to obtain grammatical features; performing vocabulary error analysis according to the grammatical features to obtain vocabulary errors; performing syntactic and semantic consistency analysis according to the vocabulary errors to obtain syntactic and semantic errors; performing article logic analysis according to the syntactic and semantic errors to obtain article logic errors; and performing comprehensive diagnosis according to the article logic error to obtain a diagnosis result. According to the method, the conjunction matching degree and the semantic compatibility are combined, cross-sentence logic analysis is achieved, misjudgment of isolated sentences is avoided, a complete error set is formed, the comprehensiveness and accuracy of diagnosis are improved, and practicability and guidance are enhanced.

The utility model discloses a transformer hoisting device mainly relates to the power station equipment installation technical field. Including the beam, the both ends of beam top side are equipped with the upper lifting hole respectively, the upper lifting hole is hung with the lifting cable, the both ends of beam bottom side are equipped with the lower lifting hole respectively, the lower lifting hole is hung with the lifting belt or the lifting cable, the both ends of beam are equipped with the length direction same direction extension's rebates respectively, the rebates are hinged with the swing arm, the inner end of swing arm is located in the rebates and the outer end of swing arm exceeds the both ends of beam, the outer end rotatable mounting of swing arm has the vertical guide pulley of axial, be equipped with the elastic element between swing arm and rebates, the elastic element makes swing arm keep with beam and keep static same direction, and when swing arm swings, the elastic element has the elastic force of making swing arm reset for with beam same direction. The utility model has the beneficial effect at in narrow space to the hoisting path can be in the middle direction, prevents and twists and turns and hangs the partiality.

The present application relates to the technical field of intelligent construction control, in particular to a beam segment hoisting assembly precision detection method and system based on improved machine vision, comprising the following steps: a visual guidance zone extending along the joint is formed in advance at the assembly interface of the to-be-hoisted beam segment and the butt joint beam segment, and a joint mark with a direction recognition relationship is arranged in the visual guidance zone; during the process of the to-be-hoisted beam segment approaching the butt joint beam segment, the visual guidance zone is continuously imaged, and according to the changes of the joint mark in the continuous images, the changes of the joint mark in the continuous images, and the changes of the relative pointing direction, the joint evolution result of the corresponding assembly interface is generated. The present application realizes explicit mapping of the gap, height difference and lateral misalignment, breaks through the instability of traditional machine vision relying on natural edge recognition, and improves the accuracy and robustness of joint state recognition in complex construction environment.

The invention discloses a drilling process state monitoring method based on interval information granulation, and relates to the technical field of geological drilling engineering.The drilling process state monitoring method based on interval information granulation mainly comprises the steps that original drilling process data is preprocessed to obtain a drilling data time sequence; performing multi-interval information granulation on the drilling data time sequence to obtain a low-dimension time sequence; according to the low-dimension time sequence, a drilling operation state monitoring model is obtained through a principal component analysis method with a kernel function; and monitoring the drilling operation state by using the drilling operation state monitoring model. According to the drilling process state monitoring method based on interval information granulation, the operation state of the drilling system can be finely monitored and sensitively sensed.

The application relates to a strip steel surface defect tracing method, system, device and medium. The method comprises the following steps: performing defect recognition on a strip steel surface defect image to obtain a defect type, a geometric feature vector and a texture feature vector, acquiring spatial coordinates and a timestamp corresponding to the image, and constructing a defect feature matrix; constructing a process knowledge graph based on production line equipment parameters, a theoretical speed curve, equipment topological relations, real-time working condition data and historical event records; performing candidate equipment positioning in the process knowledge graph by adopting a periodic matching strategy or a non-periodic matching strategy to generate a matching result set; acquiring an equipment health index from the process knowledge graph, calculating a final confidence and a comprehensive score based on matching parameters in the matching result set, and generating a tracing report. The method integrates multi-dimensional defect features and constructs a process knowledge graph, optimizes a defect and equipment matching strategy, and improves the accuracy and reliability of strip steel surface defect tracing.

The present application relates to a semantic chain feedback and reinforcement learning driven image fusion method, belonging to the technical field of computer vision and image processing. It includes: inputting the preprocessed input image into the frozen dual-path hierarchical encoder, extracting multi-scale visual features and shallow prior features in the prior injection branch; on each intermediate scale, cross-modal collaborative fusion is performed on the infrared features, visible light features, the last layer propagation features and shallow prior features in the multi-scale visual features; chain semantic enhancement is performed on the multi-scale fusion features: obtaining several candidate fusion images; optimizing the unfrozen model parameters; inputting the infrared image and visible light image to be processed into the optimized network, and selecting the noise-free reference candidate as the final fusion image output. This method cooperatively optimizes through chain semantic progressive modulation and difference driven reinforcement learning, improving the visual quality and information expression ability of the fusion image.

The application discloses a kind of engineering cost auditing method and system based on multi-source data fusion.Belongs to the field of engineering cost auditing, the present application obtains the engineering quantity list of the engineering to be audited, construction site space-time image and construction log text data, input model trained by multi-modal data, generates cost declaration and physical live characteristic vector, then calculates correlation score and extracts empirical segment features, and with cost declaration features fusion generates semantic fusion feature matrix;Finally, identify sub-item engineering category, calculate its Mahalanobis distance with process feature prototype vector, if exceed threshold value, then determine abnormal, generate the audit result containing abnormal cost item and construction period lack of empirical information.The present application effectively solves the problem that existing technology cannot accurately and efficiently audit engineering cost.

The invention discloses a meat freshness rapid detection device, and belongs to the technical field of food nondestructive detection. The device aims at solving the problems that existing detection equipment is poor in portability and difficult to use on site, the detection range is limited due to single excitation wavelength, and the detection process depends on manual operation and is insufficient in intelligence. According to the technical scheme, the device is characterized by comprising a sample placement area, an annular multi-wavelength excitation light source module, a spectrum acquisition module, a single-chip microcomputer module, a Bluetooth module and a power supply and discharge module which are integrated in a device shell; the external intelligent terminal is provided with detection analysis software, and the software controls the excitation of the LED lamp beads with specific wavelengths through the Bluetooth module, automatically identifies the type of the freshness indication label based on the collected spectral characteristics, and calls a corresponding prediction model to calculate the freshness index. The device is mainly used for carrying out rapid and portable on-site detection on meat samples with freshness indication labels.

This utility model relates to the field of blood specimen preservation technology, and in particular to a blood specimen preservation box, including a box body. The box body has multiple insertion holes evenly distributed on it for placing blood collection tubes. Each insertion hole is a conical hole, wider at the top and narrower at the bottom. A pair of sponge wheels are symmetrically arranged along the diameter of each insertion hole on its inner wall. This utility model's blood specimen preservation box features conical insertion holes, which retain the advantage of traditional larger insertion holes for easier insertion of blood collection tubes. During blood collection, medical personnel can easily align and insert the blood collection tube into the insertion hole. The larger opening at the top provides significant guidance, reducing the difficulty of insertion and improving blood collection efficiency. When inserting the blood collection tube, the sponge wheels rub against the outer wall of the tube, making insertion smoother. After insertion, the sponge wheels are in close contact with the outer wall of the blood collection tube, providing a clamping function and, together with the bottom of the conical hole, limiting the movement of the blood collection tube within the insertion hole.

The invention discloses a Transform encoder model generation method for a terahertz metamaterial sensor and the sensor, and the method comprises the steps: enabling obtained training data to generate a plurality of groups of data samples through electromagnetic simulation software; carrying out abnormal value elimination and standardization processing on the multiple groups of data samples to obtain a training data set; the method comprises the following steps: constructing a Transform encoder model; dividing the training data set into a training set and a test set according to a preset proportion; based on the training set, a mean square error is used as a loss function, and a Transform encoder model is optimized through a back propagation algorithm; and based on the mean square error on the test set, determining the dimensionality of the feature vector output by the input embedding layer, the number of subspaces of the multi-head self-attention layer, the learning rate and the optimal value of the batch size, and obtaining an optimized Transformer encoder model for terahertz metamaterial sensor design. The method is used for improving the accuracy of a model prediction result, so that the performance of the sensor is improved.

This utility model provides a traction device, including: a frame, a traction seat, and a locking rod. The frame is movably arranged along a preset trajectory. The traction seat is installed on the top of the frame and is located on the side of the frame closer to the drying oven. The traction seat has an insertion slot that extends along the length of the frame. The insertion slot is for the insertion and engagement of traction fittings on the placement frame. The locking rod extends along the width of the frame and is movably inserted into the traction seat along the width of the frame. The side wall of the insertion end of the locking rod has a guide slope, and the locking rod has an initial state, a clearance state, and a locked state. When the traction seat is away from the placement frame, the insertion end of the locking rod is located in the insertion slot, and the locking rod is in the initial state. This traction device effectively solves the technical problem in the prior art where, after the profile has been dried, the operator needs to enter the high-temperature drying space to manually push out the placement frame.

The invention discloses a design evaluation method of a lithium ion battery, and belongs to the technical field of lithium ion batteries. Comprising the steps of determining pole piece design parameters; calculating a material characteristic coefficient according to the material system; calculating a tab position factor according to the tab position coordinates; testing the resistance of the diaphragm; calculating an evaluation coefficient; and performing multi-stage evaluation judgment and outputting optimization suggestions. According to the method, the geometric dimension of the pole piece, the resistance of the diaphragm, the material characteristics, the tab design and the tab position are comprehensively considered, the battery design scheme is comprehensively and quantitatively evaluated, whether the design scheme meets the energy efficiency requirement or not can be quickly judged, the development period is effectively shortened, and the development cost is reduced.

The application relates to the field of health monitoring, and discloses a hand pollution evaluation method and system fusing multi-modal images and a storage medium. The method comprises the following steps: synchronously collecting hand visible light, fluorescence and thermal imaging data and carrying out denoising processing; extracting a hand contour and a fluorescence intensity distribution, and generating an initial pollution distribution feature map; calculating a pollution concentration gradient and classifying the pollution intensity of a hand region; spatially registering and weighting fusing the thermal imaging data and the fluorescence intensity, and obtaining a temperature-weighted pollution distribution map; correcting and normalizing the high-temperature area pollution proportion; combining the pollution degree distribution result to carry out temperature-dependent diffusion simulation and spatial mapping, and generating a hand pollution comprehensive distribution map; and carrying out regional comparative analysis based on the map and generating an evaluation report. The application solves the problems of insufficient accuracy and inability to reflect dynamic risks when a single imaging mode is used to evaluate hand pollution, and improves the comprehensiveness and accuracy of evaluation.

The present application discloses a method for predicting the casting depth of metal-based composite materials prepared by the casting infiltration method, and relates to the field of material forming technology. The casting depth prediction method includes: determining the initial casting temperature at which the molten metal starts to infiltrate into the porous preform and the final casting temperature at which the molten metal stops infiltrating into the porous preform; calculating the heat loss of the molten metal in the process of infiltrating into the porous preform according to the initial casting temperature and the final casting temperature; calculating the casting time of the molten metal according to the heat loss of the molten metal; calculating the theoretical casting depth of the molten metal in the porous preform according to the casting time and the casting speed of the molten metal. The casting depth prediction method provided in the embodiment of the present application can effectively predict the theoretical casting depth of the metal-based composite materials prepared by the casting infiltration method, and the obtained theoretical casting depth has a good evaluation and guiding role in the casting process.

The application discloses a kind of extra-fine nickel-chromium electrothermal alloy wire stretch control device, including shell and several detachable assembly in shell control wire guide pipe, shell is made of upper shell and lower shell joint combination, upper shell and lower shell are opened with multiple assembly slots in width direction, control wire guide pipe snap fits in assembly slot, control wire guide pipe adopts hollow cylinder structure, both ends of control wire guide pipe are all adopted by gradually smaller caliber from outside to inside flared mouth structure.The application is suitable for nickel-chromium electrothermal alloy wire production, the control wire guide pipe in the device is detachably connected, such structure setting makes that control wire guide pipe can be replaced according to actual needs adjustment, improves the applicability of the device, and the guiding effect of the guide control device of such guide pipe structure is excellent, meanwhile, nickel-chromium electrothermal alloy wire of control wire guide pipe does not appear transverse movement, and it is not easy to produce the condition of fracture.

The application discloses an industrial sensor data anomaly detection and repair method based on an attention mechanism, belongs to the technical field of industrial data processing, and carries out preprocessing on original data to obtain standardized data segments, a training set and a test set; end-to-end collaborative training is carried out on the training set to obtain a dynamic space-time attention detection model and a multi-scale self-attention repair model; the standardized data segments are input into the dynamic space-time attention detection model for anomaly detection to obtain abnormal related information; the standardized data segments and the abnormal related information are input into the multi-scale self-attention repair model for data repair to obtain repaired data; secondary verification and parameter fine-tuning operations are performed on the repaired data to obtain compliant repair data; and the POT algorithm is used to dynamically adjust an abnormality judgment threshold value, and normal industrial sensor data or compliant repair data is output. By using the above method, accurate detection and compliant repair of industrial sensor data anomalies are realized.

This invention provides a method for interpreting conventional well tests in complex reservoirs. The method includes considering permeability variations near the wellbore in a complex region, analyzing pressure recovery curves, calculating the flow coefficient based on shut-in time and bottom-hole pressure in each zone, analyzing the variation trend of reservoir properties around the well based on changes in the flow coefficient, calculating reservoir permeability at different time intervals, amplifying the time interval data to observe the relationship between reservoir properties and time intervals, and obtaining the wellbore reservoir coefficient based on the pressure recovery theory, considering the changes in bottom-hole pressure over time based on shut-in time and time. The method also calculates the pressure recovery rise value based on the wellbore reservoir coefficient and when the test data time intervals are the same. This invention is suitable for reservoirs with water injection, polymer injection, alternating gas and water injection, wellbore contamination, or improved permeability near the wellbore, and is also applicable to the interpretation of well test data from reservoirs with varying rock properties.

The invention relates to the technical field of material processing, in particular to a preparation method of low-temperature-resistant flat steel with a refined grain structure, which comprises the following steps: firstly, acquiring alloy components of a steel billet, specification parameters of the steel billet and corresponding process parameters and material properties; constructing a process optimization model according to the data; then target material performance is determined according to process requirements, the model automatically analyzes stored empirical data according to the target material performance, and optimal alloy components, specification parameters and corresponding process parameters are recommended; then, respectively weighing all alloy elements according to a design ratio recommended by the model, smelting, refining, and continuously casting to form a steel billet; finally, the steel billet is cut into corresponding specifications, technological parameters are adjusted according to the specifications of the steel billet, and corresponding deformation quantity and temperature are controlled for multiple times of rolling; and after finish rolling is completed, laminar cooling is conducted, heat preservation is conducted when the flat steel is cooled to the set temperature, the flat steel is gradually converted into ferrite and pearlite, then the flat steel is cooled to the room temperature, and the grain-refined low-temperature-resistant flat steel is obtained.

The present application belongs to the field of coal consumption evaluation, and discloses a coal consumption evaluation method and system for power supply and heat supply of a coal-fired thermal power unit. The present application breaks through the limitation of the prior art that mainly relies on a small number of thermal parameters and single input dimension by acquiring multi-source real-time data of the coal-fired thermal power unit in real time, pre-processing and feature extraction to construct a multi-dimensional operating state feature vector, and can more comprehensively and accurately reflect the real coal consumption state of the unit under complex variable operating conditions, providing a more reliable data basis for subsequent evaluation. The present application can calculate the consumption difference influence index of each feature parameter on the power supply coal consumption change and the heat supply coal consumption change, and screen a key consumption difference feature set by respectively establishing a power supply coal consumption benchmark model and a heat supply coal consumption benchmark model under variable operating conditions, so as to quantify the influence degree of different feature parameters on the two types of coal consumption changes, thereby improving the pertinence and precision of coal consumption evaluation.

The utility model provides a sealing structure of a gear shaft of a gear box, which comprises a shaft sleeve arranged at the extending end of the gear shaft, an oil storage cavity is arranged in the shaft sleeve, the bottom of the shaft sleeve is connected with an oil return pipe and communicated with an oil return port on a box seat through a hose, and leaked lubricating oil is recycled. A sealing ring and a felt ring are arranged at one end of the shaft sleeve to form primary and secondary sealing defense lines to prevent lubricating oil from leaking along the shaft; a sliding ejector rod is arranged on one side of the shaft sleeve, an arc-shaped oil scraping plate is fixed to the end of the ejector rod, and the oil scraping plate is attached to the surface of the gear shaft and can scrape attached lubricating oil into the oil storage cavity. The ejector rod is sleeved with a spring, and pre-tightening force is provided to guarantee that the oil scraping plate is attached to the gear shaft all the time. Through multiple sealing, active oil scraping and lubricating oil recycling mechanisms, the sealing reliability is effectively improved, the risk of lubricating oil leakage is reduced, and the shaft end sealing device has the advantages of being compact in structure, convenient to maintain, environmentally friendly, capable of saving energy and the like and is suitable for shaft end sealing application of various industrial gearboxes.

The application provides a method and device for identifying a fractured-vug reservoir type, a computer readable storage medium and an electronic device. The method comprises determining a lithology type of a reservoir in a study area and a reservoir type of the reservoir; analyzing reservoir porosity of the study area; obtaining conventional well logging curves of the study area, and determining sensitive well logging curves and sensitive well logging response characteristics that can be used to identify the reservoir type of the study area based on the conventional well logging curves; establishing identification criteria for different types of reservoirs based on the porosity of different types of reservoirs, the difference in the overlapping amplitude of the sensitive well logging curves and the values of the sensitive well logging response characteristics; and identifying and dividing the reservoir type of the study area by using the identification criteria for different types of reservoirs. The identification criteria for the reservoir type established by the application can accurately and intuitively identify different types of reservoirs, and can greatly improve the accuracy of well logging technology in identifying fractured-vug reservoirs, thereby guiding the exploration and development of oilfields.

The invention discloses a short-stress rolling mill rolling force calculation method based on thermosetting coupling simulation. The method comprises the following steps that 1, an existing short-stress rolling mill model is simplified and then imported into engineering simulation software; 2, dynamic analysis of the rolling process is conducted through explicit dynamics of engineering simulation software; 3, the Sims hot rolling formula is adjusted by combining the contact area of the roller and the rolled piece in the simulation result, and the rolling force load is obtained through calculation; and 4, comparing the rolling force average value obtained by simulation with the rolling force obtained by theoretical calculation, and verifying the accuracy of a simulation result. According to the invention, the Johnson-Cook constitutive model is utilized to simulate the stress and strain of the rolled piece, so that the simulation result is more in line with the actual situation.