16results about How to "Compensation accuracy" patented technology

The invention discloses a retrieval sample selection and multi-round error correction method for solving a mathematical problem of a large language model. The retrieval sample selection and multi-round error correction method comprises the following steps: S1, constructing a retrieval sample library; s2, a mathematical character problem is given, cue words and a plurality of fixed samples for successfully solving the problem are used as input, and the large language model is guided to generate an initial thinking chain and Python codes; s3, the generated initial Python code is submitted to a Python interpreter to be executed; s4, if the initial Python code is successfully executed, ending the process, and taking an execution result as a final answer; s5, if the execution of the initial Python code fails, selecting a retrieval sample from a pre-constructed retrieval sample library according to the error type and the problem semantic similarity returned by the Python interpreter; s6, taking the selected retrieval sample and the original mathematical character problem in the step S2 as new input, submitting the new input to the large language model again, and carrying out the next round of thinking chain and code generation; and S7, repeating the steps S2-S5 until the program runs normally or the preset maximum number of attempts is reached.

The invention discloses a multi-pointer meter reading identification method based on a traditional algorithm and deep learning, and relates to the technical field of industrial monitoring, and the method comprises the steps: 1, setting the configuration of an image collection device, collecting a meter image according to the configuration of the image collection device, and carrying out the calibration, and obtaining calibration information and a reference image; step 2, acquiring a to-be-identified meter image, and performing search matching on the to-be-identified meter image according to the reference image by adopting a template matching strategy to obtain a target meter ROI (Region of Interest); 3, identifying all pointer positions in the ROI of the target meter by adopting a Canny edge detection algorithm, a Hough straight line detection algorithm, a straight line filtering method and a deep learning algorithm according to the calibration information, and obtaining a final effective straight line set; and step 4, calculating the meter reading according to the calibration information and the final effective straight line set. According to the method, accurate identification of the pointer meter can be realized, and the robustness problem and the performance problem in a current meter identification algorithm are optimized.

The invention relates to the technical field of power distribution system control, in particular to a transformer area voltage compensation control method and system considering distributed power supply fluctuation. Constructing an electric energy quality influence coefficient of each grid-connected point in each time period according to the three-phase voltage and a difference condition among positive-sequence, negative-sequence and zero-sequence components obtained by three-phase voltage decomposition, and calculating a comprehensive disturbance coefficient of a low-voltage transformer area in each time period by combining voltage difference and voltage change trend synchronism among different grid-connected points; the distribution difference and the coupling influence relation between the grid-connected points are comprehensively considered, and the influence characteristics of the fluctuation of the distributed power supply can be evaluated more accurately; the gain coefficient in the sliding mode controller is optimized based on the obtained comprehensive disturbance coefficient, and the adjusted controller is adopted to carry out transformer area voltage compensation control, so that the defect that the transformer area voltage compensation precision and reliability are insufficient can be overcome.

The utility model relates to a numerical control rotary table surface sealing structure, which belongs to the technical field of numerical control rotary tables and comprises a rotary table body and a rotary table surface arranged on the rotary table body, at least one U-shaped ring groove is arranged on the side wall of the rotary table body, the U-shaped ring groove and the rotary table surface form a labyrinth sealing structure, and a drainage ring groove is arranged on the upper end face of the rotary table body. A drainage ring groove is formed in the rotary table body, a first drainage channel is formed in the drainage ring groove, a second drainage channel communicated with the lower end of the first drainage channel is formed in the rotary table body, and the other end of the second drainage channel extends to the side wall of the rotary table body and is connected with an air pipe connector. Meanwhile, the drainage ring groove is additionally formed in the end face, liquid such as cooling liquid or cutting liquid generated in the working process can be rapidly drained out, the situation that internal parts such as a bearing and an end-toothed disc are rusted and precision is reduced due to liquid accumulation is prevented, and the defect that labyrinth sealing cannot completely prevent water vapor leakage is overcome.

The invention discloses a method for reconstructing human body geometry and material based on a sparse flash image, and the method comprises the steps: firstly constructing and pre-training a geometric material prediction network which comprises an image feature extraction network, a geometric prediction network and a material prediction network; then, a flash image of a target person is shot, light rays are emitted from random pixels of each view angle, intersection points of the light rays and a scene are obtained by using a spherical tracking algorithm and a pre-trained geometric prediction network, and materials of the intersection points are obtained by using a pre-trained material prediction network; and based on the geometric and material attributes of the intersection points, the colors of the intersection points are calculated by using physics-based differentiable rendering, and the geometric material prediction network is further optimized by taking the color close to the actual pixel color as a target. And finally, extracting geometry and materials of the human body model by using the optimized network. According to the method, high-quality human body digital assets capable of being re-illuminated can be obtained in a relatively short time only by using the multi-view flash images and the camera pose information shot by the consumer-level equipment under dark light.

The invention relates to the technical field of spacecraft leakage detection, in particular to a leakage rate detection system and method for a gas-liquid two-phase working medium, the leakage rate detection system comprises a vacuum container, a gas sensor and a control device, the gas sensor is arranged in the vacuum container, and the control device is arranged in the vacuum container. The gas sensor comprises a gas sensitive element used for adsorbing leakage gas of the product to be detected and changing the resistance value of the gas sensor and a detection element used for collecting the value of current passing through the gas sensor; and the control device calculates the leakage rate of the leaked gas of the to-be-detected product. According to the leak rate detection system, the gas sensor adsorbs the leaked gas of the to-be-detected product, and the leak rate of the leaked gas of the to-be-detected product is calculated, so that the leak rate detection method is simplified, the defects of precision and sensitivity of actual work quality leakage detection are overcome, accurate quantitative analysis is realized, the cost of a spacecraft development stage is reduced, and the detection efficiency is improved. And the efficiency and the reliability of gas-liquid two-phase work quality leakage detection are improved.

The invention relates to the technical field of ship intrusion detection, in particular to a ship intrusion detection method and system, intelligent identification and authorization management of ship identity are realized by introducing a dynamic white list mechanism and combining with an electronic fence technology, legal passage and illegal intrusion are fundamentally distinguished, and the false alarm rate is reduced to an extremely low level. Meanwhile, a multi-source data fusion technology is adopted, so that the accuracy and reliability of ship positioning and identification are improved; through multi-dimensional automatic verification and risk assessment, manual intervention is greatly reduced, and the detection efficiency is improved; and an automatic alarm and linkage response mechanism can realize rapid emergency processing, so that the safety monitoring capability and the security response level of key water areas are remarkably improved.

The invention provides an unmanned aerial vehicle target positioning method and device based on cooperation of multiple observation points and a medium, and the method comprises the steps: building a dynamic and static target three-dimensional space positioning physical architecture, and building an unmanned aerial vehicle target recognition model based on bidirectional cross-dimension feature enhancement; an image-based unmanned aerial vehicle multi-target association matching algorithm is proposed to eliminate background interference and correct view angle influence, and an end-to-end deep neural network is adopted to model a mapping relationship between multiple observation points and unmanned aerial vehicle targets, so that multi-source feature fusion and positioning precision improvement are realized; according to the technology, the problems of poor recognition robustness, low positioning precision and the like caused by small target information loss, view angle transformation interference and optical sensor measurement deviation in the actual unmanned aerial vehicle target positioning process are solved, and efficient and reliable unmanned aerial vehicle target positioning technical support is provided for airspace monitoring, unmanned aerial vehicle compliance management, security patrol and other scenes.

The utility model provides an intelligent quality detection device for welding, which relates to the field of intelligent quality detection equipment for welding and comprises a detection platform, a base for lifting the detection platform, a protective cover fixed at the top of the base, a fixing mechanism and a three-jaw chuck for fixing a workpiece, the detection unit comprises a PLC (Programmable Logic Controller) fixed on the surface of the base and a display screen fixed on one side of the protective cover; the visual detection assembly and the three-dimensional detection assembly are combined, a CCD camera in the visual detection assembly can shoot images to obtain plane visual information of a welding part, a line laser scanner in the three-dimensional detection assembly can obtain three-dimensional contour information of the welding part, and the visual detection assembly and the three-dimensional detection assembly work cooperatively to achieve the effect of detecting the welding part. The defects of a single detection mode are overcome, the problems that a stereo camera is low in resolution and insufficient in precision are effectively solved, and therefore the welding quality detection precision is improved.

The application discloses a transmission knock noise suppression method and device of a hybrid power system. The method comprises the following steps: obtaining an engine torque of an engine in the hybrid power system; determining a current operating condition of the hybrid power system under the engine torque; determining whether the current operating condition belongs to a predetermined operating condition to obtain an operating condition determination result; in the case that the operating condition determination result is that the current operating condition belongs to the predetermined operating condition, determining a rotational speed difference of a clutch; and suppressing the knock noise of the transmission by controlling the rotational speed difference of the clutch within a predetermined range. The application solves the technical problem that the knock noise of the transmission caused by the large torsional vibration transmitted from the engine to the transmission cannot be effectively suppressed in the prior art.

The invention discloses a T / R assembly amplitude phase compensation code determination method and device and a storage medium, and the method comprises the steps: determining an amplitude compensation code based on the amplitude and phase correction of a receiving channel and a set minimum attenuation stepping amount, and determining a phase compensation code according to the amplitude compensation code; correcting the initial phase and amplitude of each antenna unit based on the phase compensation code and the amplitude compensation code, and sending a signal based on the corrected initial phase and amplitude; and performing wave beam electric scanning based on the correction amplitude and the correction phase, judging whether the signal level output by the total port of the phased-array antenna forms a curve of an antenna pattern shape, determining that the amplitude and phase compensation codes are correct during formation, and determining that the phase compensation codes are not correct when the amplitude and phase compensation codes cannot be formed. And returning to the step of determining the amplitude compensation code based on the amplitude and phase correction amount of the receiving channel and the set minimum attenuation stepping amount until a curve of an antenna pattern shape can be formed. And the precision of the T / R assembly can be effectively compensated by using the optimal compensation code.

This invention discloses a method and system for enhancing the accuracy of downhole target positioning based on the Internet of Things (IoT). The method includes: a terminal collecting target positioning-related data in real time to determine the target location and calculating the target displacement; recording the target displacement within a set time period as a continuous displacement sequence; calculating the error evaluation result of the current target displacement based on the continuous displacement sequence; when the error evaluation result exceeds a set error threshold, determining the surrounding positioning devices based on a set effective radius of the positioning device; each surrounding positioning device collecting target positioning-related data and transmitting it to the terminal via the IoT; the terminal using the target positioning-related data to determine multiple target locations; dividing all target locations into multiple clusters based on a K-means clustering algorithm; calculating the clustering rationality coefficient based on the center point of each cluster; and using the center point of the cluster with the largest clustering rationality coefficient as the current target location. This invention has significant advantages such as accurate positioning and high reliability.

The invention provides a street space vitality prediction method based on deep learning, relates to the technical field of regional people flow prediction, aims to effectively combine fitting and deep learning to realize defect complementation, and comprises the following steps: dividing a year into N periodic sub-modules, respectively establishing a fitting model for estimating the pedestrian flow of the street for each periodic sub-module, constructing a target function for minimizing a fitting error to obtain parameters of the fitting model, and obtaining a first pedestrian flow estimation result of a target day through the fitting model; and multiple kinds of real-time influence data are collected and combined with the first pedestrian volume estimation result, prediction correction is carried out through a trained error correction model, then a second pedestrian volume estimation result is output, and the real-time influence data comprise natural change influence data and artificial change influence data. The method has the advantages of being high in adaptability, low in computing power consumption and high in precision of space vitality prediction.

This invention belongs to the field of thermal energy storage control technology, specifically involving a thermal energy storage control method and control system based on flue gas parameter fluctuations. First, flue gas parameters from the boiler tail end are collected and preprocessed. Then, the parameters are decomposed and fluctuation characteristics are extracted using the EEMD algorithm. An LSTM-BP fusion model is used to predict the fluctuation range and trend. Next, a multi-objective optimization function is constructed based on relevant parameters, and the dynamic operating condition baseline value is obtained by solving it. Then, based on a fuzzy adaptive PID algorithm, the thermal energy storage device is adjusted by combining the deviation and fluctuation frequency. Finally, the actual fluctuations are monitored, and the model and optimization function are corrected to form a closed-loop control. This invention can accurately capture the fluctuation characteristics of flue gas parameters, achieve accurate prediction of fluctuation trends and dynamic adaptation to the operating condition baseline value, improve the accuracy and stability of thermal energy storage control, solve the pain points of existing methods such as adjustment lag and insufficient accuracy, and improve the efficiency of flue gas waste heat recovery.

The application discloses a magnetic fluid sealed shaft assembly, a shielded motor and a shielded pump. The shaft assembly comprises a shell provided with a containing cavity, a fixed structure arranged on the inner wall of the containing cavity, a rotating shaft supported and arranged in the containing cavity, a magnetic fluid sealing device arranged in the containing cavity, an inner sleeve sealingly and fixedly sleeved on the rotating shaft, a space reserved in the shell for the magnetic fluid sealing device to jump with the rotating shaft and / or adjust the installation angle and position, and an elastic member sealingly installed on the outer sleeve of the magnetic fluid sealing device and sealingly connected with the fixed structure. The structure compensates for the influence of insufficient precision of the flatness of the fixed structure, the perpendicularity of the rotating shaft and the fixed structure, the coaxiality and the axial and radial jumping of the rotating shaft by the elastic installation of the magnetic fluid sealing device, eliminates the additional axial force, radial force, external torsional force and static indeterminate force suffered by the bearing in the magnetic fluid sealing device during work, and enables the magnetic fluid sealing device to be applied to pump products and the like, so as to ensure the sealing effect of the pump products and the like.

This utility model relates to the field of medical device technology, and in particular to an intraoral scanning lens fixing structure and an intraoral scanning device. The intraoral scanning lens fixing structure includes: an optical engine housing with an installation channel and a fixing hole, the installation channel communicating with the fixing hole; a lens module installed in the installation channel; the projections of the lens module installed in the installation channel and the fixing hole on a plane perpendicular to the depth direction of the fixing hole at least partially overlap; a press-fitting component installed in the fixing hole, with the side of the press-fitting component facing the installation channel abutting against the outer wall of the lens module. This utility model enables the lens module to be fixed in the installation channel. During installation, the position of the lens module in the installation channel can be adjusted to achieve adjustment of parameters such as focal length, reducing errors. This eliminates the need for a high-precision housing for positioning and compensates for errors during lens module manufacturing, improving imaging accuracy and thus meeting the requirements of intraoral scanning devices.