390 results about "Transformation algorithm" patented technology

The invention provides a water quality heavy metal pollution detection method and system based on Raman spectrum. The method comprises the following steps: collecting a water sample through a water area to be detected, and scanning the water sample by adopting a Raman spectrometer to generate an original Raman spectrogram; based on the original Raman spectrogram, using a wavelet transform algorithm to perform de-noising processing, reducing background interference, using a principal component analysis technology to extract characteristic peaks, and generating a heavy metal preliminary prediction result; based on the preliminary heavy metal prediction result, constructing a heavy metal concentration prediction model by applying a partial least squares regression algorithm, performing quantitative analysis, evaluating prediction accuracy by adopting a cross validation technology, and generating a heavy metal actual concentration result; and based on the actual heavy metal concentration result, comparing with a water quality safety standard, evaluating a pollution condition, and generating a water quality heavy metal pollution detection report. The technical scheme provided by the invention has high sensitivity, can efficiently denoise and accurately predict, and provides a scientific means for monitoring and treating heavy metal pollution of water.

The invention discloses a machine vision-based intelligent detection method for steel galvanized surface defects, which comprises the following steps: S1, acquiring and preprocessing a steel galvanized surface image to obtain a standardized image; s2, constructing a specular reflection probability graph according to the brightness distribution and the gradient magnitude, and calculating a reflection intensity value; s3, calculating a structure tensor matrix, determining a main direction angle and an anisotropic consistency coefficient, and generating a direction feature matrix; s4, establishing a multi-scale direction adaptive phase kernel function, and performing phase modulation in a frequency domain by adopting an improved phase stretching transformation algorithm; s5, inverse Fourier transform is executed, and a phase response matrix is extracted; s6, performing weighted fusion to obtain a comprehensive phase response diagram; and S7, setting a threshold value according to the noise variance and the statistical characteristics, executing binarization and morphological processing, and outputting a defect region and boundary coordinates. According to the invention, high-precision identification and boundary positioning of steel galvanized surface defects are realized.

The invention relates to the technical field of regional security and protection monitoring, in particular to a regional intrusion identification method and system under the view angle of an unmanned aerial vehicle, which adopts a multi-source information fusion framework, combines the real-time position, attitude and flight state information of the unmanned aerial vehicle through an accurate space coordinate conversion algorithm, and realizes the regional intrusion identification under the view angle of the unmanned aerial vehicle. GIS geographic information, unmanned aerial vehicle monitoring and a deep learning detection result are deeply fused, high-precision positioning of an intrusion area in an image shot by an unmanned aerial vehicle is realized, and robustness in a complex environment is improved. Targets such as personnel and vehicles in the image are efficiently recognized by applying a YOLO series algorithm, and violation intrusion behaviors are accurately judged by calculating the intersection-to-union ratio IoU of the targets and the intrusion area. The unmanned aerial vehicle is utilized to quickly cover a large-area monitoring area, and the problem that the monitoring range of a traditional fixed camera is limited is solved. In addition, by means of a space coordinate conversion algorithm, the influence caused by height and angle changes in the flight of the unmanned aerial vehicle is effectively overcome, and accurate positioning of the intrusion area in the image is achieved.

The invention provides a crack three-way measurement research method and system based on multi-coordinate system fusion, and relates to the technical field of earth and rockfill dam monitoring. The method comprises the following steps: shooting concentric circle target images at multiple angles through a monocular camera, extracting feature points through preprocessing, and correcting projection distortion of non-parallel shooting; establishing a mapping relation between pixels and a three-dimensional coordinate system, and optimizing camera pose parameters; reconstructing a three-dimensional coordinate point cloud based on the multi-view data, screening outliers and fitting plane optimization data; and registering the three-dimensional point cloud to a world coordinate system through a coordinate system conversion algorithm, and comparing two measurement results to calculate the three-way displacement of the crack. According to the method, concentric circle target constraint feature precision is utilized, projection correction and plane fitting are combined to compensate monocular vision depth deficiency, high-precision displacement detection is achieved, and engineering monitoring requirements are met.

The invention discloses a storage and charging system battery capacity calculation method, and relates to the technical field of storage and charging system optimization control, and the method comprises the steps: collecting multi-modal data of a battery pack, and generating time-space aligned multi-modal data through a timestamp alignment and three-dimensional coordinate conversion algorithm; extracting local temperature gradient characteristics of an infrared thermogram and dynamic time characteristics of a charging and discharging curve through DSC and Bi LSTM based on the multi-modal data of space-time alignment, segmenting spatial distribution characteristics of electrolyte flow abnormity of an ultrasonic image by using U-Net, dynamically distributing weights of the multi-modal characteristics through a space-time attention mechanism, and generating a fusion characteristic vector; and inputting the fusion feature vector into a GRU-Transform hybrid model to generate a dynamic capacity prediction value, and identifying an aging type by dynamically analyzing historical data. According to the invention, multi-modal features are extracted through DSC, Bi LSTM, U-Net and other technologies, and comprehensive monitoring and dynamic adjustment of the battery health state are realized.

The invention discloses an LED spherical display screen-oriented geographic data dynamic adaptive display method, which comprises the following steps of: constructing a non-uniform grid mapping model based on LED spherical screen physical parameters (diameter, support structure cavity size and pixel row / column spacing); the method comprises the following steps: accurately mapping geographic data (converted into longitude and latitude coordinates in advance) from a longitude and latitude coordinate system to a spherical screen pixel space, and carrying out resampling adaptation on the data based on the resolution of a display; meanwhile, a quaternion rotation transformation algorithm and a dynamic mask technology are adopted, the shielding area of the supporting structure of the LED spherical screen is calculated in real time, invisible data are automatically cut in the three-dimensional rotation process, and the problems of coordinate mapping distortion, rotation tearing and shielding area adaptation delay existing in a traditional LED spherical display system are solved. According to the method, the sub-pixel-level mapping precision of the geographic data on the LED spherical screen and the self-adaptive shielding compensation response of real-time rotation are realized.

The invention relates to a polylactic acid test piece internal defect detection method, and belongs to the technical field of target detection, the method comprises the following steps: S1, image processing to obtain an input image; s2, attention enhancement feature extraction: preliminarily extracting spatial features, capturing global information and local information, focusing a defect area, and generating an enhancement feature map; s3, carrying out feature fusion, and outputting a fused feature map; s4, performing self-attention re-parameterization, and outputting a local feature map; s5, HSV spot detection including a color conversion algorithm and a defect enhancement algorithm; and S6, outputting a result, establishing a bounding box regression task, predicting a frame coordinate, outputting a defect position, identifying a category label, outputting a defect type, and evaluating reliability and outputting confidence. According to the method, feature extraction is carried out by using depth separable convolution, the visibility and detectability of low-contrast defects are enhanced, and the attention enhancement network is established to adaptively pay attention to key areas related to the defects, so that defect detection is more accurate and efficient.

The invention discloses an automatic welding method of a reinforcement cage welding robot, and relates to the technical field of welding robots. Based on an improved ResNet-50 multi-mode visual system, the welding point identification error is reduced to 0.1 mm level, and by matching with an SE (3) space coordinate conversion algorithm, the positioning precision reaches + / -0.03 mm (3 sigma); the visual algorithm fusing the deformable convolution and the coordinate attention mechanism still keeps the recognition rate improvement of 23.6% under the illumination fluctuation of 200-1500 lux; the improved RRT algorithm is combined with the self-adaptive B-spline interpolation, so that the motion smoothness of the six-degree-of-freedom mechanical arm is improved by 400%, and the welding defect caused by path sudden change is effectively avoided; motion control of the mechanical arm is optimized through the friction compensation model, and the welding stability is remarkably improved.

The invention relates to the technical field of clean laboratory environments, and discloses a predictive analysis method and system of a laboratory heating and ventilation system based on digital twinning. The method comprises the following steps: acquiring a plurality of first target data and a first reference value in a first time period, and respectively calculating first trend data and first spectrum data through a first trend algorithm and a first conversion algorithm; acquiring a plurality of second target data and a second reference value in a second time period, and calculating second trend data and second spectrum data; then, the difference between the first trend data and the second trend data is calculated as first state information based on the digital twin platform, and the difference frequency band between the first spectrum data and the second spectrum data is calculated as second state information. And then, matching corresponding equipment state data according to the state information, calculating a similarity value of the two, and if the similarity value is smaller than a preset equipment reference similarity value, sending out an equipment early warning prompt. According to the invention, hardware linkage can be effectively promoted, accurate prediction of the equipment state is realized, and the equipment fault risk is reduced.

The invention discloses an unmanned ship dynamic obstacle avoidance control system and method based on stochastic nonlinear model predictive control, and adopts a control structure of a planning layer and a control layer to solve the problem of dynamic obstacle avoidance of an unmanned ship in a complex obstacle environment. The planning layer is based on a random nonlinear model predictive control technology, and firstly, random modeling is carried out on the unmanned ship and dynamic obstacles encountered by the unmanned ship in the sailing process; designing obstacle avoidance switching conditions according to the whole actual obstacle avoidance process; in an obstacle avoidance random nonlinear model prediction planning control algorithm, uncertainty propagation of a dynamic obstacle and an unmanned ship in a whole prediction time domain is evaluated through unscented transformation, then obstacle avoidance constraint is described in a chance constraint mode, a chance constraint expectation operator transformation algorithm and a unit jump function approximation algorithm are designed, and a chance constraint expectation operator transformation algorithm and a unit jump function approximation algorithm are designed. Opportunity constraints are converted into deterministic constraints, and then a nonlinear optimization problem is constructed for planning. And the control layer adopts a PI D algorithm to track a planning value so as to realize dynamic obstacle avoidance of the unmanned ship.

The invention provides an automobile part visual inspection correction method and equipment. The method comprises the following steps: extracting a part contour through edge detection, calculating an inclination angle by adopting Hough transform, executing affine transform on an original image, enabling a rotation angle to be negative to the inclination angle, and ensuring that the parts are horizontally aligned; in the corrected horizontal image, calculating a transverse offset through a feature matching algorithm or template matching, and translating an image area to enable the center of the detection window to be aligned with the actual position of the part; if inclination and offset are detected at the same time, inclination correction is executed preferentially, the offset is calculated based on the image after inclination correction, synchronous correction is achieved through a composite transformation algorithm, and accumulative errors are reduced through iterative optimization; and extracting a size parameter from the corrected image, comparing the size parameter with a predetermined tolerance range, and if the measured size is outside the predetermined tolerance range, marking the image as a defective product, and removing the defective product. The method is used for upgrading the visual inspection system for automobile manufacturing.

The invention relates to the technical field of tower crane control, and provides an aerial high-risk area identification and hoisting path reconstruction method and system. The method comprises the following steps of: respectively mounting two rotary radars on a rotatable bracket of the tower crane to form a radar sensing module comprising a double-radar module; dynamically scanning the potential risk area in the construction scene through a radar sensing module to obtain real-time position information of the potential risk area; receiving the real-time position information through a processing module, and converting the real-time position information into real-time three-dimensional coordinate data in a motion coordinate system of the hoisting equipment by adopting a three-dimensional coordinate conversion algorithm; constructing a three-dimensional model of the potential risk area based on the real-time three-dimensional coordinate data; and identifying the three-dimensional model to determine a high-risk area, adopting an improved fast exploration random tree algorithm as a path obstacle avoidance algorithm, combining the three-dimensional model to dynamically reconstruct an initial hoisting path set by a user, and generating an optimal risk-avoiding hoisting track avoiding the high-risk area.

The invention discloses an intelligent fructus aurantii sorting machine based on a five-connecting-rod mechanical arm and a sorting method. The sorting machine comprises a collecting mechanism, a conveying mechanism, a supporting mechanism, a sorting mechanism, a camera support, a feeding device, a lower computer, an upper computer and a vacuum adsorption control system. The sorting mechanism comprises a vacuum adsorption sorting device, a five-connecting-rod mechanical arm and a sorting mechanism supporting base, double motors are adopted to cooperatively drive and control space positioning of an end effector of the mechanical arm, and high-precision target grabbing is achieved through angle difference compensation. The upper computer converts the target center position recognized by the visual recognition device into space coordinates of the tail end of the mechanical arm through a coordinate conversion algorithm, and the five-connecting-rod mechanical arm is driven to complete precise sorting operation. Stable adsorption of the fructus aurantii is completed by means of vacuum negative pressure, the fructus aurantii naturally falls off by directly cutting off a negative pressure air source, and intelligent grading and sorting operation of the quality of the fructus aurantii is achieved. The device is suitable for automatic sorting of the traditional Chinese medicinal material fructus aurantii and is high in sorting efficiency, accurate in positioning and high in adaptability.

The invention discloses a crystal oscillator circuit fault classification technology based on a multi-source information fusion network, and belongs to the technical field of analog circuit fault diagnosis. Firstly, a multi-source data set of different measurement points of the crystal oscillator circuit is acquired; carrying out conversion from a time domain to a frequency domain on the data set by utilizing fast Fourier transform; extracting data fault features by using a convolutional neural network, and performing a trust distribution function under each piece of source data by using a softmax classifier; fusing different trust distribution functions under the multi-source data by adopting a D-S evidence theory to obtain a final diagnosis result and diagnosis probability output, and calculating cross entropy loss; and finally, training model parameters through back propagation to obtain a final diagnosis model. According to the method, the time-frequency transformation algorithm, the deep neural network algorithm and the information fusion algorithm are combined, a multi-source information fusion network is constructed, the defects of an existing diagnosis model in crystal oscillator circuit fault classification are overcome, and the accuracy and stability of crystal oscillator circuit fault diagnosis are remarkably improved.

The invention discloses an image fusion method and device based on discrete wavelet transform and a convolutional neural network, a terminal and a storage medium. The method comprises the steps of preprocessing a received original image group to obtain an input image group; performing multi-scale decomposition on the input image group through DWT to obtain a decomposition result, and performing feature extraction on the decomposition result according to CNN to obtain an infrared low-frequency feature, an infrared high-frequency feature, a visible low-frequency feature and a visible high-frequency feature respectively; performing fusion through a preset feature fusion strategy to obtain a low-frequency fusion feature and a high-frequency fusion feature; and performing feature reconstruction on the low-frequency fusion features and the high-frequency fusion features through a preset inverse discrete wavelet transform algorithm to obtain and output a fusion image of the original image group. According to the method provided by the invention, the multi-scale characteristic of the DWT is combined with the depth feature extraction capability of the CNN, so that the comprehensive and accurate fusion of the image information is realized, and the quality and efficiency of image fusion are greatly improved.

The invention provides a cross-modal feature fusion method based on joint attention, which combines multi-modal data from different sources to predict the relative position of a target to be tracked, and comprises the following steps of: firstly, designing a cross-modal data representation network model for the data of different modals; generating a time sequence high-dimensional implicit code retaining key dependency information from the original data through a code conversion algorithm; secondly, a heterogeneous attention network unit is designed, and features of time sequence high-dimensional implicit codes corresponding to different modal data are extracted through two different forms of attention; and finally, through a cooperative training mechanism, information complementation among different modal data is utilized to generate the most effective feature representation for a time sequence prediction model, and accurate prediction of the moving position of the tracked target is realized.

The invention is suitable for the field of intelligent jet cleaning, and provides a dirt recognition cleaning method, device and equipment, and the dirt recognition cleaning method comprises the steps: obtaining an original image corresponding to target dirt and a sound reflection signal corresponding to the target dirt; converting the sound reflection signal corresponding to the target dirt into an image representation; obtaining a fused image corresponding to the target dirt according to the original image corresponding to the target dirt, the image representation and a preset multi-channel image fusion algorithm; inputting a fusion image corresponding to the target dirt into the improved deep neural network to obtain segmentation mask data and size data of the target dirt; adjusting the pose of the dirt cleaning equipment according to the segmentation mask data and a preset coordinate conversion algorithm; according to the size data of the target dirt, dirt cleaning parameters are adjusted, and dirt cleaning equipment is controlled to execute cleaning operation. According to the method, the dirt recognition and cleaning precision and efficiency are remarkably improved, and various cleaning requirements and operation environments can be better met.

The invention provides a battery broadband electrochemical impedance spectroscopy time domain rapid detection method and system, and the method comprises the steps: S1, dividing a target signal frequency band into a low frequency band, a middle frequency band and a high frequency band from low to high, and setting the parameters of an excitation signal DIBS of each frequency band; s2, enabling the discrete binary sequence to have spectrum distribution corresponding to the target signal through an optimization algorithm, and obtaining a DIBS signal containing all set frequency points; s3, performing current excitation on the battery by adopting DIBS excitation signals of different frequency bands to obtain excitation current and response voltage; and S4, respectively calculating the frequency spectrums of the excitation current and the response voltage under the three frequency bands, and obtaining the final impedance. A multi-band excitation mode is adopted, the sequence length of a single-segment signal is shortened, the clock period of the single-segment signal is prolonged, and the storage burden of excitation equipment and the data processing complexity of a time-frequency conversion algorithm are effectively prevented from being aggravated due to the long sequence period.

The invention discloses an underground multi-source fusion positioning method and system. The method comprises the following steps that initialization is carried out based on a known initial pose of underground equipment during starting; acquiring environment point cloud data scanned by a vehicle-mounted laser radar of underground equipment and motion information acquired by an inertial measurement unit; registration is carried out based on the environment point cloud data and a pre-constructed high-precision three-dimensional map, and first pose estimation is obtained by using an OpenMP-based parallel normal distribution transformation algorithm; using the motion information to obtain second pose estimation through integral operation; inputting the first pose estimation and the second pose estimation into a Kalman filter for loose coupling fusion, and outputting the fused equipment pose; and outputting the final pose as a positioning result of underground equipment for vehicle navigation and pose control. The method effectively improves the positioning precision of underground equipment.

The invention discloses a quantum circuit conversion method and system, electronic equipment and a storage medium, and relates to the technical field of quantum circuit conversion, and the method comprises the steps: extracting a feature vector of a logic quantum circuit based on initial quantum bit mapping; the feature vector is input into a pre-trained decision tree, recommendation parameters of a line conversion algorithm are obtained, the decision tree is constructed by a training set, and the feature vector of each sample corresponds to the optimal parameter of the decision tree, namely the parameter with the minimum number of physical line gates; and configuring a line conversion algorithm by using recommended parameters, converting a logic line into a physical line, and ensuring that all two quantum bit gates meet quantum computer connected graph constraints and are equivalent in function. According to the method, adaptive parameter configuration can be achieved through the feature vectors and the decision tree, the line conversion quality is effectively improved, the number of physical line gates is remarkably reduced, and the quantum program execution efficiency is improved on the premise that function equivalence and connectivity are guaranteed.

The invention discloses a millimeter-wave radar and vision fused vehicle three-dimensional detection method, which comprises the following steps of: performing space-time fusion on millimeter-wave radar data and a camera image to obtain corresponding pixel position information of an actual position of a vehicle in the image, and calculating vehicle three-dimensional frame information by utilizing a vision algorithm; and positioning to a target position according to a coordinate conversion algorithm, judging a target through a Rayleigh fusion algorithm, and drawing a three-dimensional mark at the position of the target to realize three-dimensional vehicle detection. The long-distance detection advantage of the millimeter wave radar and the fine visual perception capability of the camera are fully combined, the vehicle three-dimensional detection is stably, efficiently and accurately completed in a complex traffic environment, and the accuracy of an intelligent traffic perception algorithm is greatly improved.

The invention discloses a cradle head dynamic control method and device, and the method comprises the steps: obtaining a two-dimensional pixel coordinate of a target object on a display plane, converting the two-dimensional pixel coordinate into a physical space coordinate through a coordinate conversion algorithm, and obtaining the pixel offset of the target object relative to the center of a cradle head; based on the pixel offset and the pixel density parameter, performing angle calculation by using a trigonometric function calculation module to obtain rotation angle parameters required by the horizontal axis and the vertical axis of the holder; pWM control signal conversion is carried out on the rotation angle parameter, a corresponding number of pulse waveforms are generated through a stepping motor driving module, and a holder double-shaft motor is controlled to rotate; and based on the deviation value between the current position of the holder and the target angle, real-time error correction is performed by adopting a PID control algorithm, so that the holder tracks the target object in real time and keeps pointing to the position of the target object. Through the solid geometry correction technology, the problems of precise positioning and dynamic tracking of a traditional pan-tilt control system in a complex scene are solved, and the precision and stability of pan-tilt control are improved.

The invention discloses a thermal power plant steam engine room pipe network rapid three-dimensional modeling method and system, and belongs to the technical field of thermal power plant digital modeling, and the method specifically comprises the steps: obtaining pipe network point cloud data and position coordinate data through employing a laser scanning technology and a total station; denoising by adopting a filtering algorithm, splicing and fusing the point cloud data by adopting a point cloud registration algorithm to form a pipe network point cloud model, and aligning with a geographic coordinate system through a coordinate transformation algorithm; extracting pipe network characteristics by using a region growing algorithm, marking and classifying by using a template matching algorithm in combination with design drawing attribute data, and establishing a pipe network topological structure relationship; carrying out three-dimensional visual modeling on the pipe network through three-dimensional modeling software; and finally, checking and correcting to obtain a final rapid three-dimensional model of the steam engine room pipe network. According to the invention, the modeling efficiency and accuracy are improved.

The invention discloses a natural language processing system encryption method, electronic equipment and a computer readable medium. The method comprises the following steps: acquiring a character mapping relationship between an original character and an encrypted character determined based on a character encryption algorithm; according to a Token ID transformation algorithm, a Token ID mapping relation between the original Token ID and the transformed Token ID is determined; and according to the character mapping relationship and the Token ID mapping relationship, encrypting a pre-trained natural language processing system, so that the encrypted natural language processing system can output a ciphertext response based on an input ciphertext prompt word. Side channel attacks and middle eavesdropping can be resisted, the exposure risk of original data is remarkably reduced, the data security is improved, mathematical reconstruction of computational logic of the system is avoided, so that the computational overhead is remarkably reduced, the reasoning delay is reduced, the computational efficiency and the response real-time performance are improved, a natural language processing system does not need to be retrained, and the method is easy to implement. The calculation overhead is further reduced, and the encryption efficiency is improved.

The invention discloses a geographic positioning optimization method based on STN-YOLO and adaptive affine transformation, and relates to the technical field of geographic positioning optimization, and the method comprises the steps: employing a camera to carry out the shooting of an environment, and obtaining an original input image; performing spatial attitude alignment processing on the original input image by adopting an image pre-correction method to obtain an attitude normalized corrected image; an STN integrated YOLO target detection model is adopted to perform multi-category target recognition and bounding box regression on the corrected image subjected to attitude normalization, and a detection result with initial pixel-level coordinates is obtained; performing dynamic geometric correction on the initial pixel-level coordinates by adopting a self-adaptive affine transformation algorithm to obtain relative position information under a geographic mapping coordinate system; adopting a multi-source data fusion method to combine data of sensors such as a GPS (Global Positioning System) and an I MU (International Mobile Unit) and the relative position information to carry out collaborative filtering processing so as to obtain data after collaborative filtering; and optimizing the data after collaborative filtering, eliminating noise and abnormal values, and obtaining a global geographic positioning result.

The invention provides a time stretching Fourier transform optical frequency comb morphology measurement system and method. The time stretching Fourier transform optical frequency comb morphology measurement system comprises an optical frequency comb OFC, an interferometer module, a dispersion optical fiber module, a signal detection module and a synchronous control module. An optical frequency comb (OFC) provides an incident light beam for the interferometer; the interferometer module obtains an interference signal of the measured object by adjusting the length of the single-mode optical fiber; the dispersion transmission module performs time stretching on the interference signal through a single-mode optical fiber to generate a time domain interference signal; a signal detection module captures the stretched time domain interference signal, and solves the morphology parameters of the measured object through a time-frequency transformation algorithm; the synchronous control module drives the two-dimensional displacement platform bearing the measured object through the motion control card and triggers synchronous acquisition and storage of three-dimensional shape data of the measured object. The method has enough high precision in morphology measurement, and the detection speed of the method can meet the requirements of industrial real-time detection.

The disclosed embodiment provides an ecological environment quality monitoring system, comprising: a gateway device sends its own fingerprint information to a remote server; the server uses a private conversion algorithm to process the fingerprint information to obtain a gateway ID; the gateway device generates a report message based on the gateway ID, fingerprint information, and reported data sent by the environmental monitoring device, and sends the report message to the remote server; after the remote server parses the report message to obtain a resolved gateway ID, resolved fingerprint information, and resolved reported data, it verifies whether the resolved gateway ID and resolved fingerprint information match based on the stored association relationship in the data table; if it is determined that the resolved gateway ID and fingerprint information do not match and the resolved gateway ID is stored in the data table, the association relationship corresponding to the resolved gateway ID is deleted. The data falsification device cannot obtain the gateway ID, so it does not know the correspondence between the gateway ID and the gateway fingerprint information, making it difficult to falsify reports from a large number of gateway devices.

The invention discloses an unmanned aerial vehicle road disease detection and analysis system and method based on a YOLO algorithm, and the method comprises the following steps: synchronously collecting a road image and geographic coordinates through an unmanned aerial vehicle, and constructing an image data set with geographic reference; constructing an initial YOLO target detection model based on the data set; introducing an additional detection layer for detecting a pixel area into the model, and embedding a channel attention mechanism into the feature extraction network to obtain an improved YOLO target detection model; reasoning a data set by using the model, and outputting a disease category, a bounding box coordinate and a confidence coefficient; pixel coordinates are converted into geographic coordinates through a coordinate conversion algorithm, and disease records with accurate geographic coordinates are generated; and optimizing and updating the model based on the record as an incremental training sample. According to the method, the disease detection precision and the small target identification capability are effectively improved, and the long-term adaptability and generalization performance of the model are enhanced through a closed-loop incremental learning mechanism.

The invention relates to the technical field of water monitoring and detection, in particular to a simulation system and an early warning method for multi-point dam break flood. The simulation system comprises a data collection module, a data processing module, a model construction module and a simulation calculation module, and the simulation calculation module is used for completing calculation of multi-point dam break flood in the flood dynamic coupling model and outputting a simulation result. Different reference data are unified to the same projection coordinate system through a coordinate conversion algorithm, and terrain splicing dislocation is avoided; the model construction module firstly generates an unstructured grid based on accurate topographic data, and grid nodes are overlapped with actual topographic feature points through a grid boundary optimization algorithm; extracting a grid where a potential overflow point is located, and writing the grid into a parameter file as a dynamic boundary condition; finally integrating geometry, boundaries, parameters and source files to construct a coupling model; the problem that an existing simulation system cannot truly reflect nonlinear phenomena such as turbulence and vortex in the flood routing process is solved.

The invention relates to a template-based multi-format layout file generation method and system, and the method comprises the following steps: generating a template object and a data object through analyzing a template file and a data file, constructing a document object of a fixed page through a dynamic paging calculator and a preset strategy class diagram, and supporting multi-format output; data volume self-adaptive paging is realized through a paging strategy, and cross-page table header repeated rendering and cell merging are supported; a middle data layer is adopted to separate contents and formats, and a coordinate system conversion algorithm is utilized to realize output of formats such as PDF and OFD. I / O consumption is reduced by lazy loading of a font resource pool, and table dynamic expansion and cross-page association are realized based on gridding modeling. According to the method and the device, the problems of incapability of self-adaptive paging and poor compatibility of multi-format output of traditional template sleeve printing are solved, and the efficiency and the consistency of layout file generation in a government affair electronic scene are remarkably improved.