7323 results about "Calculation methods" patented technology

The invention relates to the technical field of unmanned aerial vehicle positioning, in particular to an unmanned aerial vehicle flight path positioning method and system based on multi-source information fusion. The method comprises the following steps: acquiring an original observation data stream of an unmanned aerial vehicle in real time through a sensor array, and preprocessing to output a multi-source data sample set; calculating relative motion increment between adjacent key frames through an IMU pre-integration model, and extracting local pose estimation through a visual geometric calculation method; evaluating the confidence of each sensor in real time to dynamically generate an adaptive weight coefficient; and constructing a tight coupling fusion filter taking position, speed and attitude errors as core state quantities, and outputting a global optimal trajectory of the unmanned aerial vehicle. According to the invention, the weight is dynamically distributed through the real-time confidence of the sensor, the multi-source data association is fully mined, and the flight path positioning precision and environmental adaptability of the unmanned aerial vehicle are improved.

The invention relates to a multi-source data fusion-based urban physical examination evaluation index calculation method and system. The method comprises the steps of extracting a multi-source data sequence; identifying a data source of the urban physical examination index set, and extracting an independent time sequence data sequence; calculating the information entropy of the independent time sequence data sequence, and distributing a basic fusion weight; calculating a dynamic state evaluation value of the independent time sequence data sequence, and performing weighted fusion on the basic fusion weight and the dynamic state evaluation value to obtain a comprehensive state evaluation value; obtaining a distribution variance of the basic fusion weight, inputting the distribution variance into the uncertainty quantification model, and obtaining an index calculation result containing uncertainty measurement; the real-time performance of the evaluation result is enhanced through an aging attenuation mechanism, and the latest state of the city system is accurately reflected; the output uncertainty measurement index provides a quantitative basis of result credibility for a decision maker, and the decision risk caused by a data fusion error is reduced.

The invention discloses a free-form surface three-axis ball-end cutter equal approximation error finish machining tool path generation method which comprises the following steps: firstly, importing a free-form surface model to be machined, and setting data such as the radius, the line spacing, the approximation error maximum allowable value and the precision of a ball-end cutter; secondly, a group of section planes are planned according to the row spacing to intersect with the curved surface, the intersecting line serves as a cutter contact curve, and an equal-bow-height-error cutter contact iterative search method for driving cutter contact adjustment through the geometric distance is provided for the cutter contact curve on the section planes; the maximum distance between a cutter cutting envelope surface and a cutter contact track line is used as an approximation error, and an adaptive discrete method is adopted to carry out approximation error calculation; and finally, the cutter location points of the equal-bow-height-error cutter contact points serve as initial values, an equal-error cutter location point calculation method of step length self-adaptive adjustment iteration is provided, approximation errors between the cutter location points are all within an allowable range, and therefore the free-form surface three-axis ball-end cutter equal approximation error finish machining cutter path is obtained.

The invention discloses a complex terrain three-dimensional modeling and earthwork volume calculation method based on a multi-source fusion point cloud, belongs to the technical field of surveying and mapping and engineering surveying, and mainly solves the problems of low terrain modeling precision and insufficient earthwork calculation efficiency in a complex scene. The method comprises the following steps: constructing a ground-air integrated multi-source sensing network to synchronously acquire laser point cloud, multi-view images and positioning data; adopting PointNet + +-based initial registration and multi-scale ICP fine registration fusion to generate a unified point cloud; combining semantic segmentation and penetration probability filtering to accurately extract a digital elevation model; constructing a similar triangular prism voxel model by using a constrained Delaunay triangulation network; and finally, the earth volume is rapidly calculated by adopting a GPU parallel voxel cutting and filling algorithm, so that high-precision terrain modeling and rapid engineering quantity calculation are realized, and the method can be efficiently and reliably applied to large-scale projects such as roads and mines.

The invention discloses a road cavity volume calculation method and device based on a three-dimensional FK migration algorithm, equipment and a medium, and relates to the technical field of road cavity detection, and the method comprises the steps: obtaining three-dimensional ground penetrating radar data, and carrying out the preprocessing of the data, and obtaining target radar data; converting the target radar data to a frequency wavenumber domain to obtain frequency wavenumber domain radar data; establishing a road hierarchical velocity model, and performing hierarchical wave field extrapolation and double weight correction based on the frequency wave number domain radar data and the road hierarchical velocity model to obtain corrected wave field data; performing sparse constraint optimization imaging processing on the corrected wave field data to obtain a target imaging result; and carrying out boundary extraction processing on the target imaging result to obtain a three-dimensional cavity boundary point set, and carrying out voxelization processing based on the three-dimensional cavity boundary point set to obtain a road cavity volume. According to the invention, high-precision restoration of the shape of the road cavity and automatic extraction of the volume can be realized in three-dimensional GPR imaging.

The invention provides a parallel computing method and device, electronic equipment and a storage medium, and relates to the technical field of parallel computing, and the method comprises the steps: carrying out the first protocol operation of a target tensor based on each computing core in each stream processor cluster, and generating a data block containing the computing result of each computing core; writing a data block generated by each stream processor cluster into a shared cache; under the condition that each stream processor cluster completes the first protocol operation, reading a data block written by each stream processor cluster from the shared cache; and executing a second protocol operation on the data block read from the shared cache to generate a calculation result of the target tensor. According to the method and device provided by the invention, the parallel architecture and memory access characteristics of the artificial intelligence chip can be better matched, the unnecessary calculation delay and synchronization overhead of the cross-flow processor cluster in the parallel calculation process are reduced, the bandwidth utilization rate of the shared cache is improved, and the overall performance and calculation efficiency of parallel calculation are remarkably improved.

The invention relates to a time-varying power high-precision calculation technology of an electric drive system under strong electromagnetic noise interference, and mainly solves the problem of inaccurate power calculation of the electric drive system under strong electromagnetic environment noise and frequency time-varying fluctuation scenes. According to the core technology, a dominant frequency fluctuation curve of a signal is obtained through dynamic tracking of a dominant frequency, and a dynamic band-pass filter changing along with the dominant frequency of the electric drive system is constructed; suppressing pulse noise by combining amplitude self-adaptive filtering of a nonlinear weighting function; a phase demodulation technology fusing zero crossing point correction and Hilbert transform is adopted to eliminate the phase interference problem caused by complex waveforms and weak noise signals; and finally, establishing a time-varying power physical model based on the sliding window. According to the technology, the power calculation accuracy of the electric driving system under the conditions of strong field environmental noise and continuous main frequency conversion is remarkably improved.

The invention belongs to the technical field of simulation analysis, and particularly relates to a medium-high voltage switch cabinet internal humidity inversion calculation method based on simulation analysis, which comprises the following steps: establishing a geometric model of a switch cabinet, importing the geometric model into finite element simulation software to obtain a simulation analysis model, adding each physical field and computational domain and boundary conditions thereof, and calculating the internal humidity of a medium-high voltage switch cabinet. All the physical fields are coupled, and mesh generation is carried out; performing numerical solution on the simulation analysis model by using a transient solver to obtain a temperature and humidity distribution condition in the switch cabinet; the simulation analysis model is optimized, a simulation data set is constructed, and a PINN is trained; based on the environment temperature and humidity and the operation current collected in the actual operation of the switch cabinet, the trained PINN is used for prediction, and the steady-state relative humidity of the current transformer is obtained. According to the invention, based on the limited boundary monitoring data, efficient and accurate reconstruction of the humidity field of the key area in the switch cabinet is realized, and a feasible path is provided for equipment state sensing and condensation risk early warning.

An offshore wind turbine integral coupling fatigue calculation method based on artificial intelligence belongs to the technical field of offshore wind power engineering, is used for solving the problem of efficient and high-precision evaluation of the fatigue life of an offshore wind turbine, and is characterized in that key environment parameter vectors influencing structural response and a data set of corresponding fatigue damage labels are acquired; training a deep neural network model by using the data set; the deep neural network model outputs corresponding fatigue damage per unit time in response to a central point parameter of an environment working condition block in an input long-term joint probability distribution diagram of the wind power site; according to the method, the defects that a traditional time domain simulation method is high in calculation cost and long in period are overcome, the calculation efficiency is improved by a plurality of orders of magnitude while the precision is guaranteed, and a powerful tool is provided for rapid design and optimization of the offshore wind turbine.

The invention discloses an attention mechanism calculation method and device, a storage medium and a product, and the method comprises the steps: carrying out matrix multiplication operation through employing a query matrix block of a first register block and a key matrix block of a shared memory, obtaining a first product matrix block, and writing the first product matrix block into a second register block; performing exponential operation by using the first product matrix blocks to obtain sub-matrix blocks, writing the sub-matrix blocks into a second register block in a covering manner, and writing the sub-matrix blocks into a third register block in the form of a target precision type; performing matrix multiplication operation by using the sub-matrix blocks of the third register block and the value matrix blocks of the shared memory to obtain second product matrix blocks, and writing the second product matrix blocks into a second register block; performing softmax operation by using the second product matrix blocks to obtain attention result matrix blocks, and writing the attention result matrix blocks into a fourth register block; and writing the attention result matrix of the fourth register group into the shared memory in blocks. According to the embodiment of the invention, overflow of the register can be avoided, and the utilization of hardware resources is maximized.

The invention provides a carbon emission calculation method based on adaptive Kalman filtering. According to the carbon emission calculation method based on adaptive Kalman filtering, a data matrix is generated by acquiring multi-source data, and a unified data basis is provided for subsequent calculation; a dynamic system model and an error measurement matrix are initialized, a state transition model indicates a carbon emission evolution law, an observation model establishes a mapping relation between multi-source data and carbon emission, and the error measurement matrix dynamically indicates a model effect and adaptively adjusts calculation parameters to ensure the adaptability of the model to the dynamic change of the system; a carbon emission prediction parameter and an error measurement matrix are calculated in real time through adaptive Kalman filtering, a prediction value is corrected through an observation parameter, an optimal estimation parameter and an observation residual error are obtained, meanwhile, the error measurement matrix is updated in real time, and dynamic fusion and noise suppression of multi-source data are achieved through the closed-loop process. And the precision and the real-time performance of carbon emission calculation are improved.

The invention relates to the technical field of risk control and data analysis, in particular to a risk control real-time feature platform calculation method and system based on a big data technology. The method comprises the following steps: firstly, acquiring multi-source data in real time through a parallelization mechanism; executing three-layer cleaning based on a streaming engine; dynamically generating numeric and associated feature vectors by adopting a sliding window; loading a pre-training model to carry out risk assessment on the feature vector and outputting a third-level risk event; executing a hierarchical response strategy: transaction blocking, manual auditing and auditing release; a layered framework is adopted, and incremental model training and deployment are supported; and real-time monitoring and dynamic configuration functions are provided. According to the invention, millisecond risk identification and response are realized, and risk control timeliness and accuracy are significantly improved.

The invention relates to a multi-channel marketing effect evaluation method and system based on causal reasoning and anti-fact Shapley, and belongs to the technical field of digital marketing analysis, and the method comprises the steps: collecting the original behavior data of a user in a multi-channel marketing environment, and constructing a behavior sequence according to the original behavior data; performing feature extraction and engineering processing based on the behavior sequence to obtain structured features; respectively training a tendency scoring model and a result model by adopting a dual machine learning method based on the structured features, and obtaining an unbiased causal effect estimated value of each channel contact on the conversion target through cross fitting; calculating a causal contribution value and a causal contribution confidence interval of each channel contact through an anti-fact Shapley value calculation method; and performing budget optimization distribution according to the causal contribution value, and outputting a marketing strategy suggestion. The method has the effects of accurately quantifying the causal contribution of each marketing channel, eliminating the self-selection deviation of the user and providing a reliable statistical basis.

The invention discloses a BNCT dose calculation method, which comprises the following steps: S1, constructing a voxel model, initializing one or more particles in a simulation system, and respectively acquiring the initial position, energy and movement direction of each particle; s2, adaptively selecting a Monte Carlo particle tracking algorithm and a flux counting mode based on the region where the particles are located and the energy of the particles; s3, repeating the step S2 until the particles leave the simulation system or are killed when meeting a truncation condition; and S4, cumulatively calculating dose distribution. Through the BNCT dose calculation method, the Monte Carlo particle transport simulation time is greatly shortened, the BNCT dose calculation efficiency is optimized, and the method is suitable for rapid and high-precision radiation dose simulation under a BNCT complex tissue structure.

The invention discloses an enterprise carbon emission measuring and calculating method and system based on production activity carbon footprint analysis, relates to the technical field of enterprise carbon emission, and effectively solves the problem of difficulty in data space-time alignment and process association in a complex production process by introducing a time sequence mapping and process feature decoupling mechanism. Multi-source heterogeneous data are fused in the feature recognition stage, and the integrity and interpretability of energy consumption behavior modeling are improved by combining graph structure modeling and causal attribution analysis methods; structured expression and dynamic weight updating of a carbon emission path are realized based on a carbon emission calculation map, and the response capability and traceability of the model to working condition changes are enhanced; high efficiency and adaptability of carbon emission measurement and calculation are realized through distributed path analysis and a carbon factor dynamic adjustment mechanism; the finally output time-phased and process-divided carbon emission result provides a scientific basis and technical support for an enterprise to carry out refined carbon performance evaluation, carbon asset management and green transformation decision-making.

The invention relates to the technical field of computer-aided engineering, in particular to a nonlinear efficient iterative solving method for thermal strain load, which is used for solving an obtained finite element equation by using a modified Newton-Raphson method and comprises the following steps of: firstly, establishing a geometric model to be analyzed and performing grid division; the method comprises the following steps: firstly, setting a model to be analyzed, then setting boundary conditions and temperature field change conditions of the model to be analyzed, finally, inputting the conditions into an algorithm solver, solving a nonlinear equation set, iteratively inputting a load continuously according to a modified Newton-Raphson method in the solving process, calculating node displacement until convergence, and solving stress-strain conditions in the welding process according to a material constitutive relation. In the solving process, by judging the size of the two norms of the displacement increment obtained in the adjacent increment step heuristic stage, the convergence of nonlinear solving of the structure is enhanced through the calculation mode, and the solving speed of the nonlinear problem in the thermal elastic-plastic constitutive structure is increased.

The invention discloses an earth heat flow joint inversion calculation method, device and system, and a storage medium. The method comprises the following steps: 1, obtaining a temperature constraint value; 2, obtaining a thermal parameter constraint value; 3, determining value ranges of thermal conductivity and heat generation rate parameters of each layer section; 4, constructing an initial temperature profile; 5, carrying out inversion optimization to obtain an optimal thermal parameter; and 6, calculating and extracting an earth heat flow value. By adopting the technical scheme of the invention, a high-precision and high-reliability earth heat flow value can be obtained under the constraint of a small amount of measured data.

The invention relates to the technical field of computational fluid mechanics data post-processing, and particularly discloses an OpenFOAM unsteady state simulation result-oriented boundary surface physical quantity calculation method, which comprises the following steps of: setting a working root directory, reading a grid file and establishing an example grid; accessing a time control function, and reading simulation time information of each time folder; establishing a global blank file to store boundary surface physical quantity results, first line writing time and physical quantity variable names at all moments; sequentially reading field quantity data required by calculation in the time folder; appointing and searching the name of a concerned boundary surface, creating a scalar field magSf of the boundary surface, and calculating and storing the area of a grid surface element; defining and initializing physical quantities and intermediate quantities of boundary surfaces, calculating physical quantities and intermediate variables of surface elements of each grid, and traversing the grids; and writing a result from the second line of the global file according to a time sequence, and traversing all times. By the adoption of the method, key data at all moments can be accurately extracted, errors and complexity caused by manual processing are avoided, and the calculation efficiency is greatly improved.

The invention relates to the technical field of underground engineering safety monitoring and disaster simulation, in particular to a digital twinborn deduction platform for underground engineering disaster chain evolution simulation, which comprises a multi-disaster coupling numerical simulation module used for acquiring multi-source data including design drawing data, geological data and engineering monitoring data, and based on the multi-source data, establishing an initial stress field model by using a numerical calculation method combining a finite element and a finite difference, and carrying out leakage-settlement-structure failure multi-disaster coupling numerical simulation. According to the method, the partial differential equation for describing the evolution law of the underground engineering is used as a constraint term to be embedded into the deduction model, and online identification and dynamic extrapolation of parameters are executed by fusing real-time monitoring data, so that the accuracy of disaster evolution simulation under complex working conditions is remarkably improved; and the problem that the traditional numerical calculation method is difficult to meet the real-time requirement of digital twinning is solved.

The invention provides a flow field solving method based on a time sequence physical information neural network, and belongs to a partial differential equation calculation method. The method comprises the following steps: firstly, determining a flow field motion law and a flow field computational domain based on a fluid motion control equation, configuring data points for training and performing data fusion operation; secondly, constructing a physical constraint residual equation, taking the training data set as input data of a neural network, calculating a data residual term, weighting a calculation result of the physical constraint residual equation and a calculation result of the data residual term, and constructing a data-physical mixed loss function; and finally, constructing a time sequence-based physical information neural network, performing training optimization on parameters of the time sequence-based physical information neural network, completing training and obtaining simulated flow field features. By introducing the time sequence module, the accuracy of flow field dynamic simulation based on the time sequence physical information neural network is improved, the requirement for the model solving speed can be met, and the feasibility and accuracy of the model are guaranteed.

The invention relates to the field of vacuum circuit breakers, in particular to a vacuum circuit breaker opening and closing dynamic characteristic calculation method, device and equipment and a medium. Establishing a three-dimensional geometric model of the pole-mounted vacuum circuit breaker arc extinguish chamber and the moving and static contacts; setting material attributes for each part in the three-dimensional geometric model; constructing a multi-physics field coupling system; the area where the moving contact is located is divided into movable grids, and the grid density of the moving contact and the grid density of the static contact dynamically change along with time; and performing multi-field coupling transient solution according to the three-dimensional geometric model, the multi-physical field coupling system and the movable grid to obtain the dynamic characteristics of the vacuum circuit breaker. The electromagnetic field, the thermal field, the fluid field, the structure field and the circuit are subjected to full coupling analysis, multi-physical field strong coupling dynamic simulation of the whole opening and closing process is achieved, and the dynamic characteristics of the whole opening and closing process can be accurately calculated.

The invention discloses a floating type offshore wind turbine aerodynamic load calculation method based on a frequency domain method. The method comprises the steps that a state derivative is determined based on a blade element momentum theory quasi-steady-state assumption, and a dynamic inflow model is used for correction; establishing a pneumatic-elastic coupling two-degree-of-freedom linear dynamic model; establishing a wind wheel kinetic model; establishing a control model according to a floating type offshore wind turbine pitch angle control strategy, a torque control strategy and a floating body motion feedback control strategy; based on the pneumatic-elastic coupling two-degree-of-freedom linear dynamic model, the wind wheel dynamic model and the control model, pneumatic additional mass and pneumatic additional damping are obtained; pneumatic exciting force acting on the hub when the position of the cabin is fixed is obtained; and based on the pneumatic additional mass, the pneumatic additional damping and the pneumatic exciting force, an overall linear dynamic model of the fan is established and solved, and overall response is obtained. According to the method, the calculation result precision can be improved while the calculation efficiency is ensured, and a technical support is provided for accelerating the simulation efficiency of the offshore wind turbine.

The invention belongs to the technical field of mechanical transmission, and discloses a conductor ring and magnetic resistance array composite permanent magnet thrust bearing and a damping force calculation method. The conductor ring and magnetic resistance array combined type permanent magnet thrust bearing realizes the bearing of non-contact magnetic thrust through the combination of the eddy current ring and the magnetic group array. When thrust from a propeller at the stern end of a propulsion shafting acts, the rotor magnetic group array axially moves, axial traction force is generated between the rotor magnetic group array and the stator magnetic resistance array to counteract the thrust action from the axial direction, meanwhile, the magnetic group array cuts the vortex ring, induction damping is generated on the surface of the vortex ring, damping force is formed, and the vortex ring is driven to rotate. And therefore, the longitudinal vibration during transmission of the propulsion shafting is reduced, and the propulsion shafting system is more silent and stable during operation. In addition, the damping force calculation method does not need complex three-dimensional structure modeling and grid division, is simple in solution, high in universality and short in calculation time consumption, and has high engineering application practical value.

The invention provides a road inspection target positioning method based on multi-source data fusion, and relates to the field of road daily inspection and infrastructure performance monitoring, and the method comprises the following steps: obtaining multi-source data based on a preset multi-source sensor; through deep coupling of satellite positioning carrier double-difference observation and inertial navigation solution of an inertial sensor, error correction is carried out in combination with Kalman filtering recursion, and fusion navigation data is determined; according to the fused navigation data, carrying out fusion processing on the two-dimensional visual observation data and the three-dimensional space point cloud data to obtain a forward view depth map; determining the national geodetic coordinates of the disease by combining a depth value back calculation method and utilizing a forward view depth map; and obtaining a starting kilometer pile number in a road inspection process, and determining a mileage pile number of the disease by combining the national geodetic coordinate of the disease and utilizing a Gaussian positive algorithm. According to the invention, centimeter-level geographic coordinate positions of diseases and corresponding mileage stake numbers can be output.

The invention discloses a new energy power grid probability harmonic load flow calculation method based on improved semi-invariant and Gram-Charlier series expansion. The new energy power grid probability harmonic load flow calculation method comprises the following steps: establishing a random variable probability model, a wind-light output model and a wind-light joint distribution model; secondly, considering the output correlation between wind and light fields, converting the wind and light combined distribution model based on a Copula function into independent variables by utilizing Rosenblatt conversion for calculation, then calculating each-order semi-invariant of load, photovoltaic output and wind power output according to the expected values of node voltage and branch power flow and a sensitivity matrix, and finally calculating the output correlation between the wind and light fields according to each order semi-invariant of the load, the photovoltaic output and the wind power output. The method comprises the following steps of: obtaining a state variable, further solving each-order semi-invariant form of the state variable and the branch power flow, and finally, obtaining a probability density function and a probability distribution function of harmonic voltage of each node by combining Gram-Charlier series expansion.

The invention discloses a non-convex contiguous group sparse variational filtering hyper-parameter adaptive calculation method, which comprises the following steps of: selecting a reference signal according to ultrasonic signal characteristics, and determining the size of a group sparse group through a specific formula in combination with a sampling frequency and a probe frequency; after interference removal is carried out on the ultrasonic signal, a scattering noise standard deviation is calculated based on the reference signal, and a regularization parameter is obtained in combination with a formula; calculating a penalty factor; when the detection sound path distance is less than 1000mm, adopting global filtering; when the sound path distance is detected to be larger than 1000 mm, local filtering is adopted, a punishment intensity reference value is estimated based on the noise level, the reference value is corrected in combination with the signal-to-noise ratio, and then a formula is substituted to calculate a punishment factor coefficient and a final punishment factor; in the iteration process, the relative variable quantity of the cost function is used as a convergence criterion, iteration is stopped when the variable quantity is smaller than a preset threshold value, and efficient and stable filtering is ensured; the method completely meets the engineering application requirements of industrial ultrasonic detection.

The invention discloses a large model calling system and method based on an MCP tool chain, and the method comprises the steps: receiving user input, and carrying out the preliminary matching of tools: querying whether the user input contains an entity in an entity database or not through a fuzzy matching technology, and carrying out the preliminary screening of a plurality of candidate tools based on a matching result, so as to obtain limited to-be-selected tools; user input is converted into semantic vectors, semantic matching is conducted in a vector database, and semantic similarities of all tools to be selected are ranked through a similarity calculation method; extracting key information in user input; abstracting the user input into a specified format; and matching the specified format with the historical workflow template, and if the historical workflow template is matched, replacing the key information to a corresponding position of the historical workflow template by adopting a structure-preserving parameter replacement algorithm to realize workflow reuse. According to the method and the device, a complete technical link from accurate tool screening to intelligent workflow multiplexing can be realized.

The invention provides a carbon emission calculation method and device based on power grid prediction, and the method comprises the steps: constructing a graph structure containing a plurality of nodes and edges based on the topological information and operation data of a power grid; the nodes and the edges respectively represent the connection relationship between the devices in the power grid; on the basis of the graph neural network model, feature extraction and information spreading are carried out on the graph structure, a prediction result is obtained, and the prediction result comprises state information of each node; a physical constraint mechanism is arranged in the graph neural network model, and the physical constraint mechanism is used for constraining a prediction result to conform to a physical rule of power grid operation; and outputting a prediction result conforming to the physical rule of power grid operation, thereby solving the problem that the prediction result in the traditional scheme is unavailable and uncredible in the key industrial field, enabling the prediction result to be seamlessly connected to the power grid dispatching and decision-making process with extremely high requirements on safety and stability, and improving the reliability of the power grid. Therefore, the practicability of the intelligent prediction technology of the power grid is greatly improved.

The invention discloses a measurement laboratory anomaly detection and diagnosis method, system and device based on deep learning and a medium, and relates to the technical field of anomaly detection and diagnos.The method comprises the steps that multi-source real-time data are collected and preprocessed; performing alignment processing based on sampling inconsistency among the data sources, and constructing unified data representation; generating a corresponding prediction result by using the prediction model; calculating a comprehensive abnormal score based on the aligned data and the prediction result; comparing the comprehensive abnormal score with a threshold value, and judging whether a comprehensive abnormal state exists or not; if the judgment result is abnormal, performing abnormal cause decoupling processing and causal inference to obtain a candidate root cause set; and inputting the candidate root cause set into a deep learning causal inference model to obtain an anomaly diagnosis result. A physical perception residual scoring mechanism is introduced, a comprehensive anomaly score is combined on the basis of anomaly detection, a weighted calculation method is adopted, and the contribution degree of each data source to an abnormal state can be accurately evaluated.

The invention provides an aviation nacelle part waviness automatic detection and evaluation method, and belongs to the field of product production detection, and the method comprises the steps: carrying out the protocol scanning of part surface contour features, and obtaining the undistorted coordinate point discrete point cloud data of the actual surface contour; filtering the point cloud data; obtaining a piece of flattened deviation value discrete point cloud data; obtaining a flattened deviation value continuous curve by adopting a general standard curve reduction method; extracting waviness components, and obtaining a curve center line; obtaining a crest value and a trough value participating in calculation; and calculating the maximum wave amplitude, the waviness and the slope for evaluating the waviness by using the wave peak value and the wave trough value. According to the method, the relation between the minimum cut-off wavelength of the waviness and the sampling interval is stipulated, the undistorted reduction of the surface profile curve is ensured, the influence of non-waviness profile components in the digital evaluation of the waviness is eliminated through a combined calculation method, and the evaluation accuracy of the waviness of the aviation nacelle part is improved.