265 results about "Superposition method" patented technology

The invention relates to the technical field of performance detection, and discloses a blade structure performance detection device and method, and the method comprises the steps: carrying out the laser ultrasonic scanning of a titanium alloy engine blade, and obtaining multi-mode spectrum feature data; performing parameter inversion and iterative optimization calculation according to the multi-modal spectrum characteristic data to obtain material parameter distribution data of a local area of the blade; performing annular scanning analysis on the titanium alloy engine blade based on the material parameter distribution data to obtain local structure feature data; performing modal decomposition on the local structure feature data to obtain fatigue damage accumulation data; and inputting the accumulated fatigue damage data into a dual decoupling diagnosis model for comparative learning and antagonistic feature separation to obtain a target diagnosis result, the method overcomes the limitation of a traditional linear superposition method, accurately predicts the fatigue damage evolution law under a complex load, effectively solves the problem of working condition interference, and improves the diagnosis accuracy. And the robustness and generalization of fault diagnosis are enhanced.

The invention provides a scene semantic occupancy prediction method based on probabilistic three-dimensional Gaussian, and the method comprises the steps: processing a multi-view camera image through employing a two-dimensional backbone network, generating multi-view and multi-scale image features, predicting the three-dimensional occupancy distribution aligned with pixels through the image features, and initializing the position attribute of the three-dimensional Gaussian according to the distribution; the method comprises the following steps: taking three-dimensional gauss as point cloud data, generating sparse voxel data through voxelization, and processing the sparse voxel data by using three-dimensional sparse convolution to complete feature interaction between the three-dimensional gauss; by using a cross attention mechanism, updating three-dimensional Gaussian features by image features; performing layer-by-layer iterative optimization on each attribute in the three-dimensional Gaussian features by using a Gaussian attribute fine tuning model; and aggregating geometric attributes and semantic attributes of the three-dimensional Gaussian by using a probability Gaussian superposition method, and generating a three-dimensional semantic occupation prediction result of the scene. According to the invention, the problem of efficient adaptive three-dimensional semantic occupancy prediction of an automatic driving scene can be solved.

The invention discloses a method for predicting the service life of a transformer in a high-proportion new energy access zone based on multi-physics field modeling, and the method comprises the steps: building an electromagnetic field-temperature field coupling simulation model based on a COMSOL simulation platform, and setting the electrical parameters, oil physical parameters and material physical attributes of the transformer; secondly, simulating a photovoltaic access working condition by utilizing a multi-power supply superposition mode, obtaining key data such as three-phase voltage, three-phase current, iron core magnetic flux density, oil temperature and winding temperature, calculating a life label based on a working state, and performing quantitative evaluation on the state of the transformer by adopting a health state scoring method; and finally, constructing a Perii-midFormer life prediction model to realize prediction of the residual life of the transformer. Compared with a traditional life evaluation method, the method fully considers the multi-physical field dynamic coupling effect caused by photovoltaic access, improves the adaptability and reliability of life prediction, and provides an important reference for the operation and maintenance of a transformer in a power distribution network.

The invention relates to the technical field of track bridge engineering, in particular to a high-speed railway track-bridge system earthquake-caused residual irregularity prediction method, which comprises the following steps of: determining a target object, and constructing an earthquake-caused irregularity database based on historical earthquake oscillation data of the target object; based on the earthquake-induced irregularity damage database, constructing an earthquake-induced peak irregularity deep learning prediction model fused with the vibration mode superposition method, and performing prediction by adopting the earthquake-induced peak irregularity deep learning prediction model to obtain an earthquake-induced peak irregularity prediction value; calculating an earthquake-caused residual irregularity equivalent coefficient based on earthquake-caused peak irregularity and earthquake-caused residual irregularity in the earthquake-caused irregularity damage database; and earthquake-caused residual irregularity is predicted based on the predicted earthquake-caused peak irregularity predicted value and the earthquake-caused residual irregularity equivalent coefficient. According to the method, the engineering safety and reliability of the result are ensured based on the mapping relation of the probability assurance rate, and the method has high efficiency and safety and is suitable for practical engineering application.

The invention discloses a multi-scale sea surface electromagnetic scattering calculation method and device based on marine environment elements and a storage medium, and belongs to the technical field of marine detection and physical remote sensing. The method comprises the following steps: calculating a tension wave sea spectrum according to an Elfouhail sea spectrum in combination with a Longuet-Higgins directional spectrum; a JONSWAP sea spectrum is combined with a Longuet-Higgins directional spectrum to calculate a gravity wave sea spectrum; superposing the tension wave on the gravity wave according to the slope by using a linear superposition method, and calculating a self-adaptive cut-off wave number; the contribution of small-scale waves to scattering is calculated by adopting an integral equation method, mirror scattering of large-scale waves is counted by adopting a Kirchhoff approximation method, and statistics and fusion are carried out on each scale wave according to the self-adaptive cut-off wave number, so that an electromagnetic scattering value is obtained. According to the method, a sea surface geometric calculation method based on real marine environment element driving is adopted, and accurate calculation is performed aiming at sea surface scattering characteristics under different sea conditions in combination with an integral equation method-Kirchhoff approximation electromagnetic scattering calculation model of an adaptive cut-off wave number, so that the calculation precision of scattering intensity is improved.

According to the information superposition method of the intelligent perception information in the virtual space provided by the embodiment of the invention, a data layering mechanism based on an importance weight is established by evaluating the information integrity and association degree of multi-source data such as images, temperatures and sounds. A hierarchical display buffer area is adopted to realize hierarchical management of information, and an interlayer visual effect is optimized in combination with marginal definition evaluation and a fuzzy processing technology. Intelligent superposition of multi-layer data is realized through contrast enhancement and transparency control, and a display refreshing strategy is dynamically adjusted based on data timeliness. According to the method, the problems of disordered display and visual interference when a traditional superposition scheme processes multi-dimensional perception information are effectively solved, and the information display quality in the virtual space is improved.

The invention relates to the technical field of unmanned aerial vehicle navigation and control, in particular to an improved sparrow searching method for three-dimensional unmanned aerial vehicle path planning. According to the method, a three-dimensional mountain terrain model is constructed through a Gaussian function superposition method, obstacles and no-fly zones are defined by adopting a cylindrical geometric model, and obstacle avoidance constraints, take-off and landing safety constraints and flight height constraints are set; a comprehensive cost function with path length, threat penalty, flight safety height and path smoothness as sub-targets is constructed, an improved sparrow search algorithm is introduced, and a sine and cosine strategy is adopted in discoverer position updating to dynamically balance horizontal exploration and vertical obstacle avoidance. A Levy flight mechanism is introduced in follower position updating so as to enhance the capability of local development and jumping out of local optimum; the method comprises the steps of population initialization, role division, iterative optimization, collision detection and an elitist retention strategy. According to the method, a safe and smooth three-dimensional flight path with the optimal comprehensive cost is output, and the method is suitable for an actual unmanned aerial vehicle navigation task.

The invention discloses a bridge service state monitoring and early warning method based on machine vision, and the method comprises the steps: firstly building a bridge numerical model through numerical analysis software, and then arranging a sensor to recognize the information of passing vehicles; before monitoring is started, a standard vehicle is selected and passes through a bridge along the center line of each lane, and the influence surface of each feature point is established by recording the vertical displacement of the feature point in the vehicle driving process; according to the vertical displacement influence surface of each feature point of the bridge and the identified vehicle information, calculating the vertical displacement of each feature point by using a superposition method; and finally, calculating the correlation between the actual measurement response and the theoretical value, and when the correlation of more than three feature points is lower than 95%, triggering an alarm to remind passing vehicles. According to the method, piezoelectric sensing and machine vision technologies are fused, and accurate inversion of vehicle loads and real-time evaluation of bridge structure states are realized through axle coupling dynamic response analysis and a data dual criterion mechanism.

The application discloses a curved surface structure zero state form finding method, comprising the following steps: (1) a model is established based on a design configuration, and deformation data is obtained by simulating the whole construction process; (2) a zero state configuration is deduced reversely: key node deformation values are extracted, arches are started, a simulation is re-performed after a linear model is fitted and adjusted, and iteration correction is performed until deformation error meets the requirement, and a zero state installation configuration is obtained; and (3) construction data is generated by extracting component line shapes and node coordinates. The application innovatively adopts an integral curvature adjustment strategy to replace a traditional node coordinate local adjustment mode, and through reverse deduction of 'construction simulation-control point arching-curved surface fitting-grid mapping', the problem of curved surface discontinuity caused by the traditional reverse superposition method is solved, construction precision and efficiency are significantly improved, and the application is suitable for intelligent construction of complex curved surface space grid structures.

The invention discloses a method for measuring the supply fairness of community old-age service facilities, and the method comprises the steps: obtaining the old-age service data of a community, carrying out the calculation and summation of the weights of four indexes, namely house type quality, activity space scale, environment greenness and service scale, and the normalized data, and obtaining an internal quality index; and evaluating the reachability score of the peripheral environment resource by adopting a Gaussian two-step mobile search method to obtain an old-age service supply index, and performing a superposition method on the internal quality index and the old-age service supply index to obtain a comprehensive score of the old-age service facility of each community. The Gini coefficient is used for calculating the comprehensive score accumulation proportion of the old people and the community old-age service facilities, the social environment space supply fairness is obtained, the community old-age service facility supply fairness is evaluated, the difference between communities is effectively reduced, and the community old-age service facilities are concerned and balanced.

The invention relates to the technical field of virtual-real fusion image processing, in particular to a target superposition method and system for augmented reality, and the method comprises the steps: firstly simulating to obtain a virtual route target, and superposing and fusing the virtual route target into an initial reality picture for guiding navigation; analyzing the change degree of the current reality picture, and judging whether the virtual target and the current reality picture need to be superposed, fused and updated or not; if yes, analyzing the similarity between the local areas of the current real picture and the reference picture, and preferentially matching the local areas; the relative displacement of the equipment is evaluated according to the matching result of the angular points in each local area, superposition fusion updating of the virtual target and the current real picture is carried out, a more accurate superposition fusion result of the virtual target is obtained, and the immersion and accuracy of a user during use are enhanced; and on the premise of ensuring the accuracy, the AR operation efficiency is effectively improved, the calculation delay is reduced, and the loss of equipment performance is reduced.

The invention discloses a blasting funnel volume solving method based on an improved physical information neural network. The method comprises the following steps: step 1, establishing a mechanical model of blast hole wall blasting load; 2, establishing a blasting physical model in which a columnar cartridge bag is equivalent to a spherical cartridge bag by using a Starfied superposition method; step 3, constructing a blasting funnel volume prediction model based on the wavelet multi-scale synchronous compression transformation enhanced physical information neural network, constructing a solution space of a physical field by using the wavelet multi-scale synchronous compression transformation, and training the physical information neural network in which a blasting funnel physical control equation, an initial condition and a boundary condition are loss functions; and 4, intelligently predicting the volume of the blasting funnel by adopting the trained enhanced physical information neural network. The trained physical information neural network enhances the robustness and generalization ability of the blasting funnel volume prediction model, and provides high-precision theoretical support for blasting design optimization in engineering blasting.

The invention provides a four-feed-source four-polarization holographic metasurface antenna based on position weighted impedance superposition, which comprises a radiation array and four feed sources, and is characterized in that the radiation array comprises M * N radiation units which are periodically arranged and are provided with I-shaped gaps in an etching manner and are of a circular patch structure; the radius of the radiation unit is determined by the maximum equivalent scalar impedance obtained by performing weighted impedance superposition on tensor surface impedance distribution obtained when single polarized electromagnetic waves are generated by taking different feed sources as centers; the inclination angle of two transverse arms of the I-shaped gap relative to the X axis is the same as the propagation direction of electromagnetic waves corresponding to the maximum equivalent scalar impedance. According to the holographic metasurface antenna, the utilization efficiency of the radiation unit on the surface waves is effectively improved through the position weighted impedance superposition method, interference among different polarization components is reduced, the defect that the aperture efficiency is low due to the fact that a traditional impedance superposition method is adopted by the holographic metasurface antenna is overcome, and the aperture efficiency of the holographic metasurface antenna is improved by exciting the four feed sources respectively. And generation of four kinds of polarized electromagnetic waves is realized.

The invention discloses an electron beam bunch superposition method and device, and the beam bunch energy of the head part and the tail part of an electron beam bunch is different by adopting a beam energy absorption effect. And then a plurality of alpha magnets are utilized, so that the movement path of the high-energy beam bunches at the head of the beam bunch string is long, the movement path of the low-energy beam bunches at the tail of the beam bunch string is short, and longitudinal superposition and compression of the beam bunch string are achieved. And the alpha magnet can simultaneously realize an achromatic function, so that the transmission envelope after the beam bunch is compressed and superposed is not greatly increased. And the obtained shorter pulse beam can be used for scientific research application such as nuclear data measurement.

The invention discloses an external rotor permanent magnet synchronous motor noise prediction method, system and device and a medium, and relates to the technical field of motor noise, and the method comprises the steps: building a two-dimensional electromagnetic model of an external rotor permanent magnet synchronous motor ERPMSM; analyzing the spatial distribution and frequency characteristics of the electromagnetic force acting on the surface of the permanent magnet through the two-dimensional electromagnetic model to obtain the electromagnetic force; establishing a three-dimensional structure model of the ERPMSM, and loading the electromagnetic force into the three-dimensional structure model in a nodal force form to obtain a nodal force acting on the surface of the permanent magnet in a three-dimensional space; based on the three-dimensional structure model and the nodal force, the radial vibration acceleration of the ERPMSM outer rotor is calculated by adopting a mode superposition method; and taking the radial vibration of the outer rotor as an acoustic boundary condition, and predicting the noise of the ERPMSM by using an acoustic boundary element method.

The invention relates to the field of audio signal processing, in particular to a multi-channel audio signal hybrid coding method and device and a storage medium, and the method comprises the steps: collecting digital audio signals through a plurality of audio input channels, carrying out the anti-aliasing filtering of the collected digital audio signals, so as to obtain audio signals in a 48kHz / 16bit format, and outputting the audio signals in the 48kHz / 16bit format. An audio signal in a 48kHz / 16bit format is processed through a loudness weighted average method, the audio signal after loudness weighted average is processed through a frequency domain mixing technology to obtain a mixed signal, and dynamic range compression is performed on the mixed signal based on calculation of an auditory masking curve to obtain a compressed signal. And carrying out hybrid coding on the compressed signal to obtain a compressed data stream, and packaging and outputting the compressed data stream. Through dynamic mixing and compression processing, the problem of signal distortion caused by a traditional linear superposition method is effectively solved, reasonable superposition of all paths of signals is ensured through dynamic mixing, and level overload caused by simple addition is avoided.

The invention belongs to the technical field of robot path planning, and provides a mobile robot path planning method and system based on an adaptive RRT * algorithm, and the method comprises the steps: initializing a multi-tree structure based on an expansion superposition method and clustering analysis; determining a dynamically adjusted sampling area by adopting a self-adaptive sampling strategy; new nodes are generated in the sampling area, collision detection is carried out on the new nodes, if the new nodes do not collide with obstacles, the new nodes are incorporated into a tree structure, and path optimization operation including father node reselection and rewiring is executed; the connection possibility among the multiple trees is checked regularly, when the starting point tree and the target tree are connected through the guide tree and a feasible path is detected, a complete initial path is extracted, and the sampling area is updated after the path is optimized; evaluating the path cost of the new node and the target point, and if the path cost meets the precision requirement or reaches the maximum number of iterations, terminating the search and outputting the current optimal path; otherwise, continuing to optimize. According to the invention, the adaptability and efficiency of a path planning algorithm in a complex environment are improved.

The present invention discloses a hybrid active noise cancellation superposition method based on a neural network, including: W f W(n) or / and W b (n) is implemented by a linear filter FIR or IIR, and the filter parameters are iterated according to the LMS or RLMS algorithm. Since S(z) is non-linear, S’(z) can still be estimated by a neural network, and the parameters of the neural network are iteratively solved according to the BP algorithm. For the non-linear link existing in the path of the original noise propagation from the A-bit noise source to the B-bit speaker, such as the case where the original noise is too large, resulting in non-linearity of the device, if the feedforward filter can use a non-linear filter, it can better control the noise; for the non-linear link existing in the control channel from the C-bit error microphone to the B-bit speaker, such as the non-linearity of the error microphone or the non-linearity of the amplifier, if the feedback filter can use a non-linear filter, it can better control the noise.

The embodiment of the invention discloses a watermark superposition method and device, equipment and a medium. The method comprises the following steps: acquiring a visual field image acquired by an image acquisition device, and determining at least one candidate static region in the visual field image; determining at least one target static region from the candidate static regions according to watermark parameters of a watermark to be superposed, and taking the target static region as a watermark superposition region; determining a coding block division mode according to the position information of the superposed watermark region, so as to obtain a block video stream corresponding to the original video stream according to the coding block division mode; and obtaining a target part image from the block video stream based on the position information of the watermark overlapping area, and performing watermark overlapping on the target part image. According to the technical scheme, the watermark information can be superposed under the condition that the performance of the server is not greatly reduced, the resource consumption during watermark superposition is effectively reduced, the watermark superposition cost is reduced, and the watermark superposition efficiency is improved.

The invention provides a heavy truck liquid cooling overcharging topology dynamic optimization method and system, and relates to the technical field of heavy truck liquid cooling overcharging, and the method comprises the steps: generating time-space thermal load distribution through a transient thermal load equation, and recognizing a thermal aggregation region coordinate set; generating a runner diameter grading mapping table; an objective function and constraint conditions of topological optimization are defined, a topological optimization algorithm is selected, parameters are set, and an optimal topological structure of the cold plate channel is obtained; an optimal topological structure is adopted, a fatigue life map is calculated through a modal superposition method, and meanwhile a thermal runaway risk matrix is quantified; and according to the fatigue life map, the thermal runaway risk matrix and the sensitivity field, establishing a dynamic adjustment health degree model of the cold plate channel, and outputting an optimized flow channel topology and a parameter set. The method has the beneficial effects that the service life of the battery pack is effectively prolonged, the maintenance cost is reduced, and the overall performance and the economic benefit of the liquid cooling overcharging system of the heavy truck are improved.

The invention discloses an image data superposition method and system, electronic equipment and a storage medium, and relates to the field of data processing. The invention provides a system hardware structure for TDI data superposition. The total stage number of a cache region is calculated by using the ratio of pixel row intervals to pixels in an image sensor and the number of light sources; overlapping row pixel data output by the image sensor with data in a final-stage cache region or a middle cache region in the data cache module, and inputting the overlapped data into the next data cache module; after each row of pixels are overlapped, data in the cache regions flow downwards step by step, data in the last-stage cache region are input into the middle cache module, and all the data cache modules correspond to different pixel rows one by one. Therefore, TDI superposition of the row pixel data in the image sensor can be realized, the spatial position corresponding to the cache region does not need to be calculated, and the image data superposition efficiency is improved.

The invention discloses an improved DMO topological optimization method obeying different material yield criteria and analysis equipment, and belongs to the technical field of engineering structure optimizing.The method comprises the steps that a topological optimization mathematical model is established with the minimum flexibility as an objective function and stress constraints and cost constraints of different yield criteria as constraint functions; the interpolation of the DMO method based on the elastic tensor is rewritten into a unit superposition method to carry out unit discretization rigidity interpolation, and a plurality of stress values of each unit of each material can be calculated by using a separable stress interpolation scheme based on the unit superposition method; finite element analysis and stress calculation are carried out on the structure, von-Mises and Ducker-Prager yield criteria are given to steel and concrete materials respectively, and an MMA algorithm is used for iteratively calculating a result to obtain an approximate optimal solution; and circularly iteratively updating the unit density and the solving steps until the new topological optimization structure reaches a preset convergence condition. According to the method, topological optimization of the steel-concrete composite structure is more accurately carried out, and the obtained topological optimization result has manufacturability.

The invention relates to a short-term wind power prediction method based on clustering optimization analysis, and the method comprises the steps: obtaining a prediction data set and a field group historical data set of an original wind power plant (one-field one-measurement), and carrying out the data preprocessing, and obtaining two types of data sets with higher credibility; obtaining an optimal clustering wind field division region by using the processed field group historical data set and combining with an AP clustering algorithm after PSO particle swarm optimization; according to the division result of the optimal clustering wind field, the prediction data sets of the sub-region wind fields are loaded into a BP neural network model, meanwhile, the correlation coefficients of the wind power plant output and the wind power plant group output are utilized, values are assigned to the corresponding wind power plants to serve as weights, and finally wind power plant refined group short-term wind power prediction is obtained. Compared with a traditional superposition method and a single BP neural network, the method has the advantage that the prediction precision is improved in 24-hour day-ahead prediction. It can be indicated that the model has excellent prediction performance and has certain reference significance in future development of wind power cluster power prediction.

The invention provides a data acquisition method of a rock fracture acoustic emission signal identification model. The data acquisition method comprises the following steps: acquisition of a pure rock fracture signal, acquisition of a noise signal, data preprocessing and generation of a synthetic monitoring signal. According to the data acquisition method of the rock fracture acoustic emission signal identification model provided by the invention, a multi-level signal superposition method is provided by systematically combining a physical simulation experiment, noise signal acquisition and a signal synthesis technology, and the method can generate representative and diversified training data, so that the data acquisition accuracy is improved. The method can significantly improve the recognition precision of a deep learning model on rock fracture signals in a complex noise environment, enhances the generalization performance of the model, and provides a solid technical support for rock burst prediction and prevention and control.

The invention discloses a coding and decoding processing method and device, and the method comprises the steps: a transmitting end obtains a basic parameter of an RM code and a plurality of to-be-processed information bits, determines a bit index set according to a predefined superposition proportion, a superposition mode and the basic parameter, carries out the coding of the to-be-processed information bits according to a preset coding mode and the bit index set, and carries out the decoding of the to-be-processed information bits. The preset coding mode is determined by a preset partially superposed Plotkin recursive structure or a corresponding generation matrix, modulating the coded code word, and sending the modulated signal to a receiving end through a channel, so that the receiving end performs channel decoding on the demodulated information through a preset decoding algorithm and outputs the demodulated information.

The invention discloses an AR label dynamic superposition method and device based on an unmanned aerial vehicle real-time video stream. The method comprises the steps that S1, an unmanned aerial vehicle collects video data in real time and preprocesses the video data to obtain a preprocessed video stream; s2, obtaining a video picture-geographic coordinate mapping table based on registration of video pictures and geographic coordinates of the preprocessed video stream; s3, generating an AR label based on the video coverage area of the preprocessed video stream; s4, converting the geographic coordinates of the AR labels into pixel coordinates of the video pictures according to the video picture-geographic coordinate mapping table to realize AR label superposition; and S5, outputting the video stream which displays and overlaps the AR label in real time. According to the method, sub-meter registration of the AR tag and the video picture is realized, accurate synchronization of the AR tag and the video picture is realized, real-time following of the moving target and collaborative display of multiple types of tags are realized, and comprehensiveness and decision-making efficiency of monitoring information are remarkably improved.

The invention provides a method and system for improving polymorphic warping of a wafer, and the method comprises the steps: 1), measuring the initial warping morphology of the wafer, and obtaining deformation distribution data; (2) calculating three-dimensional deformation of wafer warping through a finite element simulation model, and on the basis of the three-dimensional deformation, optimizing parameters of a stress film on the back surface of the wafer through a linear superposition method on the basis of the actually measured deformation distribution data, so that the stress film generates deformation distribution opposite to the initial warping morphology; 3) preparing an arch-shaped stress film on the back surface of the wafer; 4) measuring deformation distribution data of the optimized wafer; according to the method, initial deformation of various types can be counteracted, warping generated in specific steps in the production process can be reduced to the maximum extent, and the product quality and reliability requirements are fully guaranteed.

The invention provides an oil paper insulation temperature normalization method based on a Dissado-Hill model, the Dissado-Hill model is utilized to analyze an FDS curve, an activation energy theory is analyzed through a double-barrier model, frequency temperature translation factors of different polarization processes and conductance processes in the Dissado-Hill model are provided, and finally all components are superposed at a standard temperature to restore the FDS curve at the standard temperature. A Dissado-Hill model parameter is solved by using an FDS spectral line so as to characterize the oil-paper insulating medium, and the Dissado-Hill model considers the interaction between dipoles in the dielectric medium and has practical physical significance; the components of different polarization processes and conductance processes in the FDS spectral line are restored through the obtained parameters of the Dissado-Hill model, the barrier height conditions of the different components are researched, the different components are restored to the standard temperature from the test temperature, and the FDS spectral line fitting goodness obtained through the final superposition method is higher.

The invention discloses a gear forming grinding contact area temperature field calculation method based on a single-abrasive-particle cutting heat production mechanism, and the method comprises the steps: firstly, calculating the undeformed cutting thickness according to the geometric contact relation between abrasive particles and a tooth surface, and judging that the abrasive particles are in a scraping, ploughing or cutting stage; then, the heat flux density generated by each abrasive particle is calculated in stages, the proportion of heat transmitted into the workpiece is determined according to a dynamic heat distribution mechanism, and then the heat flux density distribution of a contact area is obtained through fitting; and finally, on the basis of a moving heat source model and a point heat source superposition method, a temperature field of the gear forming grinding contact area is constructed and solved. According to the method, the limitation that a traditional model adopts fixed heat flow distribution is overcome, accurate prediction of the grinding temperature field is achieved from the physical mechanism level, and a key theoretical basis is provided for effectively controlling tooth surface heat damage and improving gear machining quality.

The invention relates to the technical field of air quality monitoring, and discloses an air quality monitoring method based on an olfactory chip, which comprises the following steps: step 1, selecting and optimizing a gas-sensitive material, the optimization process comprises the steps of adjusting the surface structure of the gas-sensitive material and carrying out functionalization treatment, so that the gas-sensitive material can interact with target gas molecules, the performance of the gas-sensitive material is optimized by adjusting the specific surface area and the electronic structure of the gas-sensitive material; and step 2, after the optimization of the gas sensitive material is completed, applying the optimized gas sensitive material to a sensor array, and constructing a multi-modal sensor array. A quantum inference network is combined with a quantum state superposition method to process output signals of a sensor array, information coding in a high-dimensional space is realized, the distinction degree of gas characteristics is enhanced, a gas concentration prediction effect is obtained, and the problem that a traditional method is high in misjudgment rate in a data uncertainty environment is solved.