30results about How to "Drift suppression" patented technology

The invention provides a temperature control method of an intermediate infrared laser, and relates to the technical field of lasers. The temperature control method comprises the steps that the reference temperature T0 of the intermediate infrared laser is set, and driving current is injected into the intermediate infrared laser; in any nth period of the driving current, initial temperature parameters of the intermediate infrared laser are collected, and an initial temperature control curve T (n) of the nth period is formed; forming a reference temperature curve T1 (n) in the nth period based on the initial temperature control curve T (n); forming a gradient temperature control curve of the nth period based on the initial temperature control curve T (n), the reference temperature curve T1 (n) and the reference temperature T0; and forming temperature control data based on the gradient temperature control curve, and storing the temperature control data in the temperature control device, so that the temperature control device performs temperature control on the intermediate infrared laser according to the temperature control data. The invention further provides electronic equipment and a temperature control device.

This invention discloses a miniature flow sensor and an on-chip constant temperature difference control circuit for the flow sensor. The circuit includes a first resistor, a second resistor, an ambient resistor, an adjustable resistor, a micro-heater, an operational amplifier, a start-up resistor, and a start-up power supply. The ambient resistor and the micro-heater have the same temperature coefficient. One end of the first resistor is connected to one end of the second resistor and the output terminal of the operational amplifier. The other end of the first resistor is connected to one end of the start-up resistor, one end of the adjustable resistor, and the positive input terminal of the operational amplifier. The other end of the second resistor is connected to one end of the micro-heater and the negative input terminal of the operational amplifier. The other end of the start-up resistor is connected to the positive terminal of the start-up power supply. This constant temperature difference control circuit effectively maintains a constant overheating temperature of the micro-heater, thereby achieving a wide measurement range, low power consumption operation, and suppressing drift caused by ambient temperature, significantly improving the accuracy of the measurement results.

The application discloses a method for measuring a detection tilt angle of a two-component atomic shearing interferometer, constructs a tilt angle set of a swing angle device; the angle of a mirror is turned between the time when atoms are subjected to the action of a pi Raman laser and a second pi / 2 Raman laser; a plurality of groups of odd number and even number are alternately detected; all tilt angles in the tilt angle set are traversed; and the actual included angle of the longitudinal direction of a CCD camera imaging surface relative to the Z-axis direction is calculated by fitting. The application also discloses a measuring device for the detection tilt angle of the two-component atomic shearing interferometer. The application enables the current atomic shearing interferometer to accurately measure the tilt angle of the detection system, thereby solving the problems of noise and system error caused by the non-zero return of the tilt angle of the detection system of the atomic shearing interferometer, and suppressing the drift of the differential measurement of the two-component atomic interferometer caused by the change of the tilt angle.

The present application relates to the technical field of feeding and dosing device, especially relates to an automatic feeding and dosing device for anti-blocking granular ammonia-nitrogen removing agent and a feeding method thereof. The automatic feeding and dosing device and the feeding method thereof are aimed at solving the technical problems that the labor intensity of workers is large, dust is harmful to human body, the continuity and uniformity of dosing cannot be guaranteed, and the saving of reagent is not conducive in the prior art. The present application provides an automatic feeding and dosing device for anti-blocking granular ammonia-nitrogen removing agent, which comprises a supporting column, a material bin, a lifting control device, a guide assembly, an outer dust cover, a rotary control assembly, a sealing cover plate, a limiting seat, a screen, a flexible knocking assembly, a power device, a spraying pipe, a nozzle and a discharging adjusting assembly. The present application adopts a crane to automatically feed the ammonia-nitrogen removing agent, ensures the continuity and uniformity of dosing of the ammonia-nitrogen removing agent, saves the amount of the ammonia-nitrogen removing agent, effectively suppresses dust dispersion through spraying, and reduces the harm to human body.

The application discloses a power assisting curve self-adaptive generation method and system based on riding habit learning, relates to the field of intelligent control of electric power assisting bicycles, and comprises the following steps: establishing a riding habit library based on historical riding data of target riders, and storing a pedaling force habit center and a pedaling frequency habit center representing long-term pedaling behavior characteristics of the riders; collecting multi-source real-time sensing data such as pedal torque, pedaling frequency, vehicle driving state and battery state in real time; constructing a comfort envelope model through the pedaling force habit center and the pedaling frequency habit center, and calculating a comfort coefficient; generating comprehensive control indexes in combination with the comfort coefficient, the vehicle driving state and the battery state data, dynamically adjusting the shape parameters of a basic power assisting function, generating a self-adaptive power assisting curve matched with a current riding scene, and then determining a motor power assisting torque instruction and outputting the motor power assisting torque instruction to a motor controller. In this way, the individualized coordination and coupling of man-machine torque aiming at natural pedaling force performance of the riding user habits are realized.

This invention discloses an underwater range-gated dynamic imaging method based on metaheuristic attitude estimation, belonging to the field of underwater imaging technology. The method includes: constructing an underwater range-gated laser imaging system; acquiring a continuous, spatiotemporally matched sequence of original scanned images by synchronously controlling laser emission, scanning, and gated exposure; selecting reference frames from the original scanned image sequence and determining the effective imaging region; modeling inter-frame rigid body motion using six-degree-of-freedom pose parameters; constructing a global optimization objective function based on gray-level mean square error; and designing an adaptive weighted pixel loss function, assigning weights to pixels by normalizing gray-level and gradient information to suppress the influence of bright areas. This invention applies metaheuristic optimization ideas to the 6D pose estimation problem of underwater range-gated laser imaging, constructing a 6D pose optimization framework suitable for highly sparse and highly constrained scenarios based on PSO, overcoming the fundamental challenges of feature point scarcity and insufficient datasets.

The invention discloses a dynamic modeling analysis system for combustion atmosphere data of a biomass oxygen-enriched combustion boiler, and relates to the technical field of dynamic modeling analysis. The system comprises a working condition self-adaptive feature extraction module, a time sequence maintaining model training module, an online self-adaptive correction module and an incremental model updating module. Through a working condition adaptive feature extraction module, a time sequence maintenance model training module, an online adaptive correction module and an incremental model updating module, adaptive feature vectors are generated through feature extraction, a basic model is obtained through training, and online correction and incremental updating are performed by combining feature vector verification threshold judgment. And finally, iterative upgrading is completed through an incremental learning fine tuning model, the reliability of dynamic modeling analysis of the combustion atmosphere data of the biomass oxygen-enriched combustion boiler is improved, and the problem that in the prior art, the reliability of dynamic modeling analysis of the combustion atmosphere data of the biomass oxygen-enriched combustion boiler is low is solved.

The invention discloses an air compressor cluster cooperative control and energy efficiency optimization method based on digital twinning, and the method comprises the following steps: collecting the real-time operation data of an air compressor cluster and an air supply system, and carrying out the time alignment, and obtaining the time alignment data; establishing a digital twinborn model of the air compressor cluster air supply system; the method comprises the following steps of: constructing a Zonotop observer to obtain an initialized coupling Zonotop; generating a candidate group control strategy set in the rolling optimization window; a reachable domain propagation operator is called to execute prediction updating, and prediction coupling Zonotop is obtained; consistency shrinkage is executed, and an updated coupling Zonope is obtained; and loading each candidate group control strategy to the digital twinborn model, executing simulation deduction, selecting an optimal control strategy from the candidate group control strategy set, and issuing the optimal control strategy to an air compressor cluster execution control system for execution. The feasibility and the stable energy-saving effect of the air compressor cluster cooperative control strategy are improved.

This invention discloses a control method, system, device, and storage medium based on inertial sensor attitude calculation, including: acquiring acceleration and angular velocity; calculating motion attitude data based on acceleration and angular velocity; calculating the relative attitude angle change from the motion attitude data; mapping the relative attitude angle change to relative directional displacement to obtain relative directional displacement data and sending it to the host. This application utilizes the feature of existing smart wearable devices equipped with inertial sensing units to convert motion attitude into relative attitude angle changes, providing an attitude calculation method. This application can use BLE wireless transmission, balancing mobility and portability, making it suitable for wearable devices such as smart glasses. Furthermore, this application introduces complementary filtering, dead zone, and output filtering steps into the attitude calculation method, improving the accuracy of attitude calculation. It also adds an automatic calibration step, which can suppress drift and jitter, reducing the false touch rate.

This invention discloses a method for the collaborative restoration of structure and texture in Dunhuang murals based on structural uncertainty, belonging to the field of image restoration technology. The method includes: a structure prediction step, which generates a structure reconstruction result through an encoder-decoder architecture based on codebook quantization and simultaneously outputs pixel-level structural uncertainty parameters; a texture reconstruction step, which models the texture completion process as texture flow propagation on a graph structure and adaptively adjusts the propagation range and constraint strength according to the structural uncertainty parameters; and a fusion step, which fuses structural features and texture features at multiple scales and dynamically adjusts the fusion strength according to the structural uncertainty parameters to generate the final restoration result. This invention achieves effective linkage between structure prediction and texture reconstruction through structural uncertainty parameters, suppressing the transmission of structural errors to the texture generation process when there is large-area damage or severe information loss, while maintaining overall consistency and natural detail, making it suitable for the digital restoration of Dunhuang murals.

The invention relates to the field of phase-change switches, and provides a preparation process of a phase-change material layer in order to solve the problem that an existing phase-change material layer is initially in a high-resistance state and needs to be electrically initialized, and the preparation process comprises the following steps: S100, preparing a GeTe phase-change film through a photoetching process and a magnetron sputtering process; s200, preparing a phase change material layer from the phase change film through an annealing process; the initial vacuum degree of the annealing process is lt; the pressure is 5 * 10 <-2 > Pa, the annealing temperature is 280-350 DEG C, and the heating rate is 1t; the temperature is 20 DEG C / min, and the annealing time is gt; the time is 20 minutes. According to the invention, the first-time electric stress impact is eliminated, the destructive first-time switching operation is fundamentally avoided, the device enters a working state from the beginning under mild and uniform heat treatment, the generation of initial defects is greatly reduced, and the initial point of phase change fatigue is delayed, so that the recyclable operation life of the device is remarkably prolonged; according to the device provided by the invention, the first switching operation is omitted, the complexity of driving circuit design of the chip and the cost of chip test are reduced, and the design and test are simplified.

The invention discloses a method for improving the reliability of a phase delay film and the phase delay film, and belongs to the technical field of optics. According to the invention, the sulfur-sulfur alkyl chain-containing compound is adopted to perform molecular modification on the phase delay film, so that the adsorption and invasion rate of the phase delay film to water molecules can be reduced, and polymer swelling, plasticizing and hydrolysis effects caused by water vapor can be reduced; thermal motion of a polymer molecular chain in a high-humidity and high-temperature environment is inhibited, internal stress release and microstructure change are reduced, and then the problems of phase delay value drift, haze rising and surface physical degradation of the phase delay film in the high-humidity and high-temperature environment are solved; and the optical stability and the mechanical stability of the phase delay film in a high-humidity and high-temperature environment are improved.

This invention discloses a low-voltage fire-resistant intelligent fire-fighting cable with distributed temperature measurement and positioning function, belonging to the field of fire-fighting cable technology. It includes a cable body comprising an insulated core, an oxygen barrier layer, a shielding layer, and an outer sheath. The insulated core, from the inside out, includes a conductor layer, a fire-resistant layer, and an insulation layer. The conductor layer is formed by multiple strands of fine copper wire twisted together. The insulation layer comprises cross-linked polyolefin. A filling layer is provided at the gaps between the insulated cores, and a temperature sensing unit is also provided within the filling layer. The temperature sensing unit includes a fiber optic temperature measurement structure, which can acquire temperature distribution information along the cable. A drain wire is provided within the shielding layer. Through this invention, the temperature sensing unit, employing a distributed fiber optic temperature measurement structure arranged along the cable axis, allows the fiber optic cable to be deployed synchronously along the entire length of the cable during the cabling process, achieving continuous temperature acquisition and distributed sensing along the cable, thereby acquiring temperature distribution information for the entire line and identifying local temperature rise changes.

The invention provides an incremental SfM reconstruction method based on relative orientation uncertainty, and relates to the technical field of computer vision, and the method comprises the steps: obtaining a plurality of to-be-reconstructed images, calculating the relative orientation uncertainty index between each pair of images in the plurality of images, and calculating the relative orientation uncertainty index between each pair of images in the plurality of images; the relative orientation uncertainty index is calculated based on the minimum singular value of the relative orientation coefficient matrix; images are used as nodes, connection relations between the images are used as edges, each edge is endowed with a weight to construct an undirected graph model, and the weights are in negative correlation with relative orientation uncertainty indexes; selecting a node with the highest weight and an adjacent node with the lowest relative orientation uncertainty index of the node to form an initial image pair, and resolving an initial relative pose; and selecting a node with the lowest relative orientation uncertainty index from the alternative nodes connected with the current model, adding the selected node into the model, resolving the camera pose of a newly added image, gradually adding the image until all the images are added, obtaining a reconstruction path with the lowest uncertainty, and further completing model reconstruction.

The present application relates to the technical field of lithium battery, specifically, a kind of abnormal impedance analysis method and system for lithium battery storage location probe.The method includes, establish structured database, structured database includes structured data sequence;Select structured data sequence from structured database, construct sample space;Each structured data sequence in sample space is carried out curve reconstruction, establishes voltage-time curve, current-time curve and capacity increment curve;Voltage-time curve, current-time curve and capacity increment curve are carried out feature extraction, and construct multi-dimensional feature sequence with multiple feature dimensions;Based on multi-dimensional feature sequence, whether each structured data sequence in sample space exists abnormality is judged.The system is used to realize the method.The present application can realize the analysis detection of the abnormal impedance of the lithium battery storage location probe corresponding to each working channel based on the operation data of each working channel at the same time.

The application discloses an unmanned ship autonomous departure control method. The method comprises the following steps: data acquisition and preprocessing, collecting expert data of manual departure in multiple scenes, and cleaning and extracting features of the expert data; imitating learning initializes a departure control strategy, training the preprocessed data based on a behavior cloning method, optimizing the training process by defining a loss function, monitoring the strategy generalization ability by using evaluation indexes, and obtaining an initial departure control strategy; reinforcement learning optimization and cyclic iteration, designing a dynamic adaptive reward function integrating multiple targets, optimizing the initial departure control strategy by using an SAC algorithm, triggering transfer learning fine-tuning combined with environmental state changes, and realizing cyclic iteration and update of the control strategy. The application constructs a data-driven closed-loop framework, significantly improves the self-adaptive ability, control accuracy and generalization ability of the unmanned ship to the dynamic environment, and balances the departure safety, operation efficiency and energy consumption economy.

The application discloses an intelligent inspection robot system based on 5G communication and a control method thereof, relates to the technical field of industrial automation and intelligent inspection, and comprises three parts of a mobile robot platform, a remote control terminal and a cloud server; the mobile robot platform serves as a core execution unit and comprises a main control unit; an STM32F103ZET6 is used as a core processor, and is responsible for multi-sensor data fusion, logic control of each module and instruction analysis and execution; test results show that, in the 5G mode, the average transmission delay of sensor data and control instructions is only about 92 ms, the video stream delay is about 200 ms, and there is no freezing and packet loss phenomenon; compared with a traditional WiFi or 4G scheme, the application effectively solves the problems of high transmission delay, short distance and insufficient signal stability, and truly realizes remote real-time monitoring and high-speed data backhaul across regions, and meets the strict requirements for remote control in an industrial high-risk scene.

The invention relates to the technical field of intelligent manufacturing, in particular to an intelligent efficient heat preservation graphene plate manufacturing method which comprises the following steps: monitoring transient response values of functional particles in graphene composite slurry, obtaining a dielectric constant change rate, constructing a ratio function curve, adjusting an electric field inversion rate and judging abnormity, and generating particle orientation distribution. The method comprises the steps of constructing a dynamic coupling mechanism of a dielectric constant change rate and an alternating electric field frequency, restraining migration and identifying a heat conduction path, simulating a thermal channel focusing structure, calculating a combined load and triggering collaborative scheduling, and generating a reordering scheduling queue. According to the method, the optimal spatial configuration is established to enhance the absorption capacity of far infrared waves in a specific frequency band, and the manufacturing efficiency and the functional response density of the plate are improved on the premise of ensuring the forming consistency of the microstructure by combining with an equipment load collaborative scheduling mechanism.

The invention discloses a non-aligned visible light-thermal infrared video target detection method based on multi-modal basic model guidance, and the method comprises the steps: carrying out the feature extraction of an original visible light image and an original thermal infrared image in the same group through a multi-modal basic model encoder, and obtaining the respective modal representation; the two-stage progressive aligner is used for completing coarse-to-fine explicit alignment of the thermal infrared image relative to the visible light image on the pixel level and the image level of two modals, so that a fine-aligned thermal infrared image is obtained. And then carrying out basic model guided alignment consistency constraint on the fine alignment thermal infrared image and the original visible light image, finally realizing multi-modal fusion under receptive field difference by using a thermal infrared to visible light fusion module, and outputting a final detection frame. According to the method, modal difference is broken through large-scale pre-training prior knowledge, dependence on registration data is avoided, visible light-thermal infrared image alignment is achieved more efficiently and stably, and the method is excellent in performance in downstream detection tasks.

The application discloses a kind of photographic unmanned aerial vehicle stabilizing gimbals adaptive robust constraint following control method, belong to unmanned aerial vehicle control technical field, comprising: first based on establishing gimbals system kinematics model, through Lagrange equation construction includes all working condition dynamics model with uncertainty and disturbance;Photographic lens desired trajectory is converted into second-order constraint equation, and a constraint tracking error index is constructed;Design includes nominal control item and adaptive robust compensation item Compound controller, solve servo constraint force, while embedding fixed threshold anti-shake strategy;Unknown uncertainty of system is estimated in real time by adaptive law with leakage term, and control compensation strength is updated;Finally, the system stability is verified by Lyapunov theory, and simulation and physical testing are completed.The application improves the gimbals trajectory tracking accuracy and motion stability, solves the problem of weak control buffeting, weak anti-interference ability and parameter drift in the prior art, and has strong engineering practicability.

The application provides a kind of inverter DC welding machine feedforward high-precision feedback control system and method, it is related to inverter DC welding machine control technical field.The voltage sampling end of the system is set between full-bridge rectifier module and output reactor, and the current sampling end is set between output reactor and output terminal.The application effectively avoids inductance back electromotive force and cable voltage drop interference by placing voltage sampling point in front of output reactor, significantly improves feedback sampling accuracy by combining isolated sampling and anti-interference filter circuit;At the same time, a feedforward compensation module is introduced, which calculates the reactor and cable voltage drop in advance according to the real-time welding current and adds it to the control signal to form a "feedforward compensation + high-precision feedback" dual mechanism cooperative control.The application has fast dynamic response speed, strong anti-interference ability and high steady-state control precision, and can meet the demand of high-precision MIG / MAG welding process.

The application discloses a kind of based on component wave fluctuation characteristic flow time dynamic measurement method and system, belong to fluid parameter measurement technical field, including, S1, along the flow direction, in flow channel arrangement first component analyzer and second component analyzer, real-time acquisition target component concentration or content time series data in flowing medium;S2, from target component, select the component with significant random fluctuation characteristics as characteristic component, with its concentration value or calculated value form the fingerprint-like time series with random fluctuation characteristics;S3, to the characteristic component fingerprint-like time series measured by two component analyzers, time shift correlation analysis or dynamic time warping analysis is carried out, and the time offset corresponding to the maximum correlation value between them is determined;S4, time offset is determined as the flow time of flowing medium between first component analyzer and second component analyzer.The application can improve the precision and reliability of flow time measurement under complex industrial environment.

The invention provides a VHF and IP voice converged communication method and device for a special ship. The method comprises the following steps: monitoring environment temperature and electromagnetic interference intensity in real time; a pre-stored antenna parameter compensation library is matched based on the environment temperature, and radio frequency front end transmission parameters are dynamically optimized; and performing multi-modal noise suppression on the received VHF audio signal, wherein the multi-modal noise suppression comprises the following steps of: generating a time-frequency mask based on electromagnetic interference intensity by adopting a complex convolution attention network to suppress electromagnetic interference; and converting the processed signal into an IP voice data packet, and reversely converting the IP voice data packet into a VHF signal through a protocol conversion engine to realize a bidirectional communication link. The voice communication quality and reliability in the polar region environment are improved, and the navigation safety is guaranteed.

The present disclosure provides a model federated learning method, device, electronic equipment and storage medium, relating to the technical field of deep learning. The method comprises: the server issuing a residual weight to be updated and a global low-rank factor to be updated; each client performs a round of iteration of a model to be trained; the server aggregates the low-rank first factor and the low-rank second factor updated by each client respectively, and a global low-rank factor; the server aggregates and fuses the low-rank first factor and the low-rank second factor to obtain a dense fusion result; the low-rank first factor and the low-rank second factor are fused and aggregated to obtain a target dense aggregation result; the difference between the target dense aggregation result and the dense fusion result is determined to obtain a residual weight; and the residual weight and the global low-rank factor are issued. The present disclosure can inhibit client drift and catastrophic forgetting in a non-independent and identically distributed environment.

The invention discloses a low-power-consumption geomagnetic vehicle detection method and system. The method comprises the following steps: acquiring triaxial geomagnetic data; performing first-order difference and filtering on the three-axis data to obtain a smooth first-order difference signal; in a vehicle-free state, a mean value and a standard deviation are obtained through calibration, a Gaussian probability density function is established, an integral interval is constructed based on a deviation amount, a single-axis condition probability item is calculated through integration, and three-axis fusion is performed in combination with a state-related correlation correction coefficient to obtain a vehicle existence probability; in a state machine model including no vehicle, arrival detection, delay confirmation, and vehicle passing and leaving detection, outputting a vehicle arrival moment and a vehicle leaving moment according to a vehicle existence probability, a hysteresis threshold, a continuous point criterion and a delay confirmation mechanism, and compensating and correcting group delay introduced by filtering; and reporting detection information when the vehicle arrival event or departure event is output. According to the method, low power consumption and baseline drift resistance are both considered under the condition of a relatively low sampling rate, and the vehicle detection robustness is improved.

The utility model relates to a split charging device, specifically disclose a powder ration split charging device, including conveying device, and be located the blanking device above conveying device, the blanking device includes the blanking pipe of verticality and located the blanking pipe directly above the second conveying belt, and the feeding device of with blanking pipe upper end side wall intercommunication, the material blocking device of being located blanking pipe lower extreme, be located extruding device in blanking pipe, and the annular pressing plate of being located blanking pipe lower end portion, the powder ration split charging device of the utility model can avoid the powder of dispersing in the split charging process under the premise of guaranteeing split charging precision as far as possible.

This application discloses a multi-axis coordinated motion control method and apparatus for a dynamic hovering arc radiotherapy device, relating to the field of equipment control, and particularly to the field of radiotherapy equipment control. The method includes: acquiring the actual position information of multiple execution axes; determining the target control state of the multiple execution axes at the current moment based on the preset target motion trajectory and the actual position information; when the target control state is a linked motion state, controlling the multiple execution axes to perform coordinated motion according to the target motion trajectory; when the target control state is a coordinated locking state, controlling at least one first execution axis among the multiple execution axes to enter a position locking mode, and controlling at least one second execution axis among the multiple execution axes to enter a position maintenance mode. This application solves the technical problem of low multi-axis synchronization accuracy in existing multi-axis coordinated devices (such as dynamic arc radiotherapy devices) during dynamic hovering.

This invention relates to the field of electrocardiogram (ECG) signal denoising technology, and discloses an ECG signal denoising method based on multi-scale deep learning, including a training phase and an inference phase. The training phase includes the following steps: Step S101, acquiring approximately noise-free ECG data as a reference signal; Step S102, preprocessing the dataset; Step S103, constructing a multi-scale one-dimensional convolutional reconstruction network; Step S104, defining a morphology-aware composite loss function; Step S105, training the network using the training set. Addressing the problem that traditional frequency domain filtering methods struggle to balance signal fidelity and noise suppression due to overlap between noise and ECG signal frequency bands, this invention constructs a multi-scale feature extraction network and combines it with multi-scale time-frequency consistency constraints. This effectively suppresses various complex interferences, including baseline drift and power frequency interference, significantly reducing the risk of introducing time-domain artifacts while suppressing noise, achieving a better balance between noise suppression and fidelity.

The invention relates to the technical field of environment-friendly water quality detection, and discloses a water quality COD (Chemical Oxygen Demand) detection system based on three-spectrum multi-feature fusion and a prediction method in order to solve the technical problems of low system detection precision, weak anti-interference performance, low calculation efficiency and poor environmental protection performance. The spectrum preprocessing module is used for denoising and correcting three types of spectrums by adopting SG smooth filtering + constant offset elimination, SG + multivariate scatter correction and Norris-Williams first-order derivative + MSC, so that the multispectral combination is improved, and the detection precision is improved; the feature fusion module is used for screening feature wavelength subintervals with the highest correlation with COD in each spectrum by utilizing joint interval PLS (Partial Least Squares), and performing maximum-minimum normalization after splicing, so that the anti-interference capability of different spectrum curves is enhanced; and the prediction model module is used for establishing a COD concentration prediction model based on a kernel extreme learning machine KELM optimized by a kernel arrangement algorithm KTA, and outputting a COD prediction value of the water sample by taking the normalized fusion feature matrix as input, so that the calculation efficiency is improved.

The invention provides a hybrid expert model negative feedback iteration method and device, a storage medium and a program product, and the method comprises the steps: carrying out the cross-modal scene semantic analysis of vehicle end feedback data collected from a vehicle end, roadside sensing data of a roadside device, and macroscopic traffic data of a cloud system, and generating corresponding scene label information; based on the scene label information and the macroscopic traffic data, determining an activation weight of each expert sub-model in the hybrid expert model; negative feedback data in the vehicle running process are collected, and in combination with the influence degree of the target expert sub-model in the negative feedback scene, a responsibility expert sub-model needing to be optimized is determined; and performing directional incremental training on the responsible expert sub-model based on the negative feedback data, performing comprehensive evaluation on the expert sub-model after incremental training, and executing parameter replacement or version updating when an updating condition is met. According to the method, rapid and accurate local optimization is realized while the overall reliability of the model is ensured, and global parameter drift is effectively inhibited.