8results about How to "Fast tracking" patented technology

The civil aircraft demand analysis method based on the knowledge graph utilizes the characteristics of the knowledge graph and the graph database in explainability and high efficiency in multi-hop relationship search, finally improves the speed of demand link completeness calculation and demand link tracking; utilizes the characteristics that the knowledge graph can understand the demand sentence text features, finally can realize the recommendation of the demand link and the calculation of the demand design completeness.

The present application relates to radar detection technology field, especially to a kind of signal processing method of Doppler frequency offset interference of height-finding radar, the method is by monitoring the maneuverability of height-finding radar and dynamically adjusting frequency modulation period and frequency modulation bandwidth of symmetrical frequency modulation signal;Based on the frequency modulation period and frequency modulation bandwidth after adjustment generate positive slope frequency modulation signal and negative slope frequency modulation signal and carry out periodic alternate emission, collect and process and difference calculation first echo signal and second echo signal after reflection, obtain after eliminating Doppler frequency offset interference ranging frequency difference, further avoid the height-finding error caused by Doppler shift amount, to obtain accurate target height based on ranging frequency difference calculation.This application is by using the Doppler shift polarity opposite characteristics of positive and negative slope frequency modulation signal, by frequency spectrum line pairing and difference calculation offset Doppler shift component, finally based on the target height of corrected frequency information inversion, to realize high-precision height-finding.

The present application relates to a distributed photovoltaic MPPT method, system, device and medium, and relates to the technical field of distributed photovoltaic power generation, which comprises the following steps: preprocessing photovoltaic array data, obtaining irradiance, temperature and MPP voltage dataset; determining the optimal ElmanNN hidden layer node number by K-fold cross-validation and RMSE evaluation, and dividing the dataset into a training set, a validation set and a test set; inputting the training set into global search of the firefly algorithm and local optimization of the ant colony optimization algorithm, defining the stable solution as the FA-EAS optimal parameters after convergence; updating the ElmanNN weight threshold based on the optimal parameters, deploying the training model to perform MPP voltage online prediction; inputting the difference between the predicted voltage and the reference voltage into a PID controller, calculating the control amount through the incremental PID, generating a PWM signal to control the duty cycle of the Boost converter, and realizing maximum power point tracking. The present application can improve the tracking speed, stability and success rate of MPPT.

The application discloses a deep spatio-temporal correlation video target tracking method and system, which realizes target tracking for each video sequence and guarantees to obtain accurate video target tracking results. Firstly, a spatio-temporal feature extractor is designed to extract spatio-temporal features of a template sequence and a search sequence. Secondly, a feature matching module is introduced, which is composed of a classification branch and a regression branch. The extracted template spatio-temporal features and the search spatio-temporal features are subjected to similarity matching through correlation filtering to obtain multi-channel correlation filtering features respectively. Then, a target tracking module is deployed, which includes a classification head and a regression head, and the classification score map and the regression score map are calculated according to the input multi-channel correlation filtering features respectively, which are used to predict the target position and estimate the target scale. Finally, the spatio-temporal correlation visual tracking model is optimized by minimizing the defined joint loss. In the target tracking test, a confidence region estimation strategy is proposed, so that the target tracking is kept robust and accurate in the video sequence.

This invention relates to the field of adaptive control technology, specifically disclosing a tool wear adaptive compensation system based on multi-dimensional sensor data fusion. It acquires force, vibration, and acoustic emission signals in real time to obtain a fused feature sequence; extracts the dynamic force gradient and calculates the fractal dimension, decomposing it into long-trend and short-period components to generate a coupled modulation sequence, establishing a nonlinear mapping with two latent states: tool wear amount and workpiece hardness; employs a dual-state unscented Kalman filter to jointly estimate wear amount and hardness, using a cross-covariance matrix to decouple their contributions to the sensor signals; calculates dimensional deviations based on wear estimates, and uses hardness estimates to eliminate hardness fluctuation interference, forming a compensation amount specific to wear, which is then written into the CNC system. Simultaneously, it monitors signal changes after compensation to generate confidence levels, and uses feedback to adjust the filter covariance for iterative optimization. This invention can separate the interference of material hardness fluctuations on wear estimation, avoid erroneous compensation, and improve batch processing accuracy.

This application relates to target tracking and provides a multi-target tracking method. It acquires measurement data of the target to be tracked using at least two sensors to obtain a first set of measurement data pairs. Then, based on preset constraints, related measurement data pairs in this first set are eliminated to obtain the true target. Next, the starting point of the true target's trajectory is determined using an FCM algorithm and the measurement data pairs of the true target. Then, the true target is correlated using the FCM algorithm and the real-time measurement data of the true target to obtain a stable trajectory. Finally, the true target is tracked based on the starting point and the stable trajectory. This application eliminates false targets using preset constraints and obtains the starting point of the trajectory based on the FCM algorithm in the trajectory initiation part, and uses FCM to determine the stable trajectory of the true target in the trajectory correlation part, thereby achieving the tracking of the true target with short processing time and fast tracking speed.

This invention discloses a method for integrating frequency detection function into a software phase-locked loop (PLL) of a three-phase converter, relating to the field of data processing. The method includes the following steps: Step S1, obtaining the grid voltage in a three-phase stationary coordinate system and converting it into a coordinate system grid voltage. Compared with existing technologies, the advantages of this invention are: This invention overcomes the limitations of low-bandwidth PLLs on frequency response, significantly improving the dynamic response speed and steady-state accuracy of frequency detection, while also possessing good anti-interference capabilities, solving the problem of balancing response speed and detection accuracy in traditional solutions; without changing the PLL PI parameters to ensure converter impedance stability and weak grid adaptability, the calculated real-time angular frequency is used as a feedforward value to replace the fixed feedforward, effectively improving the PLL's tracking speed for grid frequency changes; and it saves software resource costs.

This invention relates to the field of adaptive control technology, specifically disclosing a tool wear adaptive compensation system based on multi-dimensional sensor data fusion. It acquires force, vibration, and acoustic emission signals in real time to obtain a fused feature sequence; extracts the dynamic force gradient and calculates the fractal dimension, decomposing it into long-trend and short-period components to generate a coupled modulation sequence, establishing a nonlinear mapping with two latent states: tool wear amount and workpiece hardness; employs a dual-state unscented Kalman filter to jointly estimate wear amount and hardness, using a cross-covariance matrix to decouple their contributions to the sensor signals; calculates dimensional deviations based on wear estimates, and uses hardness estimates to eliminate hardness fluctuation interference, forming a compensation amount specific to wear, which is then written into the CNC system. Simultaneously, it monitors signal changes after compensation to generate confidence levels, and uses feedback to adjust the filter covariance for iterative optimization. This invention can separate the interference of material hardness fluctuations on wear estimation, avoid erroneous compensation, and improve batch processing accuracy.