11results about How to "Real-time dynamic adjustment" patented technology

The invention discloses a control circuit of a power amplifier and a chip, and the control circuit comprises a digital control module which is used for generating a first switching signal when monitoring that an accessed audio signal meets a first switching condition, and generating a second switching signal when monitoring that the audio signal meets a second switching condition; the analog control module is used for switching from a first mode to a second mode in response to the first switching signal and switching from the second mode to the first mode in response to the second switching signal; the first mode is a high-power working mode, and the second mode is a low-power working mode. The audio signal is monitored in real time through the digital control module, the corresponding switching signal is generated and sent to the analog control module, and then the analog control module switches between the high-power working mode and the low-power working mode, so that the working modes are dynamically adjusted in real time, the continuity of audio output is ensured, and the audio output efficiency is improved. The stability of the circuit is improved, and the hearing feeling is optimized.

The invention discloses a visual characterization method for Hash mapping code peculiar smell to a 3D space, and relates to the field of software engineering. According to the method, accurate, unique and quality-associated characterization from code elements to a 3D space is realized through an algorithm link of associated code quality indexes, and the problems that traditional 2D visualization information is overloaded, 3D visualization has no quality association and calculation is complex are solved. According to the algorithm, code quality indexes serve as input, 3D space positions and visual attributes are output through calculation processing, and the real-time characterization requirements of a large-scale code library are met.

The present application relates to a method and system for adaptive adjustment of optical image detection threshold based on reinforcement learning, belonging to the field of machine vision and intelligent detection technology, which solves the technical problems of existing industrial vision detection, such as threshold dependence on manual setting, lack of adaptability leading to decline in detection accuracy, and inability to optimize in real time. The solution is: a method for adaptive adjustment of optical image detection threshold based on reinforcement learning, including the following steps: S1, collecting the original image of the measured object; S2, preprocessing the original image; S3, constructing a state vector based on multi-dimensional feature quantities; S4, outputting actions by a reinforcement learning strategy network; S5, updating the detection threshold based on the actions and applying it; S6, calculating the detection quality evaluation index and the reward signal; S7, modeling and training the reinforcement learning strategy network and updating the parameters to form a threshold adaptive adjustment strategy. Compared with the prior art, the present application has the advantages of not depending on manual setting, strong adaptability, high precision, real-time optimization, and wide applicability.

The utility model relates to the technical field of curing equipment, in particular to a track assembly and a curing oven with the track assembly, and the track assembly comprises at least two sets of track bodies arranged in parallel and turning wheels installed at the outer ends of one sides of the track bodies. The turning wheel is installed on the tensioning structure and is driven by tensioning to achieve displacement adjustment in the direction parallel to the length direction of the track body. The tensioning structure comprises a fixed sliding rail, a sliding block and a traction structure. The sliding block is matched with the fixed sliding rail and is used for fixedly mounting the turning wheel; the traction structure comprises a transition wheel, a counterweight and a traction piece; the traction piece is wound on the transition wheel, and the two ends of the traction piece are connected with the sliding block and the balance weight respectively. The turning wheel is installed on the tensioning structure, real-time dynamic adjustment of the turning wheel is achieved, the materials distributed along the track assembly always keep proper tension based on reasonable counterweight selection, the situation that the curing effect of a chip is affected due to the fact that a material belt is too loose or too tight is avoided, and the curing quality is improved.

This invention discloses a dynamic control method and system for supercritical CO2 two-phase cooling, belonging to the field of high-efficiency heat exchange technology. The invention collects and standardizes cooling system operating data, constructs a reinforcement learning input space, and outputs piezoelectric valve control signals via network computation to adjust the medium flow rate of the supercritical CO2 two-phase circulation in real time. Based on the adjusted operating data, a reward value is calculated and network parameters are updated. Combined with digital twin technology, virtual mapping of the cooling system and fault scenario simulation are achieved, realizing closed-loop intelligent control of the system's operating state. This invention can stabilize the chip cooling process, improve heat exchange efficiency, enhance system fault response capabilities, adapt to the heat dissipation requirements of high-density chips, and features fast control response and strong operational stability. It effectively solves the problems of slow response and weak fault adaptability in traditional cooling methods, optimizes the overall operating effect of the cooling system, and meets the dual requirements of efficient chip heat dissipation and continuous stable operation.

The invention relates to an online automatic flat film thickness adjusting die head and an adjusting method thereof.The online automatic flat film thickness adjusting die head comprises a front die body and a rear die body, and a melt runner is formed between the front die body and the rear die body; a front lip and a rear lip are respectively arranged at the lower ends of the front mold body and the rear mold body, a lip gap is formed between the front lip and the rear lip, and heating pipes are uniformly inserted in the front mold body and / or the rear mold body at intervals along the width direction of the flat film; by adjusting the temperature of the heating pipe in the corresponding area, the fluidity of the melt in the area is changed, and the thickness of the flat film flowing out of the area corresponding to the lip seam is adjusted. According to the invention, the local heating temperature is independently controlled, and the viscosity and fluidity of the melt in the corresponding area are changed, so that the discharging amount of the lip seam is finely adjusted to adjust the thickness of the flat film. The adjustment mode based on thermal expansion and rheological properties can realize continuous, stepless and trace thickness adjustment, and can effectively cope with production occasions with extremely high requirements on film thickness uniformity.

The application discloses a kind of multi-algorithm synergic optimization's water turbine key component additive manufacturing method, it is related to additive manufacturing technical field.The method of the present application constructs complete intelligent manufacturing system: in data acquisition stage, high-precision laser scanning technology (precision reaches 0.01mm) is used, the accurate three-dimensional reconstruction of damage area is realized;In the link of modeling analysis, through the finite element simulation of multi-physical field coupling, the thermodynamic behavior in the repair process is accurately predicted;Process optimization, innovatively combine adaptive differential evolution algorithm, improved NSGA-II multi-objective optimization algorithm and deep reinforcement learning (DRL), form the whole process intelligent decision system covering deviation analysis, path planning and parameter optimization.Especially the introduction of deep reinforcement learning algorithm, the millisecond level dynamic adjustment of key process parameters such as wire feeding speed, laser power is realized, and the stability and material utilization of manufacturing process are greatly improved.

The application discloses a production method and system of a lightly boron-doped substrate high-resistance wafer, and belongs to the technical field of production control. The method comprises the following steps: calculating a waste gas residual index based on ion concentration of waste gas; if abnormality occurs in a plurality of waste gas residual indexes in succession, updating model parameters of a layered state observer; otherwise, inputting online monitoring data into the layered state observer to obtain real-time distribution and uncertainty distribution of resistivity in a wafer growth process; setting an expected state evolution track, wherein the expected state evolution track comprises an ideal distribution matrix of resistivity at each preset time, calculating error distribution based on the real-time distribution and the ideal distribution matrix; obtaining an adjustment instruction based on fuzzy reasoning model processing of the error distribution and the uncertainty distribution, adjusting production process parameters based on the adjustment instruction; and generating an expected state evolution track of the next batch based on average quality error. The application can guarantee the stability of production quality.

The utility model discloses a kind of adjusting mechanism and video equipment, a kind of adjusting mechanism, including connecting seat, multiple first limiting parts are equipped on connecting seat;Adjusting seat, adjusting seat is slidably set in connecting seat, adjusting seat can move on connecting seat along first direction;First locking piece, first locking piece is set in adjusting seat and is movably connected with adjusting seat, second limiting part is equipped on first locking piece;When second limiting part cooperates with one of first limiting part, adjusting seat is relative to connecting seat and presents locking state;When second limiting part is separated from first limiting part, adjusting seat is relative to connecting seat and presents unlocking state.The connecting support is relatively displaced by adjusting seat and connecting seat, so that the gravity position of equipment main body relative to connecting support is flexibly adjustable, effectively reduce the risk of dumping due to unstable gravity.

The application discloses an energy equalization method for an electrically driven vehicle line control chassis multi-energy braking system, comprising the following steps: step one: first, obtaining the through vehicle speed, braking demand and residual power data of different vehicles at different times under the same road environment by using a vehicle-road cloud platform, and fusing historical data and real-time vehicle data; step two: based on the demand braking energy prediction value obtained in step one, designing a braking energy dynamic equalization algorithm, and real-time calculating the energy recovery ratio of an EMB system and an electric drive system by using an optimization algorithm; and step three: on the basis of step two, integrating a sensor network and cloud data analysis, real-time collecting and processing the energy recovery data in the braking process, and combining the real-time data with historical data. The application realizes accurate prediction of the energy demand of a vehicle under different braking conditions, and improves the foresight and adaptability of a prediction model through a self-updating energy demand prediction method.

The invention belongs to the technical field of structural vibration control experiments, and relates to a neural network training-oriented flexible structure wind-induced vibration experiment device and method. The experimental device comprises an aeroelastic model and an actuating mechanism, the aeroelastic model supports a base, a screw, a support plate, a wind shield and a top cover, the actuating mechanism comprises a rotating steering engine and a wing plate capable of rotating, an angle measuring mechanism is mounted on the wing plate, a pair of vibration acceleration measuring mechanisms is mounted on a cover plate, and the rotating steering engine is connected with a microcontroller. The experimental method comprises the following steps: putting the experimental device into an atmospheric boundary layer wind tunnel or tornado simulator, connecting a computer, changing the aerodynamic shape and wing plate angle of the aeroelastic model, and transmitting the transverse wind direction and downwind direction vibration acceleration of the aeroelastic model to the computer; and testing and data acquisition of the aeroelastic model under different configurations are carried out in a circulating manner. According to the method, the data acquisition amount is large, massive and complex random aerodynamic configuration combinations can be generated, and the data acquisition efficiency is remarkably improved.