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33results about How to "Realize self-learning function" patented technology

PCA-BP-based emotion recognition method and system

The embodiment of the invention discloses a PCA-BP-based emotion recognition method and system. The method comprises the steps that a first emotional sound spectrum feature vector of training audio isobtained by blending a first acoustic feature vector and a first sample entropy feature of the training audio; a PCA algorithm is adopted for conducting dimensionality reduction on the emotional sound spectrum feature vector, and a second emotional sound spectrum feature vector is obtained; the second emotional sound spectrum feature vectors of the training audio corresponding to various emotionsare input into a preset BP neural network model separately for training, and sound spectrum feature vector emotion models corresponding to various emotions are obtained; a second acoustic feature vector and a second sample entropy feature of to-be-detected audio are blended to obtain a third emotional sound spectrum feature vector of the to-be-detected audio, the third emotional sound spectrum feature vector is compared with all the acoustic feature vector emotion models, the emotion model matching degree is calculated, and the acoustic feature vector emotion model corresponding to the maximum emotion model matching degree is output. The technical problems that the current voice emotion recognition process is complex, the implement difficulty is high, the accuracy is low, and the efficiency is low are solved.
Owner:SPEAKIN TECH CO LTD

Internet of Things sewing machine

The invention provides an Internet of Things sewing machine. The Internet of Things sewing machine comprises a sewing machine main body (1), a display screen (2), an electric cabinet (3), a Web data server (4) and a control terminal (5), wherein the display screen (2) is arranged on the sewing machine main body (1) and is used for identifying and displaying user information and sewing machine information; the electric cabinet (3) is connected with the sewing machine main body (1) and is used for controlling the operation of the sewing machine main body (1), receiving recorded information and transmitting the information to the Web data server (4); the Web data server (4) is used for receiving, processing and storing the information and transmitting the processed information to the controlterminal (5) and the electric cabinet (3); the control terminal (5) is used for identifying and managing person information, receiving and displaying the processed information and transmitting an instruction. According to the Internet of Things sewing machine disclosed by the invention, the sewing machine can autonomously upload sewing data; the control terminal synchronize in real time, so that the intelligent degree of the sewing machine is improved, the consumption of human resources is effectively reduced and the production efficiency is improved.
Owner:XIAN TYPICAL IND

Intelligent self-learning system for electromechanical equipment

The invention relates to an intelligent self-learning system for electromechanical equipment. The intelligent self-learning system is connected with the electromechanical equipment and used for auxiliary analysis of operation of the electromechanical equipment. The intelligent self-learning system comprises a data collecting unit, an operation model self-learning system and a standard model data base, wherein the data collecting unit is connected with the electromechanical equipment and collects multiple items of parameters in operation of the electromechanical equipment in real time; the operation model self-learning system is connected with the data collecting unit, builds a standard operation model according to the multiple stems of parameters in operation of the electromechanical equipment and refreshes the standard operation model; the standard model data base is connected with the operation model self-learning system and stores the standard operation model after each refreshing. The intelligent self-learning system can collect all items of information data in operation of the electromechanical equipment and obtain the standard operation model of the electromechanical equipment to achieve the self-learning function on the basis of the collected data, so that the intelligent self-learning system can provide reference for research personnel in the process of analyzing the operation situation and faults of the electromechanical equipment and is beneficial to performing parameter preset and analysis on the electromechanical equipment.
Owner:SUZHOU KANGKAI ELECTRIC

Bridge inspection vehicle frequency conversion control system and control method thereof

The invention discloses a bridge inspection vehicle frequency conversion control system. The bridge inspection vehicle frequency conversion control system comprises a frequency converter, a PID controller, an image acquisition module and a speed prejudgment module; the frequency converter is in communication connection with a motor and is used for conducting frequency conversion control on the motor; the PID controller is in communication connection with the frequency converter and a speed sensor and is used for conducting closed-loop control on output signals of the frequency converter according to detection signals of the speed sensor; the image acquisition module is used for acquiring image information in the advancing direction of a bridge inspection vehicle; and the speed prejudgment module is in communication connection with the frequency converter, the PID controller and the image acquisition module and is used for prejudging the driving speed of the bridge inspection vehicle according to the image information acquired by the image acquisition module on the one hand and used for correcting the driving speed prejudging process according to real-time control information sent by the PID controller. According to the bridge inspection vehicle frequency conversion control system, the defects in the prior art can be overcome, and the real-time computation amount of the PID controller is decreased by presetting the driving speed.
Owner:SINO RUBBER TECH CO LTD

Method for making virtual display course based on physical teaching material

The invention relates to a method for making a virtual display course based on a material object teaching material, which comprises the following steps: determining key knowledge points needing classroom teaching or student mastery in a paper teaching material; preparing each key knowledge point into corresponding three-dimensional data; obtaining external information associated with the key knowledge points, and collecting the external information and the three-dimensional data into a three-dimensional data primary model; performing feature identification on each three-dimensional data primary model to prepare an AR code; and setting the AR code at a corresponding key knowledge point of the paper teaching material; setting an AR code or an AR total code at each key knowledge point of the paper teaching material; a user learning corresponding progress by scanning an AR code or an AR total code. The user can select different virtual scenes, real scenes or self-made information according to interests, the corresponding information and the three-dimensional data primary model or the actual data model are integrated into a three-dimensional data model, the three-dimensional data model can be fed back through the Internet, and the self-learning function of the three-dimensional data primary model is achieved according to feedback information.
Owner:HUIZHOU UNIV +1

Intelligent soot blowing control method, system and storage medium based on multi-dimensional evaluation factors

The invention discloses an intelligent soot blowing control method, system and storage medium based on multi-dimensional evaluation factors. By selecting a plurality of boilers reflecting the contamination degree of the heating surface corresponding to the soot blower and the influence of soot blowing on the safety and economy of boiler operation The operating parameters are used as the evaluation factors for the selection of sootblowers, and each evaluation factor is prioritized and grouped according to the impact of each evaluation factor on the boiler safety, the degree of economic operation, and the degree of correlation with the contamination of the heating surface; Determine whether the value of each evaluation factor is within the normal state range, count the number of evaluation factors within the priority level of each group whose value is not within the normal state range, and calculate the number of evaluation factors within the priority level of each group whose value is not within the normal state range. The number of evaluation factors judges whether soot blower is needed for soot blowing, thereby reducing the soot blowing steam loss of the power plant, reducing the risk of blowing damage to the heating surface, and improving the safety and economy of boiler operation.
Owner:STATE GRID HUNAN ELECTRIC POWER +2

Digitalized welding machine with parameter self-learning function

The invention relates to a digitalized welding machine with a parameter self-learning function, which automatically generates parameters of a plurality of working point with good welding effect into parameters of other working points within an interval through a large step pitch calibration and local Newton interpolation parameter self-regulation algorithm, thereby achieving the effect of continuous regulation and overcoming the defect of sectionalized regulation of the discretization of a digitalized arc welding power supply. The invention can realize multiple welding processes including CO2 welding, P-MIG (Metal-Inert Gas Welding) welding, DP-MIG welding, and the like, has stable welding process and good welding line formation which are proved by tests, provides the storage modes of welding parameters with different attributes and priority levels aiming at different parameter generation modes and can ensure that the welding parameters are optimized; and in addition, the overwriting of the welding parameters and the self-learning function of the digitalized welding machine can be realized by utilizing the method to ensure that the welding parameters are more and more well used and the requirements on people for the intelligentization of the digital welding machine are met.
Owner:EAST GRP CO LTD

Intelligent control system and anti-pinch method for electric passenger door

The invention discloses an electric passenger door intelligent control system and an anti-pinching method. A center processor module, a door opening and closing input signal detection module, a motordetection module, a door position sensor, a temperature sensor, a motor driving module, a nonvolatile memory module, a communication module and a fault indicating module are included, and the door opening and closing input signal detection module, the motor detection module, the door position sensor, the temperature sensor, the motor driving module, the nonvolatile memory module, the communicationmodule and the fault indicating module are all connected with the center processor module. By means of the electric passenger door intelligent control system and the anti-pinching method, the safetyrequirement that a passenger door prevents pinching of personnel can be better met, and the problem that the anti-pinching performance is limited by the environment temperature is solved; the convenience requirement of installing and debugging of the passenger door is better met, and the problem that door opening and closing are not smooth because of different door opening sizes or the manufacturing tolerance is solved; the anti-pinching performance and door opening and closing smoothness reliability requirement in the design life period of a passenger door product is better met, and the problem that because of mechanical service life and abrasion, the anti-clamping performance and the opening and closing smoothness degrade is solved; and meanwhile, maintaining is easy, and the faults of an executing mechanism or an anti-pinching mechanism can be diagnosed and recorded.
Owner:ZHENGZHOU JINGYIDA AUTO PARTS
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