19results about How to "Avoid human intervention" patented technology

The invention relates to the technical field of automobile batteries, and discloses a battery service life prediction method, which comprises the following steps: S1, collecting use data of a battery; s2, cleaning and preprocessing the collected battery data, removing abnormal data, filling missing values, and performing standardization or normalization processing; s3, a nonlinear dynamic model is constructed, the change relation of the service life of the battery along with time is described, and the model considers multiple influence factors of the battery; and S4, based on battery historical data. According to the method, the prediction strategy is dynamically adjusted by combining Gaussian process regression and reinforcement learning, and the problem that a static model is poor in adaptability to battery state change in the prior art is solved; bayesian optimization is introduced to optimize hyper-parameters, so that prediction precision and stability are improved; and through a real-time data monitoring and dynamic adjustment mechanism, the real-time performance and the accuracy of the prediction model during battery state change are ensured.

The invention relates to the technical field of equipment control, in particular to a self-adaptive switching method and system of a current transformer. The method comprises the following steps: collecting primary side parameters and secondary side parameters of a current transformer to obtain primary side collection parameters of the current transformer and secondary side collection parameters of the current transformer; performing current transformer state segmentation initialization according to the current transformer primary side acquisition parameters and the current transformer secondary side acquisition parameters so as to generate a current transformer operation state classification result; switching result judgment is conducted on the current transformers according to the current transformer operation state classification result, and when the current transformer operation state classification result is a current transformer critical state section, parallel buffering is conducted on the current transformers, and critical current transformer switching data are generated. According to the invention, through accurate state classification, a dynamic switching mechanism, time sequence optimization and visual display, the switching sensitivity and stability of the current transformer are improved.

The invention relates to the technical field of data encryption, in particular to an intelligent medical information data encryption method and system and a medium. The method comprises the following steps: acquiring medical information data by using an electronic health recording system; initial AES-256 encryption is conducted on the collected medical information data, the encrypted medical information data are stored in a database, a medical information encryption database is obtained, and the medical information encryption database comprises at least one medical information record; and carrying out expiration timestamp distribution on each medical information record to obtain a medical information encryption expiration timestamp. According to the method, efficient and safe management of medical information data is realized through dynamic management of encryption strength, expiration time check and intelligent contract optimization, so that the security of the data is improved, the burden of the system is reduced, the compliance and flexibility of medical data storage and access are enhanced, and the overall performance of users and the system is improved.

The invention relates to the technical field of motor testing, and provides a rack testing method and device for a motor and a motor testing rack. The method comprises the steps of outputting test result data of a to-be-tested motor according to at least one group of preset target test data under the condition that a console rack tests the to-be-tested motor, the test result data comprising test data of the to-be-tested motor at a plurality of continuous time points; screening out test data of the to-be-tested motor with the running state stabilized under each group of target test data from the test result data as target test result data; and outputting the target test result data. According to the method, the effective test result data of the motor running stably under the target test data are automatically screened out, so that the result is accurate and reliable, human intervention is avoided, and the test efficiency is improved.

The invention discloses a safety control method of an intelligent power utilization safety control cabinet based on an internet-of-things sensor, aims to provide comprehensive power utilization safety monitoring and management, and comprises the following steps: monitoring various parameters of a power system and an environment in real time by integrating current, voltage, temperature, humidity and smoke sensors. The data processing device is used for carrying out preprocessing and noise reduction on the collected data and carrying out anomaly detection by utilizing a topological data analysis unit and a Gaussian process regression unit. The control device triggers an audible and visual alarm according to a detection result, and transmits alarm information to a remote monitoring platform and a mobile device through quantum communication and a 5G network. A user can check the system state and historical records through the remote platform and carry out remote management and operation. According to the method, topological data analysis and a Gaussian process regression model are introduced, and quantum calculation and communication technologies are combined, so that the accuracy of anomaly detection, the reliability of data transmission and the response speed of the system are improved, and the power utilization safety is ensured.

The present invention discloses a workflow-based method for automated analysis and model optimization of hyperspectral data, and the steps are as follows: S1, processing the acquired hyperspectral image of the target sample, extracting and saving the spectral data of the characteristic area, and constructing a one-dimensional hyperspectral data set of all target samples; S2, constructing a DeepSpNet model based on a one-dimensional convolutional neural network; S3, setting the training parameters of the DeepSpNet model, and establishing a hyperparameter combination; S4, dividing the one-dimensional hyperspectral data set into a training set and a test set in proportion, training the DeepSpNet model with the training set, evaluating the accuracy, precision, and recall of the DeepSpNet model through the test set, and automatically screening the best hyperparameter combination; S5, saving the DeepSpNet model with the best hyperparameter combination for target prediction. The present invention can accurately capture the defect characteristics inside the sample and effectively improve the depth detection capability.

The utility model relates to the technical field of agricultural equipment, in particular to agricultural equipment with a self-unloading function, which comprises a carriage, a hydraulic jack, a vehicle body and an unloading mechanism, two support blocks are arranged on two sides of the carriage, a seat is arranged on the vehicle body, and the unloading mechanism comprises two transverse screws, two belt bodies, a mounting box and an unloading plate. A first belt wheel is arranged at one end of the transverse screw rod, two rotating rods are arranged in the mounting box, second belt wheels and driven gears are arranged on the rotating rods, a motor is arranged on the mounting box, a driving gear is arranged at the output end of the motor, and threaded blocks are arranged on the two sides of the unloading plate; and by arranging a driving gear, a driven gear, a belt body and a motor, two transverse screw rods can rotate at the same time, so that cargoes in the carriage are completely and automatically unloaded under the action of an unloading plate, subsequent manual intervention is avoided, and the practicability of the equipment is effectively improved.

The invention provides a robot structure generative design and optimization method based on digital twinning, and the method comprises the following steps: 1, building a mechanical arm structure generation model based on a deep neural network; the input of the mechanical arm structure generation model is task requirements, and the output is the rod length and the joint number of the mechanical arm; step 2, based on an improved particle swarm algorithm, optimizing the output of the mechanical arm structure generation model; wherein in the improved particle swarm algorithm, the inertia weight is an adaptive weight; and step 3, designing the robot and completing the construction of the robot in combination with the optimal solution output in the step 2. According to the invention, a robot can be generated based on a specific scene, and the performance evaluation indexes are diversified.

The present invention discloses an intelligent curtain control method based on control pyramid and multimodal interaction, including: collecting real-time ambient light intensity, real-time multi-point temperature and humidity to generate first-level curtain control features; capturing on-site environmental sound features, separating voice commands from environmental noise in real time, and generating second-level curtain control features; regularly requesting control instructions from user terminal devices, analyzing and converting the control instructions, and generating third-level curtain control features; correlating and analyzing the first, second, and third-level curtain control features based on a multimodal fusion algorithm to form a curtain control pyramid; learning, converting, filling, and bidirectionally extracting the curtain control pyramid to determine the control intent, and inputting it into a curtain control model to control the opening and closing state; real-time monitoring of the motion state of the curtain, and feeding back the monitoring information to the curtain control model for dynamic adjustment. The present invention improves the intelligent level, accuracy, and adaptability of curtain control.

This application relates to the field of motor testing technology, and provides a method, apparatus, and test bench for testing motors. The method includes: while controlling the test bench to test the motor under test, outputting test result data of the motor under test based on at least one set of preset target test data, the test result data including test data of the motor under test at multiple consecutive time points; selecting test data from the test result data in which the operating state of the motor under test is stable under each set of target test data as target test result data; and outputting the target test result data. This application ensures accurate and reliable results by automatically selecting valid test result data in which the motor operates stably under the target test data, thereby avoiding human intervention and improving testing efficiency.

The invention discloses an intelligent curtain control method based on a control pyramid and multi-mode interaction. The intelligent curtain control method comprises the steps that real-time environment light intensity and real-time multi-point temperature and humidity are collected to generate first-level curtain control characteristics; capturing on-site environment sound features, separating voice instructions from environment noise in real time, and generating second-level curtain control features; a control instruction is regularly asked from the user terminal equipment, the control instruction is analyzed and converted, and a third-level curtain control feature is generated; performing correlation analysis on the first-level, second-level and third-level curtain control features based on a multi-modal fusion algorithm to form a curtain control pyramid; performing learning, conversion, filling and bidirectional extraction on the curtain control pyramid to determine a control intention, and inputting the control intention into a curtain control model to perform opening and closing state control; the motion state of the curtain is monitored in real time, and monitoring information is fed back to the curtain control model for dynamic adjustment. The intelligent level, accuracy and adaptability of curtain control are improved.

The invention discloses an inclination indicating device and method for PECVD equipment packaging piece transportation, the inclination indicating device comprises a comb-shaped body, the comb-shaped body is provided with a square starting part, a placing hole is formed in the center of the long side of the square starting part, the included angle between the diagonal line of the square starting part and the long side is 30 degrees, and the angle between the diagonal line of the square starting part and the long side is 30 degrees; the long edge of the square starting part serves as the starting direction, a first branch groove, a second branch groove, a third branch groove, a fourth branch groove and a fifth branch groove are sequentially formed in one side of the square starting part, and the interiors of the first branch groove, the second branch groove, the third branch groove, the fourth branch groove and the fifth branch groove communicate with one another to form a light ball movement channel. The device has the advantages that the problem that large PECVD equipment is inverted or inclined in the long-distance transportation process or the marine transportation process in the carrying, transportation and storage processes in the prior art is solved, and faults caused by inversion are effectively recorded.

The utility model discloses a kind of automatic repair equipment of photovoltaic module cell piece, belong to photovoltaic module production technical field, including bearing assembly, laser scanning assembly, solder strip fixed assembly and cell piece replacement assembly, by setting repair bench unit to carry the cell piece to be repaired, setting laser scanning unit completes the de-soldering of cell piece to be repaired and solder strip, setting solder strip fixed unit completes the fixation of solder strip after de-soldering, and setting cell piece pick-and-place unit completes the transport of undesirable cell piece after de-soldering and the replacement of new cell piece, to accurately realize the accurate repair of undesirable cell piece in battery string. Automatic repair equipment of photovoltaic module cell piece in the utility model, its structure is compact, control is simple, can satisfy on-line repair in battery string preparation process, realize the closed loop of photovoltaic module production and repair, effectively avoid manual intervention in battery string repair process, guarantee battery string repair efficiency, while, improve the repair quality of battery string.

The present application relates to a crimp tube quality detection device based on slight resistance changes, including: a test connector for connecting to both ends of the crimping position of the crimping tube; a wireless communication device for wireless communication with a remote terminal; a milliohm resistance measuring device for sending the detected resistance data to the remote terminal through the wireless communication device; wherein the milliohm resistance measuring device connects the test connector and the wireless communication device; the resistance data is used by the remote terminal to perform quality analysis on the crimping tube. The quality of the crimping tube can be judged by detecting the resistance changes at both ends of the crimping position of the crimping tube, and the resistance statistics of the crimping tube quality detection in different states can be used to achieve qualitative analysis of the quality defect level of the crimping tube. At the same time, wireless transmission is used to realize long-distance transmission of data, which is less affected by external factors and avoids possible errors or human intervention in the measurement and recording process, facilitating data acquisition and recording, and achieving high detection accuracy.

The present invention discloses a gearbox automated intelligent assembly system and method, the system includes: a torque workstation, a multi-degree-of-freedom flip machine, a robot and a server; a torque workstation and a multi-degree-of-freedom flip machine form an assembly unit; each assembly unit is provided with a robot station and a manual station; one robot corresponds to more than one assembly unit; each torque workstation and each robot are connected to the server; the multi-degree-of-freedom flip machine is used to adjust the posture of the gearbox according to the three assembly operations of gearbox assembly, large gear clearance adjustment and small gear entry, and the posture includes a horizontal state and a vertical state; and the gearbox is switched between the robot station and the manual station according to the three assembly operations; the torque workstation, the robot and the server are connected. The present invention integrates three assembly operations into one, makes the operation process more compact, reduces the time consumed by materials, streamlines the operators and improves efficiency, and realizes the intelligent management of maintenance data.

The present application relates to the coking field of coal, specifically to a full-automatic inspection and testing system for coking raw materials and a use method thereof.The full-automatic inspection and testing system for coking raw materials comprises an automatic sampling machine (1), characterized in that: further comprising a primary crusher (2), a secondary crusher (3), a screening device (4), a first automatic filling device (5), a second automatic filling device (6), a packaging and conveying system (7), a sending device (8), a pneumatic conveying pipeline system (9), an automatic sample storage cabinet (10), an automatic moisture testing device (11), an automatic sulfur testing device (12), an automatic industrial analysis testing device (13), an automatic calorific value testing device (14), a receiving device (15), an automatic drying device (16), a full-automatic grinding device (17) and an automatic packaging and coding equipment (18). The present application improves the accuracy, representativeness and efficiency of inspection.

The invention discloses an intelligent electric energy meter carbon point safety management and transaction system based on a block chain. The system comprises an intelligent electric energy meter data acquisition module, a carbon point calculation and management module, a block chain data storage and transaction module and a client carbon transaction platform module. The intelligent electric energy meter data acquisition module is used for data acquisition and monitoring, Internet of Things communication and data processing and transmission; the carbon point calculation and management module is used for carbon emission calculation, carbon point storage and management and integration with the block chain module; the block chain data storage and transaction module is used for carbon point data recording, intelligent contract application, data security and transaction transparency; and the client carbon trading platform module is used for user interface and data visualization, carbon point trading function and trading recording and trust guarantee. According to the system, the intelligent electric energy meter is installed on the user side, power consumption is monitored in real time, and comprehensiveness and accuracy of data are ensured.

This application provides a method, apparatus, and device for online real-time source apportionment of VOCs. The method includes: screening atmospheric VOCs receptor samples to obtain a first receptor data matrix; when it is determined that there is no local source component spectrum corresponding to the receptor sample, performing a source-free spectrum analysis process including: performing PCA on the first receptor data matrix, obtaining principal components with eigenvalues ​​greater than 1 in each source component, calculating the cumulative contribution rate of eigenvalues ​​of N principal components, determining the number of first sources as the number of factors based on the cumulative contribution rate of eigenvalues, running PMF to decompose the first receptor data matrix to obtain a source component spectrum matrix; calculating the correlation coefficient and mass percentage based on the source component spectrum matrix to obtain the number of second sources; identifying sources that meet the number of second sources based on a preset pollution source characteristic tracer material library and source component spectrum matrix, obtaining source identification results, and performing trend analysis using the source identification results.

This invention discloses a device operation process optimization system and device based on interactive behavior data, belonging to the field of human-computer interaction technology. The invention performs facial recognition on a designated device for the user to be operated on, recording all identified users as potential users. If several potential users exist, user filtering is performed to determine the primary user to complete the device operation; otherwise, the operation is directly performed based on the potential user. If user filtering is performed, multiple interaction judgments are conducted using camera interaction behavior data to determine whether to execute the human-computer interaction operation, thereby identifying the primary user. During the execution of the human-computer interaction operation, a simultaneous human-computer interaction operation judgment is performed to select the issued interaction behavior command. Based on the response of the potential users to the interaction behavior command, the corresponding primary user is determined to complete the device operation. This solves the problem in existing technologies where systems struggle to accurately identify target users, leading to incorrect identity matching and potential payment errors.