21results about How to "Guaranteed intelligence" patented technology

The invention discloses a non-destructive testing system and method for a boiler pressure pipeline based on image processing, relates to the field of non-destructive testing, and solves the problem that an existing detection method for the boiler pressure pipeline is poor in effect. The sensor module is used for carrying out sensor detection on the boiler according to the boiler image processing data and respectively obtaining a pipeline pressure detection coefficient, a pipeline temperature detection coefficient and a pipeline vibration frequency detection coefficient to obtain boiler sensor data; and the nondestructive testing module is used for carrying out nondestructive testing on the boiler pipeline to be detected according to the boiler sensor data and the boiler image processing data, and issuing an abnormal early warning according to a detection result. The accuracy and comprehensiveness of nondestructive testing of the boiler pressure pipeline can be ensured.

The invention provides a service dialogue model training method and device, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining a historical service call record and user portrait data of a target service; carrying out call link segment interception on the historical service call record to obtain call segments of a plurality of call links; generating a plurality of user simulation scripts for each user setting type in the plurality of user setting types based on the user portrait data and call feature information obtained by analyzing call segments of the plurality of call links; and based on a plurality of user simulation scripts of a set type of each user, carrying out simulation service dialogue on the user artificial intelligence agent model and the consultant artificial intelligence agent model to obtain simulation service dialogue data, and training the initial service dialogue model by taking the simulation service dialogue data as training data to obtain a target service dialogue model. The labor cost in the business dialogue model training process can be reduced, and the dialogue response speed can be improved.

The invention relates to the technical field of fire fighting, in particular to an intelligent fire fighting system and a fire fighting method.The fire fighting system comprises a house body, an equipment box is fixed to the middle of the upper end in the house body, a rotating adjusting mechanism is arranged on one side of the upper end in the equipment box, and a bearing box is arranged on the rotating adjusting mechanism; an angle adjusting mechanism is arranged on the other side of the upper end in the bearing box, and a fire extinguishing mechanism is arranged at the lower end of the other side of the house body. The fire-fighting method comprises the following steps of equipment starting, monitoring and alarming, spraying assembly adjusting and water supply spraying. According to the invention, the fire extinguishing system has dual monitoring functions of smoke sensing monitoring and infrared flame monitoring, the dual monitoring can make fire monitoring more accurate, and fire extinguishing treatment can be carried out on the initial position of the fire when the initial condition of the fire occurs, so that the intelligence and applicability of the fire extinguishing system are effectively improved.

The invention provides a gravity liquid supply system and method for an energy-saving energy storage battery liquid cooling unit, and the system comprises a liquid condensation module which is used for condensing a liquid refrigerant in an outer heat exchanger; the first control module is used for controlling the first one-way valve and enabling the liquid refrigerant in the outer heat exchanger to enter the medium heat exchanger through the first one-way valve under the action of gravitational potential energy of the outer heat exchanger and the medium heat exchanger; the gaseous condensation module is used for carrying out heat exchange evaporation on a liquid condensing agent and a cooling medium in the medium heat exchanger to generate a gaseous refrigerant; the second control module is used for controlling the second one-way valve and transmitting the gaseous refrigerant back into the outer heat exchanger through the second one-way valve under the action of the pressure difference between the medium heat exchanger and the outer heat exchanger, and the gaseous refrigerant exchanges heat with external low-temperature air and is condensed into a liquid refrigerant; by reasonably utilizing natural power such as gravitational potential energy and pressure difference, dependence on external power is reduced, and energy loss and operation cost can be reduced.

The present application belongs to the technical field of resource allocation, and particularly relates to a space resource dynamic allocation method based on an AI model and BIM operation and maintenance, comprising: obtaining a to-be-processed task and a spatial position identifier thereof, and constructing a task feature vector set; inputting the task feature vector set into a modal recognition network model to obtain a plurality of primary scheduling modes containing spatial coupling components and resource demand components through mapping; iteratively updating coupling weights between the primary scheduling modes and high-level scheduling modes until convergence, determining a current resource allocation mode based on the converged high-level scheduling modes, and determining the association strength of each task relative to the current resource allocation mode based on the coupling weights; generating a scheduling instruction set containing joint scheduling paths and independent scheduling instructions according to the association strength and in combination with the spatial position identifier, and converting the scheduling instruction set into executable control instructions; and the present application realizes fine and adaptive dynamic resource allocation based on BIM and real-time situation.

This utility model relates to an automatic cleaning, recycling, and conveying structure for concrete mixing plant waste, belonging to the technical field of concrete conveying equipment. This automatic cleaning, recycling, and conveying structure for concrete mixing plant waste includes a storage and circulation component. The storage and circulation component includes a storage bin, on one side of the top of the storage bin, an extension of a mortar conveying mechanism. A pressing component is installed on the top of the storage and circulation component near the mortar conveying mechanism. Through the structural design of the storage and circulation component and the spiral conveying component, this utility model can achieve washing during the conveying of concrete waste and facilitate the recycling of water resources, increasing environmental performance and reducing emissions. Only a small amount of water lost through evaporation needs to be replenished later, reducing water waste and avoiding environmental pollution caused by direct wastewater discharge, thus reducing the environmental treatment costs and energy consumption of the mixing plant.

The invention provides an LTE (Long Term Evolution) network access parameter adaptive protection method for an intelligent electric meter, intelligent electric meter side parameter storage is divided into a backup area and a current area, the backup area is used for storing network access parameters when network access succeeds last time, and the current area is used for storing network access parameters set last time or network access parameters currently used; the intelligent electric meter is provided with an LTE communication module, and when the LTE communication module accesses the network again, the intelligent electric meter side sends the network access parameters of the backup area to the LTE communication module by adopting a rollback mechanism; when the method is applied, the network access success rate of the communication module is effectively improved on the premise that the LTE communication module of the intelligent electric meter end automatically accesses the network.

The invention relates to the technical field of sediment cutting, and discloses an intelligent sediment cutting method and system based on an automatic cutter, and the method comprises the steps: recognizing a target layer of a to-be-cut sediment, and obtaining the sediment physical state information and layer shape information of the target layer based on a preset time period; determining a cutting evaluation coefficient of the target horizon based on the physical state information and the horizon shape information; presetting a preset cutting evaluation coefficient, and judging whether the to-be-cut sediment meets a cutting condition or not according to a relationship between the cutting evaluation coefficient and the preset cutting evaluation coefficient; when the to-be-cut sediment meets the cutting condition, the to-be-cut sediment is intelligently cut based on the cutting evaluation coefficient, whether the sediment is in the cuttable condition or not is accurately judged through the real-time change information of the sediment, forced cutting and damage to the sediment structure are avoided, and meanwhile the intelligence and accuracy of the sediment cutting process are guaranteed.

The invention discloses a power management method and device, and belongs to the technical field of power management, and the method comprises the steps: S1, configuring a traversal instruction triggering condition, a time calibration task and a timing task for a time node of a cycle time wheel; s2, judging whether a traversal instruction triggering condition of a cycle time wheel is reached or not; when a traversal instruction triggering condition is reached, executing S3, otherwise, executing S2; and S3, receiving and executing the time calibration task through the power management equipment, synchronizing the local time with the network time, then matching the execution time of the timing task, and triggering the timer to execute the timing task. According to the scheme, the time node of the cycle time wheel configures the traversal instruction triggering condition, the time calibration task and the timing task, the power management device receives and executes the time calibration task when the traversal instruction triggering condition is met, then the timing task is executed, timing management can be carried out on the power supply of the electrical equipment, and the power management efficiency is improved. And the reliability of power management is obviously improved.

The invention relates to the technical field of adjustment control, and discloses an OLED display brightness and contrast combined adjustment system based on artificial intelligence. According to the system, a sample set is constructed by collecting OLED display brightness data and contrast data under the condition that the brightness is not changed, the OLED display brightness data collected in the sample set is preprocessed, and a brightness adjustment relation model is established based on the preprocessed OLED display brightness data; based on the established brightness adjustment relation model and a contrast adjustment algorithm, establishing a contrast and brightness combined adjustment model; after the contrast and brightness combined adjustment model is established, the established contrast and brightness combined adjustment model is optimized through a genetic algorithm, and the brightness and contrast combined adjustment of the OLED display is realized based on the optimized contrast and brightness combined adjustment model, so that the intelligence and high efficiency of the brightness and contrast combined adjustment of the OLED display are ensured.

The present invention discloses a laser acupoint therapeutic pen with an electrical stimulation function. The pen determines whether a therapeutic electrode contacts a human body through intermittent tiny detection pulse signals, a first low-frequency pulse signal and a second low-frequency pulse signal, in cooperation with a circuit board to collect voltage change amplitude. When the pen does not contact a human body, it can enter a standby or shutdown mode, thereby saving energy consumption, improving battery life and improving safety. On the other hand, a microcontroller automatically switches working modes according to the human body contact status. For the comfort and safety of users, the pen first generates intermittent tiny detection pulse signals that will not cause human discomfort to determine whether the pen contacts a human body. When the pen contacts a human body, it determines whether the therapeutic electrode contacts an acupoint. Only when it is confirmed that the therapeutic electrode contacts an acupoint will the pen enter a normal physical therapy state, thereby ensuring the accuracy and intelligence of acupoint finding, so that acupoint finding no longer depends on the user's human body acupoint recognition ability.

The invention provides an ultrasonic probe automatic switching system based on multiple sensors, and the system comprises a first monitoring module which is used for monitoring a probe in a probe cup in real time based on a first sensor, outputting a monitoring signal, reading the level change state of the monitoring signal, and judging whether the probe is taken from the probe cup or not according to the level change state; the second monitoring module is used for monitoring attitude data of the probe based on a second sensor when the probe is taken away from the probe cup; and the probe switching module is used for transmitting the attitude data to the control terminal for analysis and controlling the probe to be automatically switched according to an analysis result. According to the invention, the automatic switching of the probe is realized, the intelligent, accurate and efficient switching of the probe is effectively guaranteed, and convenience is provided for the switching of the probe, so that the use experience feeling of a user is improved.

The application relates to the technical field of electromagnetic wave absorbing materials and devices, and particularly discloses a dynamic regulation and control system of a high-frequency electromagnetic protection carbon-based wave-absorbing material. The system comprises an environment sensing layer, an intelligent decision-making layer and a dynamic execution layer. The environment sensing layer captures and analyzes the frequency spectrum characteristics of incident electromagnetic waves in real time; the intelligent decision-making layer calculates optimal regulation and control parameters according to the environment characteristics based on deep reinforcement learning and impedance matching optimization; and the dynamic execution layer converts the optimal parameters into a physical regulation and control field and applies the field to the material to dynamically adjust the electromagnetic parameters of the material. The application constructs a complete closed-loop feedback control chain from environment sensing, intelligent decision-making to dynamic execution. The environment sensing layer captures the accurate frequency spectrum characteristics of incident electromagnetic waves in real time, the intelligent decision-making layer calculates optimal regulation and control parameters in real time based on deep reinforcement learning and impedance matching theory, and the dynamic execution layer accurately generates a regulation and control field to act on the material.

The present application relates to a zero-carbon park energy intelligent control method and system based on power prediction, comprising the following steps: obtaining park multi-source data, the multi-source data including historical power load data, weather forecast data, renewable energy power generation data and carbon emission monitoring data; based on the multi-source data, performing multi-time scale power prediction through a pre-constructed hybrid prediction model to generate ultra-short-term power prediction sequence, short-term power prediction sequence and medium and long-term power prediction sequence; according to the ultra-short-term power prediction sequence, the short-term power prediction sequence and the medium and long-term power prediction sequence, a park energy system optimization scheduling model considering carbon flow coupling characteristics is constructed; the optimization scheduling model is solved to generate a day-ahead scheduling plan and a real-time correction plan containing source-grid-load-storage multi-end cooperation; the present application can realize more intelligent zero-carbon park energy intelligent control.

The application relates to the field of artificial intelligence and robot technology, and provides a lightweight embodied intelligent system based on a big-small brain collaborative architecture and a construction method thereof.The system comprises a global planning large model module, a real-time embodied reasoning module, a task dynamic division and scheduling module, and a joint representation learning module.The global planning large model module is used for realizing a global task planning function; the real-time embodied reasoning module is used for realizing a real-time perception control function; the task dynamic division and scheduling module is used for receiving and responding to external task instructions, and splitting the external task instructions to obtain global planning type tasks and real-time control type tasks; the joint representation learning module is used for collecting multi-modal perception data and robot body state data, and training a joint representation model of a physical space and a robot body state; and the layered perception decision control module is used for sequentially executing real-time perception processing, local action decision and motion control calculation based on the joint representation model, and generating a bottom layer control instruction.

The present invention belongs to the field of hidden dangers in on-site operations and relates to AI image recognition technology. It is used to solve the problem that the prior art cannot intelligently identify hidden dangers in on-site operations by shielding different types of on-site operations. Specifically, it is a method for AI image recognition of hidden dangers in on-site operations, comprising the following steps: segmenting an image of an on-site operation area to obtain monitoring units, identifying each monitoring unit through AI image recognition and classifying them into a personnel set, an equipment set and a space set; within the monitoring time period, alarming the hidden dangers in the monitoring area through real-time monitoring of the total number of personnel RY, the personnel flow value RL, the average recognition accuracy rate P of the equipment and the average density M of the space; and periodically updating the hidden danger warning threshold YXmax in combination with the number of hidden danger alarms generated. The present invention can combine multi-source data to identify hidden dangers for different on-site operations, thereby ensuring the versatility and accuracy of on-site operation hidden danger identification.

The present invention discloses an archive management system using an intelligent robot, which relates to the field of robot archive management, and includes: a coordinate modeling module, which is used to establish a three-dimensional coordinate system model according to the actual situation of the archive room; an archive classification module, which is used to classify and identify archives, and establish a classification identification list; an archive access module, which is used to extract and confirm the accessed archive information based on a decision tree model; a guiding robot module, which is used to guide the intelligent robot to reach the location of the archive cabinet to be accessed according to the digital three-dimensional coordinate system model, and to make an abnormal prompt; a platform processing module, which is used to establish a visualization platform, which is used to display and record the access information and abnormal prompt information of the archive. The advantages of the present invention are: the intelligent robot is used to realize automatic access to archives and identification of abnormal access, thereby effectively improving the efficiency, safety and intelligence of archive management.

The invention provides an intelligent closestool control management system, and the system comprises an area monitoring module which is used for obtaining a sensitive monitoring area of a closestool, and monitoring whether a user enters the sensitive monitoring area or not in real time; the data acquisition module is used for acquiring behavior postures and control requirements of the user in real time after the user enters the sensitive monitoring area; the intelligent control module is used for generating an instruction sequence according to the behavior posture of the user and the control requirement and controlling the closestool to work according to the instruction sequence. The intelligence and effectiveness of closestool control and the convenience of operation are effectively guaranteed, so that the experience feeling of a user is improved.

The invention discloses an intelligent operation and maintenance method and system for meteorological observation equipment, relates to the technical field of meteorological equipment operation and maintenance, and focuses on deployment of an outdoor integrated unit and intelligent operation and maintenance of the meteorological observation equipment under a low-temperature condition through an integrated unit integrating functions of multi-port fusion, equipment fingerprint identification and automatic command analysis. A sealed test bin is constructed for testing, an integrated unit deployment scheme which is low in outdoor exposure risk of operators and stable in operation under different low-temperature gradients is selected, an operation and maintenance scheme which is simple in remote control and reduces the outdoor exposure risk of the operators is selected, an integrated operation and maintenance database is constructed, and then the integrated operation and maintenance database is applied to an actual low-temperature environment. The method achieves the simplicity and stability of the whole process of connection, transmission and the like of meteorological observation equipment, guarantees the reliability of meteorological observation, improves the intelligence of operation and maintenance, reduces the outdoor exposure risk of personnel, and effectively adapts to and meets the operation and maintenance demands in a low-temperature scene in actual winter.

The invention belongs to the technical field of air conditioners, and particularly provides an air conditioner and a control method thereof. The control method comprises the following steps: acquiring current environment data and current service object data; determining whether a data group identical to the current environment data and the current service object data exists in a database or not, and recording the data group as a target data group; the data set comprises historical environment data, historical service object data and historical operation data of the air conditioner; if yes, current operation data of the air conditioner are determined according to the target data set; and the air conditioner is controlled to operate according to the current operation data. Therefore, the air conditioner can determine the current operation data according to the current environment data, the current service object data and the database and operate the current operation data, human intervention factors are reduced, the method is more intelligent, and the use experience of a user is improved.

The application discloses a local boar remote semen collection training method based on human simulation interaction, and particularly relates to the field of artificial reproductive technology, which comprises obtaining environmental parameters to calculate a situation interaction adaptation index, executing a human simulation behavior path and collecting boar response data to construct a behavior cognition connection index when the situation interaction adaptation index meets preset conditions, inputting the two indexes into a training model to output a cognition transition prediction score, reconstructing the behavior path and reevaluating if the score is lower than a threshold, triggering a real person intervention process if the score is higher than the threshold for m consecutive times and the connection index fluctuation is less than a set range, and the like. The application realizes quantitative evaluation of pig house environmental adaptability, dynamic perception of target boar behavior response, and training decision closed-loop control based on double indexes and a machine learning model, ensures efficient promotion of semen collection training under the condition of strong environmental adaptability, sufficient individual response and stable cognitive trust, and improves training success rate and intelligence level.