20results about How to "Implement IntelliSense" patented technology

The invention relates to the technical field of signal control, and discloses an intelligent signal I / O control system and method for industrial automation. The method comprises the following steps: carrying out acquisition and feature analysis on various signals in the industrial automation system to obtain a signal feature model; designing a two-stage I / O control scheme to obtain a first control strategy; constructing a state-trend matrix, and introducing an evaluation function to quantify a control effect to perform dynamic iteration updating to obtain a target control parameter; performing PLC autonomous fault diagnosis to obtain a fault diagnosis result; performing network cooperative control analysis on the plurality of PLCs based on a fault diagnosis result to obtain a hierarchical central coordination mechanism; and establishing a multi-dimensional performance index system of a hierarchical central coordination mechanism, and performing evaluation and adaptive optimization on the first control strategy to obtain a second control strategy, thereby realizing intelligent perception, accurate control and fault diagnosis of a complex industrial environment, thereby improving the performance and stability of the whole automation system.

The invention discloses a gas extraction drilling track inversion and control system, and relates to the technical field of gas extraction, and the key points of the technical scheme are that the system comprises a high-gas coal seam rapid control elimination and reduction system and a gas injection flow increasing dynamic evaluation system; according to the rapid control elimination and reduction system for the high-gas coal seam, a method of combining experimental research, numerical simulation and on-site industrial tests is adopted, the coal seam gas occurrence rule of a working face of a Chengne mining area is obtained, the multi-component gas competitive adsorption rule of a three-soft coal seam is defined, and therefore gas injection driving key technical parameters of a coal seam gas abnormal target area are mastered; a gas injection drive gas-carrying rapid and accurate extraction technical system suitable for the gas abnormal area of the Chengne mining area is formed; according to the gas injection flow increasing dynamic evaluation system, working parameters are designed and monitored, the gas concentration is accurately monitored, and real-time detection and automatic early warning are achieved.

This invention relates to the field of pole production and manufacturing execution management, and discloses an intelligent pole production execution management system based on the Internet of Things (IoT). The system includes a data acquisition unit, an edge processing unit, a cloud management platform, an intelligent analysis unit, and a human-machine interaction unit. The system collects data on raw material ratios, mold status, curing temperature, humidity, and other detection data through sensors. The edge processing unit identifies anomalies in real time and performs rapid adjustments. The cloud management platform generates a digital twin of the pole and combines it with an algorithm model to adaptively adjust curing temperature, minimize energy consumption, predict lifespan, predict production capacity, and assess mold lifespan. The human-machine interaction unit presents process information to operators through an augmented reality terminal and supports two-way feedback. This system enables real-time monitoring and closed-loop optimization of the entire pole production process, reducing energy consumption, improving consistency, extending service life, and significantly enhancing the intelligence and reliability of the production process.

The application provides a medicine cold chain logistics transportation whole-process tracking method and system, and relates to the technical field of logistics transportation monitoring. First, the original sensor tracking data stream output by the internal sensor cluster of a transportation carrier in a continuous collection time window is acquired. Then, the transportation carrier operation trajectory line is generated according to the geographic positioning parameters, and the multi-dimensional environment state marker set is generated by combining the physical parameters at the same time of each geographic position coordinate point. Meanwhile, the logistics transfer node topology connection network containing the logistics transfer node unit and the directed transfer path edge is constructed. The operation trajectory line, the multi-dimensional environment state marker set and the topology connection network are input into the pre-constructed space-time state feature fusion tracking model to generate the whole-process state tracking feature tensor. The abnormal state type identification and the space-time distribution feature are obtained by performing the abnormal state mode matching on the whole-process state tracking feature tensor, and the abnormal early warning instruction set is generated. The application can comprehensively and accurately track the whole process of medicine cold chain transportation, intelligently identify the abnormality and timely generate the early warning.

The embodiments of this specification provide a method and device for identifying the cause of abnormal operation of a transmission pipeline. The method includes: obtaining operation data of different positions of the transmission pipeline; clustering the operation data of the different positions to obtain a preset number of operation data with different abnormal fluctuation types; establishing labels for the preset number of operation data with different abnormal fluctuation types according to the correspondence between the abnormal fluctuation type and the abnormal cause; the label is the abnormal cause corresponding to the abnormal fluctuation type of the operation data; using the operation data with the label as a training sample, calculating the classification conditions of the operation data in the training sample; identifying the abnormal cause of the operation data to be identified according to the classification condition, thereby improving the accuracy of identifying the cause of abnormal operation of the transmission pipeline.

The invention provides dual-system intelligent sensing disinfection and sterilization equipment, and belongs to the technical field of sterilizers. The equipment comprises a sterilization bin and an equipment bin, and the sterilization bin is provided with a sterilization boiler, a microwave generator, a shredding machine, a conveyor, a lifting machine, an air collecting device, a hydraulic station, a microwave power source and an operation box. A water softener, a first water tank, a second water tank, a steam boiler, a cooling-water machine, a heat exchanger, a vacuum pump, a circulating water pump, a filtering sterilizing box, a biological filter and a gas-liquid separator are respectively arranged on the equipment cabin. By means of the steam generator, the sterilization boiler, the microwave generator, the biological filter, the heat exchanger, the water circulation vacuum pump, the first water tank, the second water tank, the water pump, the water filter and the gas-liquid separator, medical waste sterilization without waste water can be achieved, water resources of the system are completely internally circulated, saturated steam is recycled, and residual heat is completely recycled.

The present invention provides a dual-power drive system intelligent switching method and device for a drilling coring robot, which relates to the technical field of system intelligent switching, including: connecting a dual-power drive system, wherein the first drive system is a motor direct drive system, and the second drive system is a hydraulic drive system; collecting data on the drilling environment to obtain drilling environment data; obtaining multiple exposure factors, which are environmental factors that affect the transmission torque of the drilling coring robot; obtaining multiple corresponding prior probabilities, predicting the variation of the transmission torque, and obtaining a first variation probability; when it is greater than a preset variation probability, obtaining a first switching instruction; after receiving the first switching instruction, switching from the first drive system to the second drive system. The present invention solves the technical problem that when a traditional drilling coring robot has excessive torque during drilling, the drill rod is prone to jamming or insufficient power, resulting in poor work adaptability and efficiency.

The application provides a water supply pipe network corrosion pipe section identification and diagnosis method based on water quality inversion, the method collects water quality data and pipe section attribute information in a water supply pipe network area, determines the topological water flow direction based on the residual chlorine decay characteristics, determines the appropriate diagnosis node and target independent pipe section, monitors the water quality parameter change characteristics in the pipe section, combines the water quality change amount and the quantitative evaluation model of the pipe section corrosion degree, realizes the target positioning of the corrosion pipe section and the rapid inversion diagnosis of the corrosion state, the input layer of the model is the water quality change characteristics and pipe section information between the pipe network diagnosis nodes, the operation layer adopts an algorithm based on the water quality decay characteristics and the corrosion state mapping relationship, and the output layer is the pipe section corrosion state score, when the diagnosis result is lower than the preset safety threshold, the warning information and the maintenance suggestion are generated, the application can realize the diagnosis effect with the determination coefficient exceeding 0.95, and effectively improves the safety and reliability of the operation management of the water supply pipe network.

The invention discloses an intelligent direct-drive slurry pump and a regulation and control method thereof, and belongs to the field of slurry pumps. The intelligent direct-drive slurry pump comprises a pump body, a permanent magnet direct-drive motor, a sensor group and a control system, the pump body comprises a pump shell, an impeller, an inlet section and an outlet section. The permanent-magnet direct-drive motor comprises a main shaft; the sensor group comprises a strain gauge, a miniature thermocouple, a miniature vibration accelerometer, a sensing film, an electromagnetic flowmeter and a pressure sensor. The torque, the power, the temperature, the fault characteristic frequency, the flow, the pressure and the axial and radial abrasion loss of an impeller of the direct-drive slurry pump are collected in real time through the sensor group, and the running state of the direct-drive slurry pump and intelligent sensing of a drive transmission system are achieved; perceptual data are fused, the rotating speed / flow is adjusted by controlling the rotating speed of a main shaft and the opening degree of an electromagnetic switch valve to achieve hydraulic performance full-life-cycle compensation based on a rotating speed / flow-lift / efficiency cooperative matching self-adaptive robust control method, and then intelligent direct-drive slurry pump self-adaptive life prolonging regulation and control are achieved.

The present application provides a vehicle side collision control method, device, electronic device and storage medium, the method comprising: obtaining the lateral distance of an obstacle and current motion information of the vehicle, determining the collision control time according to the current motion information and the lateral distance of the obstacle, the collision control time being used to characterize the time corresponding to at least one of avoiding a collision and causing a collision between the vehicle and obstacles on both sides, and performing at least one of lateral collision warning control and lateral collision braking control on the vehicle based on the collision control time, wherein the lateral distance of the obstacle is obtained by inputting the images of the two sides of the vehicle body to be inspected corresponding to when the vehicle starts to turn into the environmental model on both sides of the vehicle body for obstacle detection, and the environmental model on both sides of the vehicle body is obtained by training based on historical images on both sides of the vehicle body and multiple obstacle label information; the present application reduces or even avoids side scraping collisions through intelligent perception of obstacles on both sides of the vehicle body, protects the safety of the vehicle body, and improves the safety of vulnerable traffic participants in the environment on both sides of the vehicle body.

The invention discloses an auxiliary control monitoring patrol system for an intelligent substation, which is used in the field of power transmission and transformation project design and comprises an operation and maintenance centralized control scheduling unit, a comprehensive equipment operation and maintenance unit and an operation and maintenance interaction unit. The operation and maintenance centralized control dispatching unit is used for protecting, measuring and controlling the transformer substation, and regulating and controlling the comprehensive equipment operation and maintenance unit and the operation and maintenance interaction unit in a combined manner; the comprehensive equipment operation and maintenance unit is used for monitoring primary equipment, secondary equipment and a loop of the transformer substation on line and implementing safety protection on the transformer substation; and the operation and maintenance interaction unit is used for information interaction between the comprehensive equipment operation and maintenance unit and the centralized control scheduling unit. According to the invention, a novel digital intelligent substation auxiliary control monitoring and patrolling system is constructed, functions of online monitoring, intelligent patrolling and the like are added, front-end equipment configuration and terminal equipment transmission modes are re-integrated, and panoramic dynamic monitoring, comprehensive intelligent sensing and omnibearing real-time monitoring of the substation are realized.

The present application relates to the technical field of intelligent surveying and mapping, in particular to a real estate surveying and mapping optimization method and system based on AI. In the present application, boundary error data is generated by quantifying the deviation between global navigation satellite system coordinates and cadastral vector data, the spatial features of the real estate subject boundary are deeply extracted using a convolutional neural network, and targeted boundary fitting correction is performed on the super-limit point position in combination with the error data, overcoming the passive acceptance and subjective judgment of errors in traditional data processing, realizing intelligent perception and adaptive optimization of the boundary geometric form, and subsequently using a Bayesian inference model, taking the corrected boundary as a prior distribution and fusing new observation data for probability updating, dynamically obtaining the boundary point position coordinates with minimized uncertainty, solving the problem that static data coverage cannot effectively fuse multi-source information, and then performing consistency screening on multi-temporal cadastral data based on the updated boundary.

The invention discloses an unmanned aerial vehicle inspection parking path planning method and system based on machine learning. The method comprises the following steps: collecting and screening a target image; dividing grids according to the target image and acquiring brightness data of each grid; dividing an outdoor scene area and an indoor scene area according to the brightness data of the grid; performing corresponding path planning on different scene areas to obtain an aerial photography path; performing multi-index comprehensive evaluation on the aerial photography path to obtain a qualified aerial photography path; evaluating an air route image and recording an inferior image during routing inspection aerial photography; taking the inferior image as feedback input, and generating a new post-endurance shooting path; and continuing routing inspection aerial photography and updating to obtain an optimal aerial photography path meeting the air route quality.

The invention, which relates to the technical field of the road traffic safety facilities, discloses an LED solar pile security system based on network interconnection remote control switching of warning voice, comprising an intelligent environment sensing module, a data analysis module and an intelligent control module. The intelligent environment sensing module collects environment parameter data, processes the collected data and uploads the processed data to the data analysis module; the data analysis module receives the processed data, judges a working mode in real time, predicts a people flow peak and environment change, and provides mode switching suggestions and parameter optimization schemes for the system; and the intelligent control module automatically adjusts the LED brightness according to the environment illumination and the people flow density, switches working modes according to the environment and people flow conditions, and realizes the intelligent operation of the system through multi-pile cooperation and regional linkage. According to real-time data such as illumination intensity, visibility and people flow density, the brightness and the flicker mode of the LED can be automatically adjusted, and the optimal warning effect can be provided in different scenes.

The present application relates to the field of civil engineering and traffic geotechnical engineering, solves the problems of easy breakage of probe, non-dense testing and point cloud distortion of bumpy road, provides a roadbed construction quality multi-index integrated in-situ detection system and method, which comprises a robot platform and a compaction quality detection module, a geometric appearance index detection module and a main control and data fusion center carried thereon; the main control and data fusion center is used for: driving the robot platform to travel on the set cruise route and stopping at the preset grid physical detection station, and then activating the lateral translation of the compaction quality detection module, the pre-pilot hole drilling and the probe extrusion penetration action in sequence; during the compaction degree and moisture content measurement, the current relative coordinates are grabbed as the measurement point position label, and are combined into a position-quality label package; the compaction quality and geometric appearance continuous detection report of the whole roadbed is independently output, and the multi-index integrated efficient detection and intelligent perception of roadbed construction quality are realized.

The present application relates to the technical field of vehicle-mounted human-computer interaction, and provides a vehicle-mounted multi-modal human-computer interaction method and system, which comprises the following steps: based on a specific change state, adjusting the collection parameters and processing mode of a visual input signal to improve the quality of the visual input signal, obtaining an adjusted visual input signal; at the same time, adjusting the preprocessing parameters and processing mode of a voice input signal to improve the quality of the voice input signal, obtaining an adjusted voice input signal; according to the influence degree of the environmental state judgment result on the visual input signal and the voice input signal, adjusting the weight of the visual input signal and the voice input signal in the judgment of the driver's intention, obtaining a modal weight; comprehensively processing the adjusted visual input signal, the adjusted voice input signal and the modal weight to judge the operation intention of the driver, and outputting an operation intention judgment result. The present application has the effect of improving the accuracy and safety of vehicle-mounted human-computer interaction.

The present invention provides an all-round intelligent anti-collision system and method for underground trackless equipment, which relates to the field of anti-collision technology for underground trackless equipment. The system includes: an edge computing processing unit, a signal input and output unit, a handheld positioning card, a ranging radar unit, an infrared camera fill light unit and a 360° omnidirectional positioning base station unit; the edge computing processing unit is respectively connected to the signal input and output unit, the ranging radar unit, the infrared camera fill light unit and the 360° omnidirectional positioning base station unit, the handheld positioning card transmits a narrow pulse signal to the 360° omnidirectional positioning base station unit, and the handheld positioning card and the 360° omnidirectional positioning base station unit transmit communication signals to each other. The technical solution of the present invention overcomes the problem that the prior art cannot accurately perceive approaching personnel or fixed lanes, which easily causes misjudgment and misjudgment.

The invention relates to the technical field of data communication, and discloses a router hardware acceleration processing method and system based on a heterogeneous architecture, and the method comprises the steps: generating a hardware acceleration instruction containing a physical memory address pointer of a to-be-processed data packet; writing the hardware acceleration instruction into a hardware task queue mapped to a special accelerator address space, and triggering a doorbell interrupt signal after writing is completed; in response to the doorbell interrupt signal, reading a hardware acceleration instruction by the special accelerator according to an instruction sequence in the hardware task queue to obtain a physical memory address pointer, and directly capturing a to-be-processed data packet from a host memory through the physical memory address pointer for acceleration processing to generate a processing result; and the general processor obtains a processing result, updates a local routing table item according to a routing update field in the processing result, and executes a final forwarding action of the to-be-processed data packet. According to the invention, the data processing efficiency of the network in an ultra-low time delay and ultra-high throughput scene can be improved.

The invention discloses an automatic replenishment method and system for a fresh goods shelf, a medium and a program product, and relates to the field of industrial Internet of Things services, and the method comprises the steps: determining the shelf allowance of fresh goods on a target goods shelf in a preset time period, and determining the shipment amount of the fresh goods according to the shelf allowance; obtaining the settlement amount of the fresh goods in the settlement terminal, and determining the customer temporary storage amount of the fresh goods according to the shipment amount and the settlement amount; when the shelf margin is lower than a preset margin threshold value, sending replenishment request information of the fresh goods to a replenishment management terminal; when the customer temporary storage amount is lower than a preset storage amount threshold value, monitoring image data of the position where the target goods shelf is located are obtained; and when it is determined that the fresh goods are in the preset loss quality according to the monitoring image data, goods exchange request information is sent to the replenishment management terminal. By implementing the method, the condition that the replenishment decision lags behind the actual demand can be avoided.