104results about How to "Strong real-time" patented technology

The invention discloses a load self-adaption device based on online system identification. The device comprises a track-Jacobian matrix offline generation module used for obtaining a pseudo-inverse matrix of a track-Jacobian matrix offline; the online excitation and measurement module is used for online controlling the robot to execute excitation motion and measuring to obtain an actual joint response error vector; and the rapid parameter identification module is used for combining the actual joint response error vector with the pseudo-inverse matrix to obtain an inertial parameter of a target load. The track-Jacobian matrix represents a linear sensitivity relation between inertia parameter disturbance of a load at the tail end of the robot and a joint response error. According to the method, the dynamic solving process with high calculation complexity is transferred to the offline stage to be completed, and the deterministic matrix-vector operation only needs to be executed once in the online stage, so that the calculation delay of online identification is greatly reduced on the premise of ensuring the identification precision.

The invention relates to the technical field of roadbed detection, and discloses a roadbed compaction quality detection method based on ultrasonic wave collaboration, and the roadbed compaction quality detection method comprises the following steps: collecting full-wave band ultrasonic echo signals, and obtaining current environment data; calculating a longitudinal wave speed, a transverse wave speed and a wave speed ratio, and extracting an attenuation coefficient and a frequency dispersion characteristic of the ultrasonic echo signal to obtain an acoustic characteristic set; inputting the acoustic feature set and the environmental data into an environmental compensation model, outputting a standard acoustic parameter set subjected to temperature, humidity and water content correction, analyzing the standard acoustic parameter set through a soil texture classification algorithm, and judging the current soil texture type; and combining the standard acoustic parameter set and the current soil texture type into a multi-dimensional feature vector, inputting the multi-dimensional feature vector into a compactness calculation model, and calculating to obtain a roadbed compactness value of the current measuring point. According to the method, high-precision compaction degree numerical calculation is realized, and intelligent and visual whole-process support is provided for roadbed construction quality.

The invention discloses a DSP (Digital Signal Processor) online self-adaptive wavelet denoising and concentration inversion system and method for TDLAS (Tunable Diode Laser Absorption Spectroscopy) measurement, and relates to the technical field of gas spectrum detection. Comprises: a laser module for emitting semiconductor laser light; the absorption cell module is used for absorbing specific components of the laser through a gas absorption cell formed by the to-be-detected gas; the detection and amplification module is used for converting the transmission light signal into an electric signal and amplifying the electric signal through a photoelectric amplifier; the phase-locked amplification module is used for filtering and extracting noise; the digital signal processing module is used for performing digital sampling, performing wavelet denoising and signal reconstruction, performing wavelet inverse transformation reconstruction on a denoised waveform, and extracting a second harmonic characteristic parameter; and the upper computer module is used for obtaining the concentration of the gas to be detected based on a pre-established gas concentration inversion model according to the second harmonic characteristic parameters. The method is suitable for high-precision detection of trace gas, and has the obvious advantages of strong real-time performance, high precision, good system stability, good portability and the like.

The application discloses a kind of based on space alignment and timing correction multi-intersection adaptive signal control method, belong to traffic signal control field, including: through the traffic detection sensor deployed in intersection, real-time traffic state data are collected and sent to signal lamp controller;According to road network topology, send cooperative data to downstream intersection;Traffic flow and candidate phase set are constructed;The traffic data associated with candidate phase is aggregated as demand value and executes ordering transformation to obtain combination state;To combination state, execute spatial feature alignment processing and map as state feature vector;State feature vector is input into near-end strategy optimization controller, and output target phase and basic phase duration;The traffic flow information of last phase period on upstream intersection is combined to carry out timing correction to basic phase duration;Drive signal lamp hardware to execute and generate reward feedback and update near-end strategy optimization controller parameter.The application realizes the cooperative optimization of multi-intersection traffic signal, improves the traffic efficiency and adaptive capacity.

The utility model discloses a motor stalling detection device, which is characterized in that a rotor is added on a rotating shaft of a motor to be detected, a stator is arranged around the rotor, and the rotating shaft of the motor to be detected drives the rotor to rotate, so that the stator cuts magnetic induction lines, and an electric wire connected to the stator generates voltage and current. The rotation condition of the to-be-detected motor can be judged by detecting the voltage and the current, and when the motor is blocked, a response can be made in time.

The invention discloses a laser scanning imaging detection system for a large belt conveyor, and relates to the technical field of laser scanning imaging, a laser scanning module is used for carrying out full-width laser scanning on the running surface of a conveyor belt, and a data acquisition module obtains continuous point cloud data frames and caches the continuous point cloud data frames to form a sliding point cloud sequence; the reference modeling module performs curved surface fitting on the point cloud sequence to establish a band body reference model; the defect positioning module identifies a local abnormal region based on the height deviation; the feature extraction module extracts multi-dimensional morphology parameters of the abnormal region to form defect candidate vectors; the defect identification module inputs the vector into a lightweight convolutional neural network, and outputs a defect type and a confidence score; the alarm output module triggers an alarm when the threshold value and the inter-frame continuity condition are met; the system has the characteristics of high detection precision, strong robustness and intelligent recognition, and is suitable for online detection of surface defects of the conveyor belt in a complex environment.

The invention discloses an oil and gas pipeline risk gradient dynamic management and control method based on multi-dimensional risk data, and particularly relates to the technical field of risk identification. The method comprises the steps of collecting structural data, environmental data, operation monitoring data and human factor data, and constructing a unified risk feature vector; extracting dominant risk factors based on principal component analysis, constructing a space-time joint risk evolution model, and identifying risk abrupt change points; calculating risk levels according to the risk change gradient and a scoring function, and dividing multiple levels of risk gradient intervals; constructing a resource matching priority table, calling a strategy library to implement differential processing, and updating a risk level based on a feedback result; according to the method, dynamic risk identification and optimal resource configuration are realized, and the intelligence and refinement level of oil and gas pipeline risk management and control is improved.

The application relates to a CAD drawing sharing and discussing system, which comprises a first terminal, one or more second terminals, a first CAD drawing sharing module and a first instant messaging module in the first terminal, a second CAD drawing sharing module and a second instant messaging module in each of the one or more second terminals, the first CAD drawing sharing module and the second CAD drawing sharing module transmitting and sharing CAD drawings with each other, and the first instant messaging module and the second instant messaging module transmitting instant messaging information with each other. In the application, each terminal can look at the CAD drawing while instant messaging, so that each party of CAD cooperation can view the CAD drawing at any time during the communication and discussion, which is convenient and fast.

This application provides a portable oil and gas well fluid level monitoring system and method, relating to the field of underground wellbore fluid level monitoring technology. The system includes: a virtual instrument platform configured with a LabVIEW-based program for casing pressure signal acquisition and control, a sound-generating device control program, and a sound wave signal acquisition program; a portable acquisition instrument including: a USB data acquisition card, a pressure transmitter, a sound-generating module, and a microphone; the pressure transmitter acquires pressure information at the inlet of a normally closed solenoid valve within the sound-generating module; when the pressure information reaches a preset pressure, a pressure ready signal is generated; when the pressure ready signal is valid, the sound-generating module is controlled to generate infrasound; and the infrasound reflection signal received by the microphone is acquired, processed by a MATLAB-based signal processing program, and displayed in the user interface of the sound wave signal acquisition program. The implementation method provided in this application is beneficial for improving the efficiency and safety of oil well production.

This invention relates to a markerless real-time registration and tracking method and system for mandibular surgery. The method includes the following steps: the patient performs multiple opening and closing movements of the upper and lower jaws while the robotic arm is fixed, and the system synchronously records the changes in the angles of each joint of the robotic arm; based on the forward kinematics of the robotic arm, the continuous motion trajectory of the distal end of the jaw in space is calculated to form an actual jawbone trajectory point cloud; a preoperative image model is formed using the actual jawbone trajectory point cloud, a simulated jawbone trajectory is constructed in the preoperative image model, and the actual trajectory is aligned using the ICP registration algorithm to achieve automatic registration; the system establishes a mapping between angle changes and the spatial posture of the jawbone to achieve dynamic tracking and visual navigation during surgery. This invention solves the problems of large errors, high complexity, many limitations, and low efficiency in preoperative image data registration technology during maxillofacial surgery, avoids the need for preoperative implantation of markers, and achieves high-precision registration, high automation, and strong real-time performance under natural conditions.

The invention discloses an observer-based satellite attitude system active fault-tolerant control method under dynamic interference, which comprises the following steps of: firstly, establishing a mathematical model of a satellite attitude system by considering external interference, actuator fault and model uncertainty, and further designing a nonlinear interference observer to estimate the external interference in real time; meanwhile, an actuator fault is dynamically estimated through a fault estimator, and an adaptive law is constructed to carry out approximation on uncertainty of a system model; and designing an anti-interference fault-tolerant controller according to a satellite attitude system model in combination with an observer, an estimator, an adaptive law and a system state to realize attitude control of the satellite. According to the method, under the action of various factors, the stability of the system of the satellite can be kept, interference factors can be accurately compensated, good robustness and practicability are achieved, and the anti-interference capability of the satellite is effectively improved.

The application provides a press operation information and operation and maintenance service edge computing system and method, which is independent of a press control PLC, comprises a dual-core edge computing controller, a data acquisition module, a communication module and sensors deployed on the press, has press information acquisition and data processing, fault diagnosis, motion pair temperature and friction block life analysis and prediction, remote data management and other functions, interacts with the main control PLC in real time to exchange press information data, and uploads the data information of the press to a cloud platform to provide support for remote service of the press. The application can obtain more press state information, effectively overcomes insufficient data analysis and processing capacity of the press main control PLC, and moves the detection sensors to the edge side, shortens the main control PLC scanning cycle, realizes real-time sensing and rapid response to the press operation information state, avoids overload, overheating, excessive wear and brake failure, and improves the safety, reliability and intelligent level of the press.

The application belongs to the technical field of application software development test, and discloses an application software development test system with real-time vulnerability detection, which comprises a code real-time collection module, a multi-dimensional vulnerability detection module, a vulnerability accurate positioning module, a vulnerability risk quantitative evaluation module, a dynamic repair guidance module, a data storage module, a visual interaction module and an iterative optimization module, and each module cooperates to form a whole-process closed-loop vulnerability detection and management and control system. The application software development test system with real-time vulnerability detection is adopted, real-time capture, accurate positioning, risk evaluation and dynamic repair suggestion output of the vulnerability are realized, and the software development test efficiency and application program security are improved.

This invention discloses a method and system for synchronous inversion of multiple atmospheric parameters, belonging to the field of atmospheric laser remote sensing technology. The probe light and the reference light are obtained by splitting laser pulses; the probe light is expanded, reflected, and then perpendicularly incident into the atmosphere, where it is scattered by the atmosphere to obtain the echo light. That is, all parameters originate from the same measurement and the same spectrum, resulting in perfect spatiotemporal consistency of the data, efficient measurement methods, and accurate measurement results. The temperature and pressure parameters in the atmosphere are calculated using the normalized scattering spectrum, and then aerosol and wind speed parameters are obtained, achieving true synchronous inversion of the four key parameters of temperature, pressure, wind speed, and aerosols for the first time. Furthermore, in applications such as meteorological forecasting, achieving synchronous measurement of atmospheric temperature, pressure, wind speed, and aerosols can save costs and improve efficiency, which has significant practical implications.

The utility model relates to the technical field of tobacco processing, in particular to a cigarette storage cabinet stockpiling height real-time monitoring device and a cigarette spreading traveling crane device comprising the same, which are positioned on two sides of an auxiliary traveling crane and comprise a base, an adjusting frame and a detection component, the adjusting frame comprises a first connecting rod and a second connecting rod, one end of the first connecting rod is hinged to the outer side of the base through a first damping shaft, the other end of the first connecting rod is hinged to the second connecting rod below the first connecting rod through a second damping shaft, and the other end of the second connecting rod is hinged to the detection assembly through a third damping shaft. The detection assembly comprises a millimeter-wave radar and a support hinged to the second connecting rod. The support is fixedly connected with the millimeter-wave radar through a damping spring. The millimeter wave radar is in communication connection with an early warning device. According to the utility model, the dust penetrating capability is enhanced through the millimeter wave radar, the vibration influence is reduced by arranging multiple damping structures, the real-time alarm of abnormity is realized by arranging the early warning device, and the monitoring accuracy, stability and real-time performance are effectively improved.

A method for planning an autonomous landing safe trajectory suitable for UAV inspection is proposed. After the UAV takes off, it acquires the current pose of the UAV, the point cloud map information of the surrounding environment, and the spatial orientation of the target point. By establishing the spatial transformation relationship between the camera coordinate system and the body coordinate system, the orientation vector relative to the ground target is calculated, and the target point is generated within the radar-sensible area. Based on the generated target point, an optimization function that minimizes the fourth derivative is constructed based on multiple high-order polynomials to generate a smooth trajectory with continuous position, velocity, and acceleration. The initial trajectory is transformed into a B-spline curve, and local trajectory segments with collision risk are optimized. A segmented penalty mechanism is designed based on the boundary threshold to guide the trajectory away from the boundary area. The time span is adjusted by calculating the trajectory derivative over-limit ratio, and a trajectory similarity cost function is introduced to ensure that the final optimized trajectory maintains the original geometric structure, thereby achieving trajectory control optimization and safe landing of the UAV.

This invention discloses an online detection system for airbag coating defects based on machine vision and deep learning, belonging to the field of airbag coating detection technology. It includes: a multispectral imaging module containing visible and infrared light sources, forming a ring-shaped multispectral light source array for acquiring visible and infrared spectral images of the airbag coating surface; an FPGA-accelerated lightweight deep learning model, including adaptive convolution kernels and channel-parallel computing modules, achieving real-time inference at <50ms / frame; an adaptive illumination control module integrating an ambient light sensor and deep learning model output, adjusting light source parameters in real time through a closed-loop control algorithm; and a multi-angle imaging and image fusion module, including a ring camera array and a compressed sensing encoder, for acquiring multi-angle images of the airbag surface and generating a 3D defect distribution map. This invention achieves high-precision, high-speed, and highly robust online detection of minute defects in airbag coatings.

The invention relates to a billiard game intelligent management system based on AI visual analysis, and belongs to the technical field of management systems, and the system comprises a high-definition camera which is installed above a billiard table and is used for collecting a game video stream; the AI edge calculation box is internally provided with a GPU / NPU, runs a deep learning model and is used for performing real-time analysis on the competition video stream acquired by the high-definition camera; the billiard recognition model is a ball detection and trajectory tracking model trained based on a YOLO or DeepLab algorithm; the rule engine module is used for carrying out logic judgment according to billiard match rules; the mobile application / large screen system is used for displaying real-time scores, wonderful playback and match data; and the storage server is used for storing the video clips, the match logs and the wonderful instant marks.

The invention relates to the technical field of physiological signal detection, and provides a blood oxygen detection method and device based on dual-band signal fusion, and the method comprises the following steps: aiming at an obtained reflected signal, adopting a dual-band fusion judgment method to judge whether the blood oxygen detection device is close to a detection state, and determining whether the blood oxygen detection device is in effective contact or not; when the contact is effective, a current self-adaptive adjustment algorithm is started, and the driving current of the transmitting unit is corrected in real time; and calculating the oxyhemoglobin saturation based on the obtained reflected signal to obtain a detection result. Reliable contact detection is achieved through comprehensive judgment of the red light signals and the infrared light signals, the optical signals are maintained in the optimal working interval through the current self-adaptive adjustment algorithm, and therefore the accuracy and stability of blood oxygen measurement are guaranteed.

The application discloses a kind of barometric altitude dynamic correction method based on airborne data.First, the sliding window parameters are screened using recursive feature elimination method, and then the sliding window is initialized and updated;Clean the sliding window data, first determine whether the sliding window data is null, then correct;For the data fusion multiple methods to detect outliers and correct after completing null judgment and correction;Construct the LSTM model and optimize the sliding window size, select the window size of the best performance indicator, use the LSTM model to correct the barometric altitude dynamically.This method has the characteristics of high precision, strong real-time, etc., improves the deficiency that the existing method can only correct the barometric altitude at a specific location, realizes the dynamic correction of barometric altitude in the whole approach process, improves the obstacle safety under low temperature conditions, at the same time, has the ability to correct the barometric altitude under high temperature conditions, and can be widely used in flight operation using barometric vertical navigation program.

The present disclosure relates to a liquid flow measurement structure and a measurement system using the same. The measurement structure comprises a flow channel body, an electrode sheet assembly arranged inside the flow channel body, the electrode sheet assembly comprising a plurality of capacitive sensing electrode sheets, and a digital capacitive sensing assembly connected to the electrode sheet assembly through signal lines, configured to collect capacitive signals of the plurality of capacitive sensing electrode sheets and output capacitive data associated with liquid level height. The plurality of capacitive sensing electrode sheets are arranged in a multi-layer grid structure inside the flow channel body, the multi-layer grid structure is distributed along the flow direction of the flow channel body, and a single layer grid structure is configured to arrange a single capacitive sensing electrode sheet. Alternatively, part of the capacitive sensing electrode sheets in the electrode sheet assembly are arranged in the sidewall of the flow channel body. The present disclosure has the advantages of simple structure, low cost, high reliability, and adaptability to various extreme application scenarios.

The application discloses a non-contact cognitive load evaluation method based on infrared thermal imaging, which comprises the following steps: using an infrared thermal imager to shoot facial videos of a tester in a sitting state and when performing a cognitive task; positioning a nostril area in the facial images and extracting original breathing signals from temperature changes of the nostril area; after denoising the original signals, extracting breathing features in a time domain and a frequency domain; based on the extracted breathing features, performing feature selection, and selecting a random forest to construct a cognitive load level classification model; extracting breathing feature samples of the tester and inputting the breathing feature samples into the cognitive load level classification model to evaluate cognitive load levels of the tester. The application provides a non-contact cognitive load evaluation method which is objective, comfortable and robust.

The invention relates to a text controllable semantic perception image enhancement method and system for power equipment inspection, and the method comprises the steps: obtaining a to-be-enhanced inspection image collected by a power equipment inspection terminal, carrying out the feature extraction of the to-be-enhanced inspection image, and obtaining the image state information; and obtaining text control information corresponding to the inspection task, fusing the text control information and the image state information to generate a joint state representation, inputting the joint state representation into the trained parameter generation model, and outputting a low-dimensional image enhancement parameter vector for controlling the inspection image enhancement process by the parameter generation model. And constructing a parameterized mapping function according to the low-dimensional image enhancement parameter vector, performing pixel-level mapping processing on the to-be-enhanced inspection image by using the parameterized mapping function, and outputting an enhanced inspection image for defect detection or state evaluation of the power equipment as a final enhancement result. The method is suitable for efficient enhancement processing of the power equipment inspection image in a complex environment.

The application belongs to the field of crane trajectory planning, and particularly relates to a crane trajectory planning method driven by deep reinforcement learning, which designs a crane operation state space, an action space and a dense reward function; an improved Actor-Critic network architecture is constructed, and an HER experience replay strategy is improved to more effectively learn from failure trajectories; the method has the advantages that the strategy can be adjusted in real time according to changes in the load and the environment, and is suitable for complex and variable working conditions in a port. The method promotes the intelligent process of crane operation, reduces the influence of human factors, and has strong real-time performance and adaptability.

The invention discloses an unmanned aerial vehicle airborne ground multi-target online positioning method and system and a storage medium, an unmanned aerial vehicle is in communication connection with a vehicle end, the unmanned aerial vehicle carries out preliminary positioning on multiple ground targets and sends a preliminary geographic positioning result of the multiple ground targets to the vehicle end, and the method is executed by the vehicle end. Comprising the following steps: carrying out secondary correction on a ground multi-target preliminary geographic positioning result sent by an unmanned aerial vehicle, and projecting the corrected ground multi-target positioning result to a vehicle BEV space; target risk values of the multiple ground targets are calculated respectively, the multiple ground targets in the first data set are sorted according to the risk values from high to low, and a second data set is obtained; and the data set 2 is used for the vehicle end to carry out multi-target online positioning on the ground. According to the method, the preliminary positioning of the unmanned aerial vehicle is combined with the vehicle end correction, so that the multi-target high-precision online positioning of the road surface is realized, the vehicle end positioning calculation complexity is reduced, and the method has the characteristics of high positioning precision, strong real-time performance and the like.

The application belongs to the technical field of structural health management, and particularly relates to a multi-sensor failure compensation method based on high-dimensional feature reconstruction, comprising: initializing algorithm parameters, acquiring monitoring data by using multi-sensors, and converting the monitoring data into a matrix; standardizing observation values of the matrix to obtain a standardized data matrix, and obtaining a covariance matrix in a subspace after dimension reduction; based on an ADMM method, decomposing the covariance matrix in the subspace after dimension reduction to obtain a low-rank matrix and a sparse matrix; reconstructing missing sensor data based on the low-rank matrix and the sparse matrix to obtain a reconstructed sensor vector. The aviation aircraft sensor failure compensation algorithm based on high-dimensional feature reconstruction fully considers the coupling relationship between sensors and real-time requirements, significantly improves the prediction accuracy under the condition of missing fault sensors, and is suitable for wide application of various aircrafts such as civil aviation passenger planes and unmanned aerial vehicles.

This invention discloses a soil volumetric water content (VWC) measurement system based on LoRa-RSSI and a drone. The system comprises several underground LoRa nodes for collecting environmental monitoring data; a host computer embedded in the soil; and an aerial node carried by a small drone. Combining IoUT technology, this invention designs an innovative system for soil VWC measurement based on LoRa received signal strength and a drone. The system utilizes the changes in LoRa-RSSI between the soil's internal transmitter and the drone's aerial receiver during the drone's angular rotation. Combined with a Long Short-Term Memory (LSTM) network, it collects differential LoRa-RSSI values ​​and uses a deep learning (DL) algorithm to calculate soil VWC, achieving relatively accurate soil VWC data. This invention eliminates the need for depth measurement of VWC data, utilizes soft sensors to measure soil VWC, and offers low cost, high efficiency, and small measurement error, providing a novel approach for soil VWC measurement design.

The invention provides a dynamic monitoring method based on SD-WAN resources, a computer program product, electronic equipment and a storage medium, and the method comprises the steps: obtaining lightweight data from a client of SD-WAN service; preprocessing the lightweight data to obtain normalized data; performing time sequence analysis on the historical data to obtain statistical characteristics; and performing dynamic threshold comparison on the standardized data according to the statistical characteristics, and dynamically monitoring the resources of the client according to a comparison result and formulating a corresponding strategy. By implementing the method and the system, efficient, accurate and intelligent monitoring and early warning of customer resources and active health management and control of enterprise network operation and maintenance can be realized, the real-time performance is higher, the resource consumption is lower, and the efficiency and the reliability of SD-WAN resource management and control are remarkably improved.

The application discloses a kind of based on light spot visual identification's yarn breakage detection method of spinning machine, it is related to textile machinery detection technical field, including the following steps: in yarn production area setting image acquisition equipment, the image acquisition equipment is used to acquire the target image data of the yarn production area;The image acquisition equipment transmits the target image data into image processing equipment, the image processing equipment carries out yarn state judgment to the target image data, and outputs yarn state judgment result;The image processing equipment transmits the yarn state judgment result to PLC controller, and the PCL controller executes the safety action of pre-set according to the yarn state judgment result.Besides, it solves the problems, such as the problems of large detection delay, high false alarm rate, high hardware cost and weak generalization ability in the existing yarn breakage detection technology.

This invention relates to the field of robotic arm control technology, specifically disclosing an active vibration suppression system for a hydraulic robotic arm. The active vibration suppression system for a hydraulic robotic arm includes the following steps: Step 1, acquiring the driving force of the hydraulic cylinder of the hydraulic robotic arm as a vibration signal; Step 2, performing multi-window function filtering on the vibration signal to extract the overall trend of the vibration signal; Step 3, using a narrow time window function to identify the maximum and minimum values ​​of all signals within a wide time window function, and sliding point by point around the test point to further capture the detailed changes within the narrow time window function. If the point is the maximum or minimum value within the narrow time window function, then that point is output; Step 4, calculating the vibration index characterizing the system vibration; Step 5, calculating the joint angles of the hydraulic cylinder based on the actual stroke, subtracting the joint angle θ from the desired angle, deriving the vibration joint angle information that should be compensated, and performing compensation.