35 results about "Passive detection" patented technology

The application discloses an industrial label printing self-adaptive optimization method based on multi-dimensional defect quantification. The method realizes intelligent management and control of label printing quality through task data preparation, image acquisition and parallel diagnosis, defect quantification and shunt decision, quality trend analysis and self-adaptive tuning, and predictive maintenance warning. The core of the method is to construct a defect severity index quantification model, combine the improved YOLOv8 algorithm to realize accurate classification and root diagnosis of defects, and realize real-time fine tuning of printing parameters through a fuzzy PID self-tuning tuning engine, and match a cache level real-time bit-level check to ensure data accuracy. The application breaks through the limitations of traditional passive detection, realizes active optimization and predictive maintenance, greatly improves production efficiency and reduces the rate of defective products, ensures stable label printing quality and accurate data, and is suitable for high-speed industrial label printing scenes.

The application provides an underwater vehicle optimization cooperative detection array position method, a target optimization function of an AUV cooperative detection array position is constructed by coupling AUV detection error and AUV position error, and the optimization object is minimization of global average detection error, so that passive detection AUVs construct an array position according to maximum cooperative detection accuracy; an improved HS-DPSO fusion algorithm is adopted to iteratively optimize the target optimization function; in the local optimization process, a dynamic inertia weight adjustment strategy combining normal distribution randomness and an adaptive expectation mechanism is adopted, so that the inertia weight regularly and dynamically fluctuates in each iteration, and the ability of the algorithm to jump out of a local optimum is enhanced; and a random number is used to dynamically adjust the adaptive random weight expectation value, so that the limitation of a manually preset fixed random weight expectation value is avoided, and the adaptability of the algorithm to different detection scenes is improved. The method makes each passive detection AUV quickly obtain an optimal cooperative detection position, and improves the cooperative detection efficiency and detection accuracy of the AUV formation.

This disclosure relates to a method and computer device for controlling underwater vehicles. It pertains to the field of underwater navigation and addresses the safety and mission execution difficulties caused by underwater vehicles being detected. The method includes: constructing an underwater environment simulation model; acquiring passive detection data during the simulated operation of the underwater vehicle based on the underwater environment simulation model; training an explicit risk memory model based on the passive detection data from the underwater vehicle's operational history; generating a multi-dimensional observation vector indicating the current probability of detection based on the risk memory features output by the explicit risk memory model and instantaneous operational data; and performing memory fusion based on the multi-dimensional observation vector and the hidden state of the previous time step of the gated loop unit to output a normalized angular velocity control command to control the underwater vehicle. The technical solution provided by this disclosure is applicable to complex underwater navigation scenarios, achieving efficient and accurate autonomous decision-making for detection avoidance.

This application belongs to the field of multi-target state estimation technology. This application provides a method for joint optimization of the states of multiple passive sensors and multiple targets based on a two-factor graph. The embodiments of this disclosure first construct a passive detection multi-target measurement solution layer to obtain coarse positioning points of multiple targets as state measurements; then, a joint optimization framework is constructed containing a multi-target management layer, a multi-target state optimization layer, and a multi-sensor state optimization layer. The non-Gaussian distribution characteristics of the fused measurements and the non-Gaussian distribution characteristics of the fused measurement reprojection error are modeled using a three-dimensional Gaussian mixture model and a two-dimensional Gaussian mixture model, respectively. Then, a two-factor graph is established based on the three-dimensional and two-dimensional Gaussian mixture models; finally, the sensor attitude state and target state are jointly optimized and estimated using sliding window nonlinear least squares, and the optimization results are fed back to the multi-target management layer to form a closed-loop update.

The application discloses a UAV guiding capture and evidence obtaining system and method, which comprises: an omnidirectional sensing and communication module for passive detection of airspace radio signals and establishment of a directional communication link; a software-defined radio module for receiving, decoding, modulating and transmitting the detected signals; an edge computing unit with protocol analysis and guiding control algorithm built-in, for identifying target UAV models, analyzing or simulating communication keys, and generating guiding instructions; an integrated safety capture device for physically restraining the target UAV when it is guided to a preset position; and an electronic evidence storage module for recording remote control signals, telemetry data and communication process data. The edge computing unit identifies the target UAV through passive listening, loads a communication protocol template, analyzes or cracks session keys or frequency hopping sequences to establish a connection, sends control instructions simulating the original remote controller to guide the UAV to fly to the capture device, completes physical capture, and generates an unforgeable evidence report.

The present application belongs to the field of underwater acoustic signal processing and underwater target positioning technology, and relates to a low-cost pseudo-bistatic passive acoustic positioning method and system. The system adopts a four-element hydrophone array in combination with a single auxiliary hydrophone to form a short-baseline pseudo-bistatic structure, and has both direction-finding and ranging capabilities. Through adaptive bearing estimation, beam signal purification, Hilbert envelope anti-multipath and weighted generalized cross-correlation time delay estimation, combined with synchronization error compensation, confidence evaluation and trajectory constraint, high-precision two-dimensional passive positioning is realized. The present application uses bearing constraint to reduce the two-dimensional positioning calculation to one-dimensional distance estimation, which significantly reduces the hardware cost and system synchronization complexity while ensuring the accuracy of angle measurement and distance measurement, effectively suppresses the shallow water multipath interference, improves the positioning stability in low signal-to-noise ratio environment, and is suitable for passive detection and positioning of underwater targets in coastal, shallow water and other waters.

This application provides a method, apparatus, electronic device, and storage medium for de-identification verification. The de-identification verification method includes: generating a sensitive data feature library, which includes: sensitive data features, actively identified URL addresses, and passive data sources; responding to an active detection request, obtaining front-end content returned by the server corresponding to the URL address, and performing de-identification verification on the front-end content based on the sensitive data features; and responding to a passive detection request, performing de-identification verification on the passive data source based on the sensitive data features. Implementing the above embodiments achieves comprehensive de-identification verification of web business data.

The application discloses a natural gas pipeline leakage passive detection device and a detection method thereof, which comprises a detection shell, a detection cavity is formed in the detection shell, a detection unit is installed in the detection cavity, and a waterproof air-permeable valve is installed at an air inlet of the detection cavity; an air-permeable pipe is communicated with the detection cavity and arranged at the bottom end of the detection shell; a mounting pipe is embedded in the soil layer of a detection point and used for protecting the air-permeable pipe; a floating assembly and a rotary sealing assembly are installed in the air-permeable pipe; when the floating assembly floats upward, the rotary sealing assembly can be pushed to press and seal the air inlet; the application can be integrally buried and installed, is not easy to be damaged by construction, can resist mud water immersion and mud sand accumulation and blockage, can be stably operated for a long time, is suitable for long-distance natural gas pipeline network unattended online monitoring, has the advantages of high sensitivity, maintenance-free, flexible deployment and the like, and effectively solves the problems of traditional device power supply hidden danger, easy damage, waterproof failure and frequent maintenance.

The present application relates to the field of acute high altitude disease risk monitoring, and specifically discloses a kind of based on wearable PPG's acute high altitude disease risk continuous monitoring method, comprising: obtaining the photoelectric volume pulse wave signal and geographic elevation information collected by wearable device, constructs PPG feature vector;Geographic elevation information and PPG feature vector are respectively input into environmental branch and physiological branch Gaussian process model, obtain the estimated value and corresponding uncertainty of environmental branch and physiological branch;Based on the uncertainty of physiological branch and the difference between the estimated value of environmental branch and physiological branch, adaptive weight is calculated;According to adaptive weight, the estimated value of environmental branch and physiological branch is fused to obtain the final LLS estimated value.The present application method realizes the change from discrete passive detection to continuous active monitoring of AMS risk, and has high estimation accuracy and robustness in the complex environment of high altitude and high altitude oxygen alternation, providing reliable technical means for health protection in high altitude hypoxic environment.

This invention discloses a method and system for testing stator iron loss in a generator. The method includes the following steps: Step 1: Before the test, a finite element thermo-magnetic coupling simulation model is constructed based on the three-dimensional model and material parameters of the iron core, serving as a digital twin of the iron core; Step 2: During the excitation phase, based on the preset iron core structural parameters and target magnetic flux density, the target voltage range is dynamically calculated using an adaptive control algorithm, and phased voltage regulation is performed; Step 3: During the test phase, multi-dimensional state information of the iron core is collected synchronously. Through the implementation of this invention, a thermo-magnetic coupling simulation model is constructed before the test, and multi-dimensional state information is collected in real time during the test and the model parameters are inverted and corrected, making the digital twin dynamically consistent with the physical iron core. This provides a highly reliable virtual image for subsequent fusion calculations, achieving a leap from passive detection to active intelligent diagnosis.

The application discloses a method for direction finding of unknown coherent sources based on double relaxation solution, and belongs to the technical field of array signal processing. The application calculates the covariance matrix of array receiving signals, and performs eigenvalue decomposition on the covariance matrix, then sorts the eigenvalues to obtain the eigenvectors corresponding to the maximum eigenvalue and the minimum eigenvalue, constructs a dictionary matrix of beam domain steering vectors, and realizes convex optimization solution of the linear relationship between the dictionary matrix and the maximum and minimum eigenvectors by introducing a relaxation factor, and completes accurate calculation of the signal wave direction. The application can provide a high-precision direction finding method for the passive detection field under the condition that there are related sources and the number of sources is unknown.

The application discloses an agricultural sensor adaptive topology networking device, method and storage medium. The device comprises a sink node and a plurality of sensor nodes, the sensor node comprises a microcontroller module, an environment perception module and a multi-mode radio frequency transceiver module, the microcontroller module reads the current relative humidity and photosynthetically active radiation attenuation rate, calculates the directed link cost, and when the directed link cost exceeds the cost threshold and the current packet loss rate change slope is greater than zero, the omnidirectional microstrip antenna is cut off and the directional spiral antenna is turned on, the media access control layer radio frequency transmission power is improved, and the network topology reconstruction is initiated by executing the directional routing request with the direction identifier. The application can solve the problem of route response lag caused by passive detection, and improve the stability of network structure and communication data.

The application discloses a gas identification method suitable for low-resolution high-noise spectral data, and is suitable for low-resolution high-noise spectral data obtained by a medium-long wave infrared spectrometer or a hyperspectral imager in an open space in a passive and passive measurement mode, and performs the following steps: a) extracting spectral radiation values of a measured gas at corresponding characteristic spectral position wave number coordinates by taking preset typical gas spectral characteristic points as templates, and filtering noise interference outside the characteristic spectral position wave number coordinates; b) judging a positive-negative matching number coefficient of multiple characteristic spectrums, judging a positive-negative matching direction coefficient of the multiple characteristic spectrums, and jointly judging a characteristic vector cosine similarity, so that the dimension of the judgment is increased, and the positive-negative temperature difference change of the gas and the background is adapted; and c) comprehensively judging by multiple gas similarity sorting methods. The application effectively matches the spectral gas identification accuracy, and is suitable for application scenes limited by conditions such as an open space environment, long-distance passive detection, and low sensor sensitivity.

A system and method for measurement and correction of aero-optical and aero-thermal effects to an EO / IR sensor's window / dome on a supersonic flight-vehicle. Range-gating of laser pulses measures and separates aerodynamic and atmospheric effects. Separate control algorithms and control loops at different update rates both simplifies the control algorithms and improves overall performance. The use of a MEMS MMA having tip / tilt / piston capabilities as the deformable mirror to provide wavefront correction enhances overall performance. The corrected laser pulses may also be used to actively illuminate a target to provide both active and passive detection.

The present application relates to a kind of joint underwater acoustic target passive detection and azimuth estimation method based on YOLO model, the method is first based on the underwater acoustic data received by towed horizontal array, using wideband beam forming method extracts frequency-beam domain FBD feature, and is divided into training set and test set, and sample expansion is carried out to training set;Then, the convolutional neural network of YOLO model is built, loss function is designed, and the FBD feature sample in the training set after expansion is used to train YOLO model;Finally, the FBD feature sample in test set is input into trained YOLO model, to obtain the existence probability of target spectrum in FBD feature and the specific azimuth of target spectrum.The present application can directly input FBD feature into YOLO model, and simultaneously use regression method to obtain target existence probability and target DOA information in FBD sample, effectively utilize the joint information of target spectrum and target azimuth, can detect the existence probability of target source in the marine environment of multiple interference, while giving the specific azimuth of target source.

This invention discloses a dual-loop management method and system for rockburst disaster risk, relating to the field of coal mine safety engineering technology. The management method includes the following steps: conducting a rockburst hazard assessment, delineating rockburst hazard areas and hazard levels; real-time collection of multi-source monitoring data underground; identifying risk types, calling preset mitigation schemes for regional and / or risk management, and completing the inner-loop known risk management once the risk is eliminated; for risks of uncertain hazard types or risks that cannot be eliminated by the above-mentioned preset mitigation schemes, supplementing with large-scale mining environment disaster-inducing structure analysis; deploying active or passive detection and monitoring systems to achieve dynamic identification and assessment of rockburst hazards; implementing precise rockburst prevention and control measures and verifying the prevention and control effects; and inputting the verified and effective mitigation schemes and their corresponding risk characteristics into the aforementioned risk characteristic and measure database, integrating the accident causal chain and trajectory intersection theory to complete the dual closed-loop management.

A method and system for anti-islanding protection of multiple novel entities connected to a distribution network includes: real-time monitoring of the voltage and frequency at the grid connection point of the distribution network for passive signal detection and active signal injection, obtaining passive signal detection results and active signal injection feedback; system state identification based on the passive signal detection results and active signal injection feedback, distinguishing between non-islanding type disturbances and islanding type disturbances; generating corresponding control strategies based on the non-islanding type disturbances and islanding type disturbances combined with preset instructions from the upper-level control software; and performing corresponding anti-islanding protection operations based on the control strategies. This application solves the problems of passive detection being fast but susceptible to non-islanding disturbance interference, and active detection being highly reliable but posing a risk to system stability, by using passive signal detection and active signal injection. It improves the system's anti-disturbance and anti-maloperation / refusal-operation performance after the connection of novel entities, and accelerates the response time of anti-islanding protection actions.

This application provides a method and system for predicting oxygen content in the process of preparing monocrystalline silicon. During the preparation of monocrystalline silicon in a monocrystalline furnace, multiple key process parameters affecting the oxygen content within the furnace are collected in real time from various sensors installed on the furnace. Based on these key process parameters, target data features reflecting the changing trend of oxygen content are calculated. These target data features are then input into a pre-trained oxygen content prediction model, which outputs the predicted oxygen content. This application enables real-time prediction of oxygen content within the monocrystalline furnace based on key process parameters collected during the monocrystalline silicon preparation process. This not only overcomes the technical limitation of existing technologies that can only passively detect oxygen content after the monocrystalline silicon preparation is complete, but also effectively reduces the reliance on high-energy-consuming magnetic fields in traditional control methods, thus reducing related preparation and control costs and facilitating the promotion and implementation of the solution.

Provided are a device and a method for passively detecting tunnel excavation adverse geology. The device for passively detecting tunnel excavation adverse geology includes a plurality of detection mechanisms. The plurality of detection mechanisms are disposed in a forepoling borehole located at a working face of a tunnel. The plurality of detection mechanisms includes a protection system, a signal acquisition system, a signal transmission system, and an intelligent terminal system. The signal acquisition system is disposed inside the protection system. The protection system is configured to protect the signal acquisition system. The signal acquisition system is connected to the intelligent terminal system through the signal transmission system to transmit acquired signals to the intelligent terminal system for processing.

The embodiment of the specification provides a particulate matter concentration detection device and method, by integrating a laser emitting unit and a light signal receiving unit in the same package and sharing an optical lens assembly, a detection area is formed in the external open air, and a traditional active sampling mechanism such as a fan is abandoned, so that the sensor module is significantly miniaturized and low in power consumption. The design not only simplifies the structure, reduces the manufacturing cost and failure rate, but also realizes noiseless operation and longer service life. At the same time, the passive detection mode makes it more natural to respond to the real state of the environment air, and provides a key technical basis for realizing efficient and reliable particulate matter concentration detection in various compact electronic devices and scenes requiring long-term silent monitoring.

The present application belongs to the field of underwater acoustic signal processing and underwater target positioning technology, and relates to a low-cost pseudo-bistatic passive acoustic positioning method and system. The system adopts a four-element hydrophone array in combination with a single auxiliary hydrophone to form a short-baseline pseudo-bistatic structure, and has both direction-finding and ranging capabilities. Through adaptive bearing estimation, beam signal purification, Hilbert envelope anti-multipath and weighted generalized cross-correlation time delay estimation, combined with synchronization error compensation, confidence evaluation and trajectory constraint, high-precision two-dimensional passive positioning is realized. The present application uses bearing constraint to reduce the two-dimensional positioning calculation to one-dimensional distance estimation, which significantly reduces the hardware cost and system synchronization complexity while ensuring the accuracy of angle measurement and distance measurement, effectively suppresses the shallow water multipath interference, improves the positioning stability in low signal-to-noise ratio environment, and is suitable for passive detection and positioning of underwater targets in coastal, shallow water and other waters.

This invention discloses a method for detecting and controlling drum imbalance and collision in a washing machine, relating to the field of intelligent control technology. The method includes the following steps: First, acquiring environmental reference parameters, including basic friction torque and damping coefficient, before starting the spin cycle; then, applying dual-modal active excitation to the motor in the low-speed distribution zone, extracting a spin-drying risk feature vector corrected by the reference parameters; calculating the fluid-structure instability characterizing the risk of water accumulation based on this vector and historical adaptive coefficients; arbitrating this instability using a drum collision prevention risk arbitration model, generating a spin-drying safety index and operating condition label, and executing a graded control strategy accordingly; finally, updating the historical adaptive coefficients based on the feedback results after strategy execution, achieving self-evolution of the detection algorithm. This invention solves the problem that existing passive detection technologies struggle to identify the false balance exhibited by waterproof clothing at low speeds due to uniform fluid adhesion to the wall.

This invention relates to the field of network security and discloses a method for detecting unauthorized external connections. The method includes: acquiring and preprocessing real-time data traffic of a target monitored network via a bypass method; performing passive detection on the preprocessed traffic data based on feature matching to identify known unauthorized communication patterns; injecting probe packets carrying unique source identifiers into internal network hosts and actively probing based on the response capture results from the external network to discover unknown unauthorized external connection channels; correlating the output results of the active and passive detection processes to perform comprehensive analysis and risk assessment of the host's behavior; generating unauthorized external connection alarms based on the risk assessment results and securing relevant electronic evidence. By combining passive feature matching detection with an active probing mechanism, this method solves the problem that existing technologies relying solely on feature matching cannot discover unknown or hidden external connection channels, achieving a comprehensive detection effect for both known and unknown unauthorized external connection behaviors.

This invention belongs to the field of passive underwater target detection technology, and discloses an adaptive detection method and system for underwater maneuvering weak targets using passive sonar buoys. First, a cooperative detection buoy group is automatically constructed using a dual-maximum method. This group is used to locate underwater acoustic signals and eliminate underwater noise and interference outside the cooperative detection area. Second, the segmented sampling and processing of the positioning information is projected in both the horizontal and vertical directions. Pre-detection tracking theory and the Hough detection algorithm set are used to adaptively detect the position information on both planes, extracting points that satisfy the dual accumulation thresholds from noise and interference. If detection fails, the segmented sampling and processing are repeated, and the projection and detection process is repeated to obtain initial detection points. Finally, multi-level motion constraints are used to fuse the points on both planes to obtain a high-precision true target trajectory, thus achieving passive detection of underwater weak targets.

The present application relates to the technical field of PCB intelligent detection, in particular to a PCB warping improvement method. The method comprises: scanning the PCB placed on the quality inspection platform through a laser scanner to obtain a spectrum pattern; analyzing the deformation index of the PCB based on the spectrum pattern, and adjusting the production process of the PCB based on the deformation index when the deformation index is greater than a preset threshold. The present application obtains the spectrum pattern through the laser scanner, represents the height information with RGB value, restores the actual height distribution of each point on the whole PCB bare board, then converts the complex spectrum pattern into a comprehensive deformation index, so that the warping degree of different batches has a comparable numerical scale. When the deformation index exceeds the preset threshold, not only an unqualified conclusion is given, but also the production process of the PCB is further adjusted based on the deformation index itself, realizing the leap from passive detection to active improvement, which can effectively reduce the scrap rate and improve the yield stability of batch production.

The application discloses a dining chair production and assembly system and a process thereof, and relates to the technical field of production and assembly.The system comprises a position detection module, a reference hole acquisition module, a point cloud receiving module, a deviation detection module and a reference correction module.Through three-dimensional scanning, the point cloud of the finished dining chair is obtained, and the assembly deviation values such as the perpendicularity of the chair leg and the levelness of the crosspiece are obtained by comparison with the standard model.The deviation statistics of the qualified products of the historical batches are used to generate the reference hole theoretical data, and the statistical mean value is used as the reference for the deviation correction of the subsequent batches, so that the assembly quality is changed from passive detection to active optimization, the consistency of the assembly precision between batches is improved, and the problems of poor consistency of the assembly precision, large quality fluctuation and inability to continuously optimize caused by the batch difference of wood in the dining chair production and assembly process in the prior art are solved.

The application belongs to the technical field of distributed multi-sensor passive detection multi-target tracking. The application provides a factor graph optimization passive detection multi-target tracking method based on a Gaussian mixture model. The embodiment of the disclosure distributes multi-target batch numbers by constructing a distributed passive sensor cooperative coordinate system and combining the same target determination results between two sensors; based on two-dimensional observation of the sensor, a direction finding line is calculated, the same batch number direction finding lines are combined, a least square method is used to obtain a multi-target position estimation point set, and a weighted fusion is used to obtain a multi-target rough positioning point; a Gaussian mixture model is used to model and fuse the measurement distribution characteristics, an expectation maximization algorithm is used to solve the parameters and complete the solvable conversion of the optimization problem; a factor graph optimization model containing multiple factors is constructed, a sliding window optimization is used to realize state estimation, and the Markov distance and the Hungarian algorithm are combined to complete trajectory association and state updating; and the performance of distributed sensor passive detection multi-target tracking is effectively improved.