19results about How to "Fix false positives" patented technology

The invention provides a method for regulating and controlling a hydrodynamic balance valve with a real-time load feedback function, and the method comprises the steps: collecting the strain, water level, gas, vibration and motor current data of the balance valve in real time, constructing and utilizing a comprehensive load balance model, and calculating the effective safety torque of the balance valve in real time at an edge calculation layer; a mechanical wear degradation factor is calculated based on the action history and the current variance of the locking mechanism, and the instantaneous instability risk probability is calculated in combination with the effective safety torque and the current locking torque; according to the instantaneous instability risk probability, an output mode of a locking mechanism is dynamically adjusted to execute a graded locking action; and periodically calculating a full-life-cycle health degree index, and automatically generating a maintenance or replacement work order when the full-life-cycle health degree index is lower than a preset threshold value. According to the invention, the conversion from passive alarm to active defense is realized, and the safety and operation and maintenance efficiency of the urban balance valve in rainstorm, heavy load and corrosion environments are obviously improved.

The invention relates to the technical field of handbag material surface defect image detection, in particular to an environment-friendly handbag material surface defect image detection method and system, and the method comprises the following steps: obtaining image data of the surface of an environment-friendly handbag material; dividing the image data into a plurality of local areas; for each local area, extracting image features representing visual features of the local area; establishing a normal feature range of the local area, and continuously adjusting the normal feature range in combination with the environment information; comparing the current image feature with the continuously adjusted normal feature range to identify an abnormal region deviating from the continuously adjusted normal feature range; and according to the image feature mode of the abnormal region, natural textures and defects are distinguished, and defect information is output. According to the method, natural textures and real defects on the surface of the environment-friendly handbag material can be effectively distinguished, potential defects with low contrast and fuzzy edges can be identified, and the accuracy and reliability of detection are improved.

The application relates to the technical field of yaw slip ring state monitoring, and specifically discloses a multi-dimensional state operation monitoring method and system based on a yaw slip ring, which comprises the following steps: obtaining an original operation data set of the yaw slip ring, wherein the original operation data set contains operation parameters in the electrical, mechanical, attitude and environmental dimensions which are collected via sensors and subjected to redundancy checking; constructing a noise suppression matrix based on the physical mechanism of the yaw slip ring, filtering isolated fluctuations and cross-modal abnormal values in the original operation data set by using the noise suppression matrix, and inputting the noise suppression matrix into a convolutional neural network model to obtain a fusion feature vector. By introducing the noise suppression matrix constructed based on the physical mechanism and the channel interaction mechanism guided by the physical topology, the technical problem that a lightweight model is difficult to extract cross-modal strong coupling features at an edge end is effectively solved, and the sensitivity and accuracy for early composite faults are significantly improved without increasing the computing power burden.

The application discloses a battery replacement cabinet safety control method based on an intelligent Internet of Things, relates to the technical field of thermal safety monitoring and control of a battery replacement cabinet, and utilizes a multivariate time sequence anomaly detection model combined with a long short-term memory autoencoder and an attention mechanism to extract deep features from voltage, current and environmental temperature data, effectively identify internal heat accumulation initial signals that are difficult to capture by external sensors, overcome the limitations of traditional fixed threshold monitoring, dynamically learn normal charging and discharging modes, sensitively capture subtle abnormal changes, thereby advance the early warning time, and reduce the risk of missed reports caused by surface temperature lag; a dynamic threshold mechanism is based on quantile numbers of a target false alarm rate and working condition parameters and is adaptively adjusted, so that the system can flexibly cope with complex factors such as different environmental temperatures and battery aging degrees, avoids the false alarm problem caused by a unified threshold, and improves the early warning accuracy.

This invention provides a drop-proof detection unit and a photovoltaic panel cleaning robot. The drop-proof detection unit includes a substrate, an ultrasonic sensor, a first laser sensor, and a controller. The ultrasonic sensor and the first laser sensor are both mounted on the substrate, and are spaced apart in a first direction. The controller is mounted on the substrate and electrically connected to the ultrasonic sensor and the first laser sensor. This invention's drop-proof detection unit, by simultaneously utilizing both ultrasonic and laser sensors, achieves comprehensive detection of the edges and gaps of photovoltaic panels, effectively avoiding false alarms that may occur with a single sensor. It also reduces work interruptions caused by signal anomalies. This allows the photovoltaic panel cleaning robot to not only avoid falls but also clean multiple photovoltaic panels across gaps, improving cleaning efficiency.

The embodiment of the invention provides a parking brake isolation device and a railway vehicle, and the device comprises a parking control box and a parking monitoring box which are oppositely arranged at the two transverse ends of the lower part of a vehicle body respectively; the parking control box comprises an air supply cock, a pressure reducing valve, a parking brake electromagnetic valve, a two-way check valve and a first parking isolation cock. The parking monitoring box comprises a second parking isolation cock, a first pressure switch and a second pressure switch. An air supply cock, a pressure reducing valve, a parking braking electromagnetic valve, a two-way check valve, a first pressure switch and a second pressure switch are arranged, and double monitoring and intelligent judgment of the parking braking state are achieved in combination with a control main part, the parking monitoring box and the parking control box achieve bilateral synchronization of parking braking isolation operation when a vehicle enters a platform in the forward direction and the reverse direction, braking state recognition accuracy and the fault-tolerant capability of the system are effectively improved, and the problem of false alarm caused by faults of a pressure switch in a traditional system is solved. And the safety, the stability and the maintenance efficiency of train operation are improved.

The invention discloses a light-oxygen dual-response anti-counterfeiting composition and application thereof, and belongs to the technical field of anti-counterfeiting. The composition consists of a polymer matrix, a fluorescent probe molecule with a free radical response discoloration function, and an RAFT (reversible addition fragmentation chain transfer) reagent serving as a free radical source. Aiming at the technical pain point that an existing anti-counterfeiting material is prone to false alarm, an oxygen-dependent photochemical response mechanism is constructed by utilizing an RAFT reagent and a fluorescent probe: under an oxygen-free sealing condition, fluorescent probe molecules keep chemical stability to illumination; after the package is opened and is in contact with oxygen, the RAFT reagent in the system is uniformly split to generate free radicals through ultraviolet irradiation, and oxygen in the environment is synchronously activated to generate reactive oxygen species (ROS). ROS and free radicals synergistically induce probe molecules to generate irreversible chemical structure transformation, so that a pi conjugated system of the probe molecules is expanded, a HOMO-LUMO band gap of the probe molecules is reduced, remarkable red shift of an emission spectrum is generated, and visual irreversible color change is realized. The method has the advantages of high environmental stability, accurate response, irreversible recording and the like, and can be widely applied to anti-counterfeiting traceability and opening state recording of high-value products.

This invention discloses a lightning potential forecasting method integrating cloud microphysical conditions, belonging to the field of lightning potential forecasting technology. It involves acquiring numerical weather prediction data for a target area, constructing a cloud microphysical dynamic-water vapor coupling index for the target area, and determining the meteorological forecast results for the target area based on the cloud microphysical dynamic-water vapor coupling index. Based on the meteorological forecast results, convection parameters for the target area are extracted, and convection information for the target area is obtained through comprehensive analysis. Based on the convection information, mixed-phase cloud microphysical parameters for the target area are extracted. Based on the mixed-phase cloud microphysical parameters, collision intensity characterization parameters for the target area are determined. The collision intensity characterization parameters are then corrected for charge separation capability based on numerical weather prediction data to obtain an effective collision intensity index for the target area. Based on the effective collision intensity index, the lightning potential index for the target area is determined, and the lightning potential information for the target area is output, thus improving the accuracy of lightning potential forecasting.

The application discloses a kind of based on time-frequency phase feature rolling bearing fault diagnosis and physical positioning method, this method includes: obtaining the vibration time series signal at two different circumferential positions of the monitored bearing seat, and carry out time-domain impact feature enhancement processing;Two enhanced impact signals are analyzed by cross spectrum, and extract coherence function spectrum and cross-phase spectrum;According to the energy peak value of impact signal, coherence function spectrum and cross-phase spectrum set fault diagnosis condition, find out the real fault characteristic frequency that meets the condition, compared with various fault characteristic frequency theoretical value, determine the fault type of rolling bearing;According to the geometric relationship of fault point and two vibration collection points on bearing seat, establish circumferential angle solution model, the stable phase difference and collection point position are substituted into model, and the circumferential position of fault point on bearing seat is calculated.The method can distinguish real bearing fault from external random disturbance from physical principle, greatly improve the reliability and accuracy of diagnosis.

The invention discloses a network intrusion detection method for multi-feature time sequence atlas collaborative coding, which aims at the characteristics of high network flow data dimension, feature isomerism and strong time sequence dependence, takes a plurality of continuous flow records belonging to the same source IP as a time sequence, and performs decomposition based on GASF to form a two-dimensional time sequence atlas. By using the two-dimensional space texture processing capability of a convolutional neural network, stacking the generated feature maps in sequence according to channel dimensions to form a multi-channel tensor with time sequence-feature relevance; meanwhile, in order to solve the problem of high-dimensional feature redundant noise, a channel attention mechanism is introduced, so that the model can adaptively learn the weight of a feature channel, and passively accept full data to actively pay attention to a key attack mode, thereby solving the problem that tiny attack features cannot be captured in a complex network environment.

The application discloses an industrial equipment health evaluation method and system based on acoustic analysis, and relates to the technical field of equipment evaluation, comprising: setting a plurality of excitation reference points and a plurality of groups of microphone arrays, applying a reference response, calculating a transfer function matrix for each frequency to obtain a reference impulse response; calculating a deviation index according to the transfer function matrix, the reference impulse response and the measured impulse response waveform respectively; spatially fusing the deviation indexes of multiple microphone channels to calculate a single-action component combined abnormality and a component comprehensive abnormality, setting a screening threshold range, screening suspicious components and calculating a confidence degree, and performing abnormal identification; by establishing a transfer function matrix and a reference impulse response template under the health state of the equipment, the acoustic propagation characteristics of each individual equipment are taken as personalized reference standards, and the individual difference false alarm problem caused by the use of a general threshold in the prior art is solved.

The utility model relates to the field of household daily necessities, and provides an auxiliary positioning early warning device for a drilling platform. The auxiliary positioning early warning device for the drilling platform comprises a rectangular long frame, a flooding detection mechanism, a GPS positioning module, a 4G transmission module, a controller and an alarm mechanism, and the front end face and the rear end face of the lower end of the rectangular long frame are fixedly sleeved with U-shaped mounting plates. According to the auxiliary positioning early warning device for the drilling platform, through cooperation of the floating ball and the waterproof pressure sensor, instantaneous wave interference is avoided, the water logging condition can be accurately detected, the false alarm problem of a traditional water level sensor is avoided, meanwhile, the position of the platform is monitored in real time in combination with the GPS positioning module, and the positioning accuracy is improved. Once a safety range is exceeded, offset early warning is triggered immediately, simultaneous operation of multi-dimensional safety monitoring, flooding alarm and offset early warning is realized, risks can be analyzed in a linkage manner, whether water enters due to drifting or not is analyzed, decision time is shortened, and emergency response can be optimized.

The utility model discloses a self-locking device for controlling the liquid level of a solution storage tank, and relates to the technical field of liquid storage and control equipment. Comprising a liquid storage tank, a liquid level synchronous control assembly arranged on the outer side of the liquid storage tank and used for controlling the height of the liquid level in the liquid storage tank, and an auxiliary flow blocking assembly arranged on the inner wall of the liquid storage tank and used for conducting secondary locking operation on the liquid storage tank. The liquid level in the liquid storage tank can be synchronized in real time without electric power by utilizing the communicating vessel formed by the intercommunicating pipeline, the fixed barrel and the liquid storage tank, the problem of false alarm caused by circuit faults of an electronic sensor is avoided, the reliability of the device is improved, automatic liquid level control is realized by utilizing the control valve and the liquid level switch, preliminary locking is formed, and the safety of the device is improved. The device is simple in structure and high in response speed, secondary locking is formed on a solution in the liquid storage tank under the matching action of the spoiler and the limiting sleeve, circulation of the solution can be forcibly blocked under the extreme conditions of power interruption and a control system fault lamp, and the practicability of the device is improved.

The invention provides a thermal energy storage system pipeline vibration anomaly identification method, and belongs to the technical field of thermal energy storage systems. Vibration sensors are installed at key nodes of a thermal energy storage system pipe network, a topology model based on a graph theory is constructed, and wavelet packet decomposition and empirical mode decomposition technologies are adopted to extract multi-dimensional vibration feature vectors; a working condition identification code system is established, a longest common subsequence algorithm is utilized to match a historical working condition reference, an upper-layer game model with detection precision maximization as a target and a lower-layer game model with a false alarm rate minimization as a target are constructed to realize parameter collaborative optimization, and accurate positioning of an abnormal source is realized by combining finite element transfer function calculation. And according to the deviation measurement value, grading anomaly judgment is performed, and a self-adaptive monitoring frequency adjustment and sliding window database updating mechanism is adopted, so that the technical problems of insufficient pipeline vibration anomaly detection precision and relatively high false alarm rate of the thermal energy storage system are solved.

The invention relates to a carding machine web quality detection system, which comprises a dielectric plate, an upper surface of which is a smooth convex arc surface; the airflow generating mechanism is used for generating high-speed wall-attached airflow in the tangential direction of the smooth convex cambered surface; the acousto-optic fusion detection module comprises an optical imaging assembly arranged above the dielectric plate and an acoustic emission sensing array attached to the non-contact surface of the dielectric plate; the central control module is respectively connected with the optical imaging assembly and the acoustic emission sensing array and is configured to execute the following detection logics: the optical imaging assembly acquires a web image to identify visible defects, and the acoustic emission sensing array captures stress wave signals generated when hard impurities in the web collide with a dielectric plate under the pressure of wall-attached airflow; and the central control module performs space-time alignment on the image defect coordinates and the stress wave source signal coordinates to generate a web quality distribution diagram. High-speed wall-attached airflow is generated through the variable-curvature dielectric plate, the web is forcibly flattened to eliminate high-speed shaking, and the detection precision is remarkably improved.

The application provides a file monitoring method and an electronic device. The method comprises the following steps: during the running of a first operating system, changing a kernel code to replace an initial inotify event processing function in the kernel with a preset inotify event processing function; obtaining a target file operation event and target context information of a target file through the preset inotify event processing function; wherein the target file operation event and the target context information are determined by the preset inotify event processing function based on a preset first configuration file, and the first configuration file is used to record at least one target file; and recording the target file operation event and the target context information in a kernel log. By dynamically replacing the inotify event processing function and adding the context information of the file operation, the application can ensure that the key file operation is captured in time. In this way, during the problem positioning and troubleshooting process of the electronic device, the whole process of the event occurrence can be accurately restored, thereby greatly improving the maintainability of the system.

The present application belongs to the technical field of anti-seepage structure evaluation, and particularly relates to an anti-seepage structure integrity evaluation method and system based on resistivity imaging, which comprises the following steps: firstly, collecting complex admittance data of monitoring points and extracting phase loss angle features to strip the interference of underground environment humidity fluctuation through phase information; then, constructing virtual part admittance gradient features in combination with structure anisotropy correction factors to enhance the recognition degree of small damage edges; calculating seepage probability weight by using reference gradient deviation, and identifying seepage clusters based on adaptive seed point screening and eight-neighbor connected domain marking algorithm to obtain continuous seepage area; finally, calculating integrity score through a nonlinear model by introducing risk sensitivity index and area penalty weight to realize accurate early warning and positioning. The present application effectively solves the problem of poor seepage recognition accuracy under complex background interference, and significantly improves the robustness and scientificity of the evaluation result.

The invention discloses a hydropower station gas pipeline monitoring system based on multi-source data, and belongs to the technical field of monitoring analysis. The method is used for solving the technical problem of poor robustness of a monitoring system in an existing scheme. Through space-time two-dimensional correlation filtering, a dynamic characteristic matrix is fused with time domain difference and frequency domain dominant frequency components, and a sensor weight dynamic adjustment mechanism, data reliability under extreme working conditions is ensured. Through recursive estimation of a pressure fluctuation coefficient alpha and self-adaptive adjustment of a leakage risk index lambda, full life cycle pressure change accurate tracking of start-stop impact-stable operation-aging fluctuation is carried out on a hydropower station pipeline, and the problem of misinformation of single parameter monitoring is solved. Through combined input of the pressure fluctuation coefficient alpha, the leakage risk index lambda and the dynamic characteristics, the capturing capability of the LSTM on the pressure fluctuation-leakage risk coupling relation is improved, and the fault identification accuracy can be effectively improved.

This invention provides a method for segmenting and classifying real-world photo instances, relating to the field of computer vision technology. The method includes: constructing a real-world verification dataset based on the spatial distribution of the vector data to be verified; establishing an interpretation feature library containing texture and geometric features; constructing a cascaded network architecture consisting of an object detection subnetwork and a segmentation subnetwork, using bounding boxes to guide segmentation operations, freezing the segmentation encoder parameters during training, embedding interpretation feature data into the network backbone to obtain a lightweight cascaded instance segmentation model; projecting the vector data onto the image coordinate system using a spatial mapping transformation algorithm to obtain a theoretical projection area; comparing the spatial overlap and attribute consistency between the model segmentation results and the theoretical projection area to generate classification verification correction information. This invention solves the problem of the lack of an effective correlation verification mechanism between heterogeneous data, achieving automation and efficiency in ground feature verification.