8 results about "Adaptive sensing" patented technology

This application relates to the field of information technology and discloses a multi-source heterogeneous data fusion and analysis platform for smart cities. It includes a data acquisition end error calibration module, a transmission link integrity assurance module, a multi-source data fusion and cleaning module, and a dynamic timeliness management module. Each module achieves data flow through a unified data interaction protocol. The acquisition end is used to collect data from traffic cameras and environmental monitoring sensors. The data acquisition end error calibration module is used to calibrate errors generated by the data collected by the acquisition end. The acquisition end error calibration module also includes an environmental adaptive sensing unit and a device health assessment unit. Through the synergistic effect of the environmental adaptive sensing unit and the device health assessment unit, data reliability is improved from the source. The environmental adaptive sensing unit uses a pure hardware electrical signal transmission link to achieve real-time response to changes in visibility and illumination.

This invention relates to the field of coal mine safety monitoring and intelligent early warning technology, and discloses an edge computing-driven multi-parameter adaptive sensing and anomaly identification sensor network for underground coal mines. The network includes: multiple intrinsically safe intelligent sensor nodes for constructing a distributed monitoring network, comprising: a multi-parameter acquisition module for real-time acquisition of various monitoring parameters in the coal mine; an edge computing module deployed with a lightweight long-short-term relation-improved gated cyclic unit time-series prediction model, which adaptively corrects the background values ​​of monitoring parameters to dynamically generate threshold ranges and generate preliminary anomaly judgment results; a collaborative communication module that, after generating the preliminary anomaly judgment results, interacts with neighboring nodes to generate spatiotemporal collaborative verification results; and an anomaly decision module that, based on the preliminary anomaly judgment results and the spatiotemporal collaborative verification results, generates multi-parameter fusion identification results and outputs graded early warnings. This invention significantly improves the accuracy, real-time performance, and engineering feasibility of identifying precursors to dynamic disasters in underground coal mines.

This application discloses a database intelligent monitoring and early warning method based on large models and multi-dimensional sensing data, belonging to the field of power data technology. The method includes: combining historical global sensing monitoring data sequences to output a predicted fault risk index; configuring an adaptive monitoring and early warning sliding window within a preset time period; optimizing multi-dimensional sensing strategies to obtain an adaptive sensing factor cluster; and performing intelligent monitoring and early warning of cascading avalanche faults on the power database within the preset time period. This solves the technical problem of existing database monitoring and early warning methods relying on threshold judgments of a single fixed indicator and failing to dynamically adjust according to actual operational risk conditions, resulting in lagging risk perception and low early warning accuracy and efficiency.

This invention belongs to the field of optoelectronic sensing technology, specifically disclosing a reconfigurable junction optoelectronic device based on adaptive sensing computing and its fabrication method. The device includes a gate semiconductor photosensitive layer, an insulating layer, a semiconductor photosensitive window, a gate electrode, a source electrode, a drain electrode, and a Te nanofilm photosensitive layer. Compared with existing technologies, this invention utilizes gate voltage to control the conductivity of the junction transistor to dynamically change the distribution of photogenerated current at the gate-source and source-drain terminals, thereby achieving reconfigurable photoelectric polarity, i.e., achieving bidirectional positive and negative response behavior. This junction phototransistor not only significantly expands the spectral range of Te-based devices through the broad spectral response capability of the gate semiconductor photosensitive layer, enabling sensing from deep ultraviolet to infrared light; but also further achieves reconfigurable bipolar response behavior through gate voltage control of the gate semiconductor photosensitive layer and its synergistic or competitive effects with the Te photosensitive layer.

The application discloses a kind of plant carbon flux monitoring data abnormal self-adaptive sensing method and system, specifically related to ecological monitoring data intelligent processing technical field, by collecting frame serial number, receiving time stamp, original sampling time stamp, carbon dioxide mole fraction, water vapor mole fraction and vertical wind speed, establish receiving account book and sampling account book, determine receiving difference and sampling difference, further identify the sampling section to be detected, judge deviation source, write in synchronous boundary, determine closed serial number interval, and complete abnormal segment typing and index output.The application can distinguish receiving link deviation, sampling link deviation and multi-channel synchronization misplacement from the level of time sequence relationship, accurately determine the start and end boundary of abnormal segment, and complete abnormal typing according to peak-valley pairing result and backswing characteristics, form structured index output result, so as to improve the accuracy, stability and subsequent data correction, quality marking and layered processing of plant carbon flux monitoring data abnormal identification.

This invention discloses a continuous positioning system and method for high-speed rail based on feature targeting, belonging to the field of rail transit positioning technology. The system completely abandons ground transponders and satellite navigation, using only the inherent geometric features of the track itself as the sole calibration benchmark. It achieves continuous sub-meter-level positioning throughout the entire journey through multi-sensor adaptive sensing, real-time feature matching, filtering fusion, and dynamic error compensation. The sensing module is adaptable to harsh environments such as rain, snow, fog, tunnels, icing, and oil contamination; the matching module includes temperature deformation correction and anchor point fallback mechanisms; the control module can identify and compensate for slippage and attitude deviation; and the closed-loop module has emergency positioning and automatic speed limiting safety strategies. This invention significantly reduces the construction and maintenance costs of railway lines, provides continuous and stable positioning, strong anti-interference capabilities, and sufficient safety redundancy, making it suitable for various high-speed rail and urban rail vehicles and possessing strong engineering practicality.

The application discloses a tunnel blasting charging robot positioning and path planning method and system, and belongs to the technical field of tunnel engineering construction. The application constructs a three-dimensional tunnel map in real time through laser SLAM, constructs a double closed loop dynamic fusion mechanism of global pose correction and local alignment fine adjustment, corrects long distance cumulative pose drift by taking blast hole feature points as SLAM loop detection fixed anchor points, and synchronously outputs optimal global pose of the robot and accurate target coordinates of the blast hole. The MQ-RRT* algorithm is optimized and improved for the long and narrow limited space of the tunnel, tunnel axis preferential sparse sampling, dynamic target bias and charging safety constraint cost function are adopted, a multi-section continuous path suitable for charging operation is generated, local incremental path re-planning, environment adaptive sensing and hierarchical fault degradation strategy are matched, and unmanned charging operation in the whole process is realized.

This application relates to the field of biomimetic neurotechnology and proposes a pluggable biomimetic optical neural network system with adaptive sensing capabilities. The system includes a laser source, a pinhole amplifier, a digital micromirror device, a beam splitter prism unit, a photodetector, a pluggable metasurface structure, a spatial light modulator (SLM), a mirror, and a digital camera with a charge-coupled device (CCD) image sensor. This application can adjust the state of the pluggable metasurface structure according to the contrast of the input image light, and adaptively extract high-frequency information of the object based on the contrast of the surrounding environment, thereby improving the accuracy of target recognition tasks. Furthermore, the activation level of neurons in the diffraction layer can be updated in real time based on the initial classification result of the input image light, improving the dynamic adaptive adjustment capability of visual attention, and thus achieving adaptive adjustment to the perceived target.