90 results about "Time signal" patented technology

The application discloses a kind of underground space optical cable high fidelity sound restoration method based on DAS system, comprising: the real-time signal collected to optical cable is carried out data demodulation, identify whether it contains energy impact signal generated by the optical cable after being padded and being hit, if it contains, the energy abnormal distribution position in energy impact signal is positioned, obtains positioning point;Continuous analysis time domain signal of positioning point, after filtering low-frequency interference signal, phase anomaly signal is rejected;The sound signals of a plurality of equivalent sensing nodes adjacent to the positioning point are superimposed and averaged to suppress additive noise, and then the sound signal is restored.The application can realize rapid positioning according to the spatial distribution mapping relationship of optical cable, and after filtering background noise from the collected signal, the highly correlated signals of multiple spatial sensing nodes near the positioning position are linearly superimposed to suppress additive random noise, and high-fidelity sound signal restoration is realized.

This invention relates to the field of temperature measurement and sensor signal processing technology, specifically disclosing a multi-channel high-precision automatic temperature acquisition and dynamic compensation system. First, it simultaneously acquires temperature sensing signals and environmental reference signals from multiple locations. Then, based on physical rules, it constructs and optimizes an initial physical relationship containing dynamic error terms, outputting optimized parameters through an automatic optimization process that integrates data features and physical constraints. Next, it uses symbolic regression technology to analyze the optimized physical relationship, generating an explicit compensation function that conforms to metrological descriptions. Finally, it dynamically fine-tunes this function based on real-time signal characteristics to achieve accurate compensation for subsequently acquired signals. This invention improves the accuracy of temperature measurement in complex dynamic environments while ensuring the interpretability of the compensation process, the quantifiability of uncertainty, and the compliance of value transfer.

This invention relates to the field of industrial intelligent nondestructive testing, and more specifically, to an intelligent identification method for fatigue failure precursor signals of forgings under complex stress environments. The method includes: first, constructing a physical space mapping; extracting streamline vector fields based on finite element simulation data of the forging; calculating sensor path coupling factors; and quantifying the anisotropic constraints of complex stress structures on signal propagation. Next, dynamically setting the signal decomposition algorithm penalty factor according to the streamline geometric curvature; constructing a reference signal by combining the load spectrum and coupling factors; and extracting characteristic responses from stress environment monitoring data. Subsequently, calculating the real-time signal-to-noise ratio (SNR), constructing an adaptive index, and obtaining a blocking index by combining the coupling factor and directional transfer entropy. Finally, setting a dual statistical window based on the load period; and completing the identification and judgment of failure precursor signals according to their statistical characteristics. Through streamline field physical constraints and adaptive SNR modulation, the accuracy and timeliness of fatigue failure early warning are significantly improved.

The application discloses a kind of three-dimensional radar low altitude multipath detection and elevation dynamic measurement method of double channel, and the adaptive decision threshold of multipath decision model is constructed in combination with real-time signal-to-noise ratio, so that the judgment of target echo complex signal can be accurately identified the occurrence and end of multipath interference like " switch ", when target echo is interfered by multipath, start the elevation measurement method for multipath interference, significantly improve the environmental adaptability and robustness of radar;The imaginary part characteristics of complex single pulse ratio are used in combination with the adaptive threshold of signal-to-noise ratio, which is more accurate than the simple distance threshold in identifying the multipath state, with higher detection accuracy.The application uses the characteristics that phase information is distorted but still maintains segmented monotonicity under multipath environment, first locks the subdivided monotonic interval where the target is located, and then uses high-sensitivity amplitude information to perform table lookup inversion in the interval, without changing the 1T2R hardware architecture, the problem of angle measurement error caused by multipath interference is solved.

A system for monitoring subject movement is provided. The system includes one or more sensors attached to a subject. The one or more sensors monitor and provide muscle data and inertial measurement unit (IMU) data. The system also includes one or more computing devices in communication with the one or more sensors and including at least one processor programmed to: a) receive a plurality of sensor data including muscle data and IMU data; b) preprocess the plurality of sensor data to remove noise data; c) execute at least one artificial intelligence (AI) model trained with the muscle data and IMU data, where the at least one AI model outputs a classification and an identification of a subject movement; and d) provide feedback to the subject based on the classification and identification of the subject movement.

The application provides a multi-target connected unmanned relay control method and device based on reinforcement learning, which is aimed at an emergency communication scene containing a command center, a relay unmanned aerial vehicle and multiple mobile task nodes, utilizes an attention mechanism to aggregate features of variable-length multi-node observation data, processes a historical state sequence by introducing a memory-enhanced deep reinforcement learning model, extracts a belief state and outputs a flight acceleration instruction of the relay unmanned aerial vehicle, simultaneously constructs a multi-target reward function containing communication quality and flight energy consumption, dynamically adjusts weights by using an adaptive balance factor based on real-time signal strength, and performs model training in combination with signal offset exploration and a priority sequence experience playback mechanism. The application solves the technical problems of poor generalization ability, easy falling into local optimization and difficulty in dynamically balancing each optimization target of existing methods when facing dynamic changes in the number of task nodes, partial observability of the environment and multi-target conflicts of communication and energy consumption.

A short-distance distributed high-precision optical fiber time synchronization system and method are disclosed. The system consists of a master time unit, several slave time units, and several optical fiber links. In this method, the time signal of the master time unit is looped back and transmitted between the master and slave time synchronization units using an optical carrier of the same wavelength. The master time synchronization unit uses the loopback method to measure the transmission delay of the optical fiber links and adjusts the delay of the transmitted time signal, so that each slave time synchronization unit receives a time signal synchronized with the master time synchronization unit, thereby realizing the distributed transmission of the time signal.

The invention relates to the field of parameter control, in particular to a drilling parameter self-adaptive control method and system based on historical machining data, and the method comprises the steps: obtaining a global universal fingerprint curve, and determining a single machine correction factor of each machine tool according to a ratio of a single machine historical average load to a global average load; the main shaft current of the machine tool is collected in real time, a single machine correction factor is used for conducting normalization processing on a real-time signal, and a normalized material response value is obtained; obtaining normalized material response values reported by a plurality of machine tools in a preset sliding time window, and calculating a global hardness trend index by adopting a multi-source weighted voting mechanism; and according to the global hardness trend index and the single machine correction factor, dynamically reconstructing a self-adaptive proportionality coefficient of a PID control algorithm, and outputting a target feeding speed by using the PID control algorithm to realize self-adaptive control of the drilling parameters of the machine tool. According to the invention, self-adaptive control of machine tool parameters based on historical data is realized.

This invention discloses a self-calibration method and system based on the metrological function of an intelligent measurement switch, relating to the fields of electrical variable measurement and magnetic variable measurement technology. The specific steps of the method are as follows: In a standard metrological test environment, the inherent step electrical signal of the contact pre-breakdown is collected as the sole calibration benchmark; parameters are extracted to construct a full-condition benchmark library and encrypted for read-only storage; real-time signals are synchronously acquired during equipment operation with phase-locked loop, and orthogonal decomposition is used to purify and match benchmark features; combined with multi-physics parameters, errors are separated through a decoupling model, and amplitude and phase errors are calculated; calibration coefficients are generated and transmitted via a verification bus; calibration verification and fault tolerance processing are completed through dual-channel verification. This invention achieves in-situ calibration without shutdown by using the inherent signal of the device as a benchmark and encrypting its storage; multi-source errors are separated through phase-locked acquisition and orthogonal decoupling, improving metrological correction accuracy; and a closed loop is formed through an adaptive algorithm and dual-channel verification to ensure accurate calibration and stable equipment operation.

The application discloses a substation signal intelligent monitoring method and system based on an agent, relates to the technical field of substation signal monitoring, and comprises the following steps: constructing a physical abnormal conduction relationship corresponding to a physical topology link and a signal abnormal conduction relationship corresponding to a signal topology link according to the physical operation mechanism and the signal transmission mechanism of power equipment; classifying power equipment in the monitoring range of the same environment monitoring equipment into the same monitoring set, and acquiring spatial state deviation influence according to historical signal data and historical spatial states of the same type of power equipment in different monitoring sets; outputting the comprehensive abnormal probability of each power equipment according to real-time signal data, spatial state deviation influence, the physical abnormal conduction relationship and the signal abnormal conduction relationship; and outputting an abnormal positioning result according to the comprehensive abnormal probability by using the reasoning mechanism of the agent. The application takes into account the abnormal sensing sensitivity and the alarm output reliability.

A method for error event analysis performed by an electronic device includes: in response to an error event of an autonomous driving system, feeding a sequence of signal states, collected from the autonomous driving system into a prediction model, where the prediction model is trained based on signal states collected from a plurality of autonomous driving systems for predicting, based on a first signal state, a second signal state, the first signal state representing signals collected at a first time, and the second signal state representing signals collected at a second time succeeding the first time; converting the error event into an event signal state having signal values at an event time; comparing the second signal state with the event signal state; and in response to the second signal state matching the event signal state, tracing the error event back to the first signal state as a root cause.

The application provides a kind of underwater fish length measurement method based on binocular vision and attitude estimation, belongs to image recognition and underwater measurement technical field.The method constructs a new type of cascaded perception measurement framework combined with underwater context attention enhancement module and geometric statistical filtering engine;The framework is based on a top-down target detection and key point positioning cascaded network, introduces an underwater context attention enhancement module at the key point feature fusion end, and introduces a spatial orthogonal circular arc compensation and double-stage time signal filtering mechanism at the three-dimensional object understanding algorithm end, through the collaborative optimization of visual feature topology perception and space-time joint filtering, realizes the accurate capture of fish key points under light and shadow interference, and effectively suppresses the non-rigid swimming deformation and depth noise jump, effectively solves the distortion problem of underwater dynamic length measurement, significantly improves the anti-distortion ability and overall output stability of measurement in underwater dynamic environment.

The application relates to the technical field of substation debugging and monitoring, in particular to a device for a new substation debugging handheld monitoring background, which comprises a handheld terminal body and a handheld computer connected with the handheld terminal body; a wireless communication unit, a quantum encryption chip module, a laser radar scanning unit, a signal strength acquisition unit, a three-dimensional reconstruction module, a multi-target optimization engine, an antenna control unit and a power module are arranged in the handheld terminal body; and a visual display unit is arranged on the handheld computer. The laser radar scanning unit integrated in the handheld terminal body is used; a debugging personnel only needs to hold the device and walk in the station normally, so that the cloud data of the whole station can be collected in real time; the multi-target optimization engine is used to calculate the best deployment position and match the strongest signal of the node; according to the real-time signal strength, control instructions are sent to each position node; the antenna control unit is adjusted to ensure the debugging stability, so that the picture and data of the monitoring background are obtained.

The application discloses a zero-intervention blade tip timing signal extraction method based on multi-feature fusion, and belongs to the technical field of non-contact vibration testing of rotary machines. The application firstly constructs a candidate time window to intercept a pulse section based on a key phase signal; secondly, four types of arrival time features, i.e. a peak value moment, an energy barycenter moment, a cross-correlation peak value moment and a fitted zero-crossing point moment, are extracted in parallel in the candidate window; then, local signal-to-noise ratios and other signal quality indexes are calculated, feature fusion weights are adaptively determined, and a fused arrival time is obtained; finally, a median absolute deviation is used for outlier rejection, and a stable and reliable arrival time sequence is output in combination with adjacent blade time interval consistency verification. The application can significantly improve the arrival time extraction precision and robustness under the conditions of low signal-to-noise ratio, waveform distortion and working condition fluctuation, and is suitable for blade health monitoring and online vibration measurement in a closed casing environment of an aero-engine, a gas turbine and the like.

The application discloses a new energy power station grid connection method and system based on Beidou satellite timing and synchronous compensation, and the method comprises the following steps: receiving a Beidou satellite timing signal, generating a unified reference synchronous time, and calculating a reference synchronous phase angle according to the reference synchronous time; taking the reference synchronous phase angle as a control reference, driving a network type inverter to perform a grid connection operation; monitoring a Beidou timing signal integrity index in real time, and when detecting that the Beidou timing signal is abnormal or invalid, starting at least one level of synchronous compensation mechanism according to the abnormal or invalid duration and the system operation state, so as to maintain the phase continuity and frequency stability of the new energy power station grid connection operation.

This invention discloses a switching module for a high-reliability clock synchronization system. The invention includes: a signal processing module comprising a receiving unit and a processing unit; the input of the processing unit is connected to the output of the receiving unit, used for level conversion of the time signal received by the receiving unit and determining the next hop transmission path of the time signal; a PTP clock module, the input of which is connected to one output of the processing unit, used for receiving the level-converted time signal; and a switching chip, one input of which is communicatively connected to the output of the PTP clock module via a PHY chip, and the other input of which is connected to another output of the processing unit, used for PTP clock synchronization based on the level-converted time signal. Compared with existing technologies, this invention significantly reduces the risk of single-point failure and adapts to heterogeneous network environments.

This application discloses a method, apparatus, storage medium, and electronic device for evaluating the signal quality of fNIRS (functional optical brain imaging). The method includes: acquiring incident light intensity data and emitted light intensity data emitted by a light source; determining the coefficient of variation based on the incident light intensity data, and determining the signal-to-noise ratio based on the incident light intensity data and the emitted light intensity data; processing the incident light intensity data to obtain the number of peaks and heartbeat signal characteristics within a preset frequency range; and determining the quality evaluation result of the fNIRS signal based on the coefficient of variation, signal-to-noise ratio, number of peaks, and heartbeat signal characteristics. The evaluation method of this application can comprehensively measure the quality of near-infrared signals and can adapt to the physiological characteristics of different individuals to guide real-time signal quality detection and iterative hardware design.

The application provides a railway track traffic control management method and system, and relates to the technical field of railway track traffic control.The method comprises the following steps: establishing a time synchronization network based on a railway NTP protocol; using a colored Petri net model to perform vulnerability state reachability analysis on an NTP protocol authentication process based on a trusted certificate, and judging whether the current protocol has vulnerability; determining a first dynamic key and a second dynamic key according to key parameters of the NTP protocol authentication process; performing verification according to the first dynamic key and the second dynamic key; if the verification is passed, correcting a synchronization time signal; generating a synchronization timestamp for a target train; collecting real-time running parameters; determining a tracking interval time; and generating and issuing a control instruction.According to the application, the running state of the train can be controlled according to the communication security state and the tracking interval time, and the reliability of the real-time running parameters in time and the line utilization rate of the train are improved.

This invention discloses a radar-communication integrated antenna beam coordination optimization method and system based on big data, belonging to the field of radar communication technology. The method includes the following steps: acquiring electromagnetic energy distribution signals, target motion trajectory signals, and communication signal power timing signals during rapid changes in the target scene; expanding these three types of real-time signals under a unified time reference to establish a dynamic characteristic basis reflecting beam response lag; and continuously analyzing the time misalignment relationship between radar echo energy change signals and communication power timing signals based on the established dynamic characteristic basis. This invention restores the master-slave correspondence between radar transmission and echo sampling through time reference unification and timing coordination adjustment, reducing energy misalignment and detection distortion in dynamic scenarios. Furthermore, by allocating communication power in a segmented timing sequence, it achieves staggered release of radar and communication energy, reducing mutual interference and improving the overall sensing and transmission stability in complex electromagnetic environments.

The present application relates to nursing training auxiliary equipment technical field, specifically for a kind of transfer system anti-collision and angle safety monitoring control device and method, including the anti-collision detection module being arranged in the bottom of host computer, angle monitoring module, and motor driver control module motor is driven by PLC controller and electric hoist belt;Control method includes: S1, system initialization and parameter configuration;S2, multidimensional real-time signal acquisition;S3, safety boundary logic determination;S4, multi-information filtering and collaborative control;S5, closed loop cycle and data record;The present application can detect the angle and height of electric hoist belt in real time by setting anti-collision detection module and angle monitoring module, and motion intention and safety analysis are carried out through PLC controller, when user suddenly falls or electric hoist belt is lifted too high, can quickly respond, brake and stop, effectively improve the security of user in training.

A personnel positioning system and method for a large underground cavern complex based on a 5G communication network is disclosed. The system includes: a 5G communication network module transmitting the unique NR-PCI code and antenna deployment information of each base station to a GIS information system module; the GIS information system module providing an indoor geographic database containing the binding relationship between NR-PCI codes and geographic locations to a positioning engine module; the positioning engine module calculating the location of the user equipment based on the measurement data, NR-PCI codes, and GIS geographic information reported by the user equipment, and sending the positioning result to a data management server module; the data management server module storing the positioning result, personnel trajectory, and system configuration data, and supporting access by upper-layer applications; and the user equipment accessing the 5G network, collecting positioning measurements such as reference signal received power, signal arrival time, and signal arrival angle, and uploading the data to the positioning engine module to report its own location. This system addresses the problems of insufficient positioning accuracy, reliance on additional base stations, and poor adaptability in existing technologies.

A high-resolution spaceborne SAR imaging processing method for a ship target under complex sea conditions, which method relates to the technical field of radar imaging processing. In the method, by means of a dynamic adjustment strategy from a fine-tuning index, a cumulative energy ratio threshold value can be flexibly adjusted on the basis of real-time signal conditions; a phase compensation function is introduced as a basis function and a time window parameter is added, so as to better adapt to the instability of echoes from strong scattering points under complex sea conditions, thereby further improving the robustness of an algorithm; parameter estimation, residual updating and component extraction are performed in a frequency domain, thereby reducing search dimensions and increasing the operation speed; and a parameterized time-frequency distribution construction method is proposed, thereby effectively reducing the impact of cross terms and sidelobes. Upon verification, after processing is performed by using the method, the image quality of a ship under complex movement conditions is significantly improved.

The present application relates to the technical field of hydroelectric generating set operation monitoring, in particular to a hydroelectric generating set vibration signal abnormal early warning method based on iTransformer-Bootstrap, comprising the following steps: collecting vibration signals in the health operation stage of the hydroelectric generating set, and sequentially performing extreme value elimination, normalization and denoising preprocessing; training an iTransformer model, realizing vibration signal single-point prediction through the dimension reversal attention layer of the model, and simultaneously calculating the residual sequence of the predicted value and the true value; using a Bootstrap non-parametric resampling method to process the residual sequence, and constructing an adaptive prediction interval; comparing the preprocessed real-time collected vibration signals with the adaptive prediction interval, and if the real-time signals are out of the interval, determining that it is abnormal and issuing a warning. Experimental verification shows that the prediction interval coverage rate of the present application reaches 100%, the average interval width is significantly reduced, the fault signs can be accurately identified, the early warning reliability is effectively improved, and technical support is provided for the safe operation and preventive maintenance of the hydropower station.

The application discloses a full-band GIS ultrahigh frequency partial discharge pulse non-loss collection system and belongs to the technical field of intelligent sensing of primary equipment. The system comprises a signal collection and conditioning module, a double-channel high-speed ADC module and a high-speed data processing and storage module. The signal collection and conditioning module is used for connecting an ultrahigh frequency sensor signal and performing filtering and amplification preprocessing on the signal. The double-channel high-speed ADC module comprises two independent and synchronous collection channels and is used for synchronously collecting the preprocessed signal in a full band. The high-speed data processing and storage module is used for controlling the alternate collection of the double channels, real-time linear compensation, trigger timing control and real-time signal processing. The intelligent analysis and control module is used for performing real-time analysis and fault diagnosis on the collected data and dynamically adjusting system parameters. The application adopts a double high-speed channel collection single signal and realizes a cooperative working mechanism of mutual backup, effectively avoids pulse loss caused by system processing delay, and improves the accuracy of partial discharge analysis and the intelligent level of equipment state sensing.

This application relates to the technical field of fixed-point inspection, and more particularly to an inspection method and system for intelligent identity recognition in data centers. The method includes real-time monitoring of signal quality parameters of the identity recognition device in the inspection area; when the signal quality parameters are lower than a preset threshold, an automatic activation of a backup recognition mode is performed, wherein the backup recognition mode acquires the operator's biometric features through a visual acquisition device; based on the biometric features, a pre-stored identity database is matched to generate an identity verification result; if the identity verification is successful, missed registration events caused by signal quality issues are dynamically compensated, and a complete inspection log containing timestamps, operator identity, and device location information is generated. This application solves the problem of missed registrations caused by signal interference in densely populated equipment areas through real-time signal monitoring and automatic switching of the backup mode, improving the completeness of audit logs and eliminating compliance risks caused by missed registrations.

The application discloses a real-time signal early warning system based on geotechnical engineering slope monitoring and belongs to the technical field of geotechnical engineering safety monitoring. The system comprises four modules of multi-source data sensing, multi-field coupling mechanism analysis, critical state early warning discrimination and multi-modal early warning release. Four types of slope data are collected and classified as primary and secondary, and the data validity is ensured through standardized preprocessing. Based on the physical mechanism, effective rainfall, pore pressure response and microseismic damage function are constructed, and the internal disturbance index of the slope is generated by coupling with the geometric mean method. Based on the critical state line theory, the dynamic critical displacement rate function and the ratio type early warning index are constructed, and after being modified and smoothed, the discrete early warning grades are generated by combining the time accumulation mechanism. The grading early warning signals are output according to the early warning grades, the emergency equipment is linked, and closed-loop management is simultaneously performed. The application realizes the unbiased coupling and dynamic critical discrimination of multi-source data of the slope, and provides reliable technical support for the safety prevention and control of the slope engineering.

The application discloses a kind of mine drill multiple operating condition operating state data processing and evaluation method, belong to coal mine equipment condition monitoring and artificial intelligence technical field.Solve the technical problem of coupling of operating condition and state characteristics, data distribution confusion, signal baseline drift, weak model generalization ability and easy misjudgment of evaluation under multiple operating conditions of drill.The technical scheme is: data set is constructed by collecting multidimensional sensor signals;Temporal characteristics are extracted by inflation convolutional encoder, and are divided into operating condition and state latent variables according to physical priori, and operating condition residues are washed out by using gradient reversal layer;Replace operating condition latent variables with all-zero priori statistical prototype, and reconstruct homogeneous stationary signal by double-flow decoder;The model is optimized and trained by using multi-objective joint loss;After inputting the real-time signal homogenization, the final prediction entropy realizes high uncertainty early warning.The application can effectively purify state characteristics, eliminate baseline drift, realize cross-operating condition distribution alignment, and significantly improve the accuracy of drill condition monitoring.