145 results about "Signal edge" patented technology

The invention discloses an automatic identification and expansion communication method based on an RS485 interface, and relates to the technical field of industrial automation communication. The problems that an existing RS485 interface is complex in configuration, poor in protocol compatibility and high in data transmission delay are solved. According to the scheme, the terminal matched resistance and the bias current are adjusted in real time by dynamically measuring the bus equivalent distributed capacitance value, and signal attenuation caused by the capacitance effect is inhibited; a silicon controlled rectifier trigger type charge discharge mechanism is adopted to force bus residual charge to return to zero quickly, and an idle state is accurately judged in combination with a hysteresis comparator; dynamically compensating signal edge distortion and calibrating a sampling window time sequence based on a pre-emphasis filtering and Kalman filtering algorithm; multi-node stable communication is realized through capacitance value driven conflict detection threshold adaptive adjustment and a Poisson back-off model; according to the invention, the real-time performance, the anti-interference capability and the multi-node expansion reliability of RS485 communication in a complex industrial scene are obviously improved, and the debugging and maintenance cost of the system is reduced at the same time.

The invention relates to the technical field of high-speed rail platform safety monitoring, and discloses a high-speed rail platform area intrusion detection and early warning alarm system, which comprises an acoustic and vibration sensor network deployed in a platform area and used for collecting environment signals in real time, the edge calculation unit extracts signal features and compares the signal features with a dynamically maintained environmental rhythm feature baseline to generate a detuning event mark, and the detuning mode analysis device identifies an abnormal mode through space-time correlation and triggers an alarm. According to the method, early perception of subtle anomalies is realized by constructing a multi-modal environment rhythm baseline, active perturbation injection and differential response analysis technologies are combined, the recognition capability of a silent target is remarkably improved, meanwhile, the monitoring continuity under an extreme working condition is ensured by using an elastic baseline adaptive mechanism, and the detection accuracy is improved. And a closed-loop security and protection system from passive sensing to active discrimination is formed.

The invention relates to the technical field of stoma nursing devices, and discloses an AI visual stoma leakage early warning system, which comprises a plurality of passive piezoelectric film sensors embedded in a stoma chassis and used for capturing acoustic signals generated by adhesion interface structure instability; the edge calculation unit periodically collects an electric signal sequence and calculates an information entropy value, and through comparison with a self-adaptive resting entropy baseline, the structural instability risk is judged and early warning is generated when the entropy value continuously and abnormally rises. The risk orientation is accurately identified in combination with a multi-sensor cooperative positioning technology, body movement interference is avoided by using a dynamic compensation mechanism, and the early warning accuracy and clinical practicability are improved.

The invention discloses a primary and secondary fusion pole-mounted circuit breaker state monitoring system and method, and relates to the technical field of power system automation. The system comprises a native signal acquisition module which is used for multiplexing an inherent electrical loop of a circuit breaker and acquiring a current signal of an opening and closing coil and a capacitive reactance change signal of a parasitic capacitor between a high-voltage electrode and a grounding end; and the edge analysis module is used for processing the signal acquired by the original signal acquisition module, including generating a mechanical health degree through feature extraction and state mapping, calculating an insulation aging index based on capacitive reactance change, and dynamically correcting a monitoring reference in combination with a digital twin model and a filtering algorithm. Non-auxiliary element monitoring is realized by multiplexing the inherent electrical loop of the circuit breaker, so that the service life of the monitoring system and the service life of primary equipment are completely synchronous, and elements do not need to be replaced in the whole life cycle; errors introduced by additional sensors are avoided by using the original electrical signals, and the mechanical fault recognition and insulation state evaluation precision is remarkably improved.

Provided are a data transmission circuit system and a data reception circuit system, which use an edge of a pulse signal. The data transmission circuit system modulates a digital signal by using time levels determined by time differences between rising edges (or falling edges) of a clock pulse signal and rising edges (or falling edges) of a data pulse signal. The data reception circuit system demodulates a digital signal by using time levels determined by time differences between rising edges (or falling edges) of a recovered clock pulse signal and rising edges (or falling edges) of a data pulse signal.

The invention relates to the technical field of rail traffic monitoring, and discloses an urban rail vehicle driving analysis system based on digital twinning, which is characterized in that vehicle vibration and traction motor current signals are collected in real time through a vehicle-mounted sensing unit, and an edge feature extraction unit calculates energy ratio features of a predefined fault frequency band; the data transmission unit transmits the characteristic data and the working condition information to a digital twin platform, a digital fault tree model is arranged in the platform, and a cross-physical domain fault conduction path is analyzed and recognized through multi-source data coupling. Through combination of frequency band energy ratio characteristics and fault tree logical reasoning, electromechanical coupling fault risks which cannot be found by traditional isolated monitoring are effectively captured, meanwhile, a diagnosis threshold value is dynamically adjusted according to the wheel-rail adhesion state, and the diagnosis reliability under the complex working condition is improved.

The invention discloses a switch cabinet anti-explosion multi-parameter rapid identification and alarm method, and relates to the technical field of power equipment safety, and the method comprises the steps: obtaining a known switch cabinet historical fault record, analyzing the attribute preference and occurrence rule of different faults, constructing a multi-modal time sequence fault diagnosis model, and generating a fault knowledge base; operating parameters are monitored in real time, a field programmable gate array is used for solidifying primary judgment logic, and if the current change rate and the arc light signal intensity exceed preset threshold values at the microsecond level at the same time, a primary fault trigger signal is generated; the edge intelligent calculation unit automatically extracts the original data of the multi-source heterogeneous sensor in a set time window before and after the triggering moment, and substitutes the original data into the multi-modal time sequence fault diagnosis model to obtain a diagnosis result and a risk level of a known switch cabinet fault; and in combination with the multi-modal time sequence fault diagnosis model, executing a layered response mechanism. The beneficial effect of the invention is that the fault loss is reduced.

The invention discloses a brain-computer interface interaction control device and method based on multi-mode brain signal fusion. The device comprises a perception acquisition layer, an edge processing layer, a fusion decoding layer, a control application layer and a closed-loop optimization cloud platform. The sensing acquisition layer synchronously acquires multi-modal brain signals; the edge processing layer adopts a condition alignment time sequence diffusion model to carry out signal enhancement and completion; the fusion decoding layer realizes multi-modal feature fusion and intention decoding through a lightweight graph neural network; the control application layer provides adaptive control mapping and multi-mode feedback; and the closed-loop optimization cloud platform realizes continuous performance optimization through federated learning and incremental learning. According to the method, the problems of single signal, insufficient precision and poor practicability of a traditional brain-computer interface are effectively solved, the decoding precision, the real-time performance and the individuation degree of the system are remarkably improved, and the method can be widely applied to the fields of intelligent home control, medical rehabilitation training, industrial control and the like.

The invention discloses a high-voltage positive and negative pulse detection circuit, which relates to the technical field of signal conditioning, and is characterized in that a voltage division circuit is responsible for attenuating input pulse signals, a switching diode is responsible for rectification and inputting positive and negative pulse signals into corresponding conditioning circuits respectively, and a charging circuit is responsible for maintaining pulse width characteristics of the signals; and the steepness of the signal edge is ensured by the comparator, and FPGA identification can be realized. Uncertain high-voltage pulse signals can be processed, and application scenes are diversified. The edge characteristic, pulse width and pulse direction of the pulse signal can be identified, and the signal processing capability is prominent.

The invention discloses a building cluster cloud-edge collaborative optimization control method and device and an application architecture. The architecture comprises an edge device, a radio frequency communication LoRa module and a cloud platform. The edge device and the cloud platform realize cloud edge two-way communication through the LoRa module; the edge device comprises a sensing layer, an edge calculation core and a control layer and is used for collecting real-time building data, executing a local model predictive control algorithm MPC based on a building thermodynamics RC model and generating an optimal control instruction to drive air conditioning equipment; the cloud platform comprises a network service interface module, an optimization algorithm module and a data storage system and is used for operating a global coordination algorithm based on an alternating direction multiplier method (ADMM) and generating differentiated price signals; the edge device uploads data such as power requirements to the cloud platform, the cloud platform issues differential excitation signals to the edge device, and the edge device and the cloud platform perform collaborative iteration. According to the invention, distributed optimization control of the building cluster is realized through cloud-side cooperation, and the value of the building cluster as a power grid flexible resource is significantly improved.

This invention belongs to the field of wind power equipment condition monitoring and fault diagnosis technology, specifically relating to an intelligent diagnostic device and method for blade icing based on acoustic-vibration feature fusion. It includes: a multimodal sensing unit for acquiring vibration response signals and aeroacoustic signals; a signal conditioning and synchronous acquisition unit connected to the multimodal sensing unit for conditioning and synchronous analog-to-digital conversion of the vibration response signals and aeroacoustic signals to obtain synchronized digital vibration and digital sound signals; and an edge computing and diagnostic unit connected to the signal conditioning and synchronous acquisition unit. This invention synchronously acquires and deeply fuses vibration signals reflecting the blade's structural state with specific frequency band sound signals reflecting the aerodynamic state of the blade surface, constructing an intelligent diagnostic system based on acoustic-vibration coherence analysis and machine learning models. This achieves high-precision, robust online diagnosis and early warning of blade icing conditions.

The invention relates to the technical field of semiconductor processing equipment, and discloses a plasma processing device and a plasma processing method. The plasma processing device comprises a processing chamber which comprises a lower electrode used for bearing a substrate and an upper electrode arranged opposite to the lower electrode; the edge source radio frequency power source is used for applying a first radio frequency signal to the edge area of the upper electrode and / or the lower electrode, and the first radio frequency signal is used for generating plasma in the edge area between the upper electrode and the lower electrode; the upper electrode bias radio frequency power source is used for applying a second radio frequency signal to the upper electrode; the edge bias radio frequency power source is used for applying a third radio frequency signal to the edge area of the lower electrode; wherein the second radio frequency signal and the third radio frequency signal are synchronized by a reverse pulse signal.

The invention relates to the technical field of manufacturing data processing, and discloses a production business data processing system for a discrete manufacturing workshop, which comprises an asynchronous data acquisition module for acquiring an asynchronous event pulse sequence of a discrete execution node; the mapping transformation module establishes an addressing mapping relation between an event source and a memory logic bit plane and generates an original differential bitmap; the bitmap filtering module is used for hedging paired logic flipping signals by utilizing an exclusive-OR logic self-reversal principle and filtering jitter interference at the edges of the signals so as to generate a net value difference bit plane; the state synchronization processing module performs in-situ upset updating on the state global bitmap through address offset addressing according to the bit identifier, and through a bitmap differential synchronization mechanism, asynchronous state updating without transaction lock constraint is achieved, calculation blocking generated by high-frequency pulse impact is relieved, and the real-time performance and stability of system data throughput are enhanced.

The invention discloses a high-precision digital double-mixing phase discriminator, and belongs to the technical field of time transfer. Comprising a sampling amplification module, the output end of the sampling amplification module is connected with a signal processing module, and the output end of the signal processing module is connected with a result output module; the sampling and amplifying module is used for receiving two paths of input clock signals fCLKA and fCLKB, and sampling and amplifying the fCLKA and fCLKB by cascading two paths of multi-stage D triggers, so that the phase difference of the two paths of input clock signals is reserved and amplified, and the probability of metastable state occurrence is reduced; the signal processing module is used for carrying out jitter optimization processing on the two paths of sampled and amplified signals and extracting stable signal edges; and the result output module is used for measuring the amplified phase difference according to the two paths of signals subjected to jitter optimization, and obtaining the original phase difference through scaling down. Digital amplification is adopted, analog devices are not needed, noise introduction and delay uncertainty are avoided, and therefore the linearity and reliability of measurement are improved.

Various embodiments of the present disclosure relate to a method for managing the startup of a phase-locked loop and a corresponding integrated circuit. The operation of the phase-locked loop includes a startup phase, during which a reference signal with a 50% duty cycle is applied to a phase comparator of the loop. A first frequency divider of the output signal of the loop's voltage-controlled oscillator is reset at each first-type signal edge of the reference signal. The phase comparator receives the reference signal and a feedback signal from the first frequency divider and generates a control pulse at each second-type signal edge of the reference signal, which causes the control voltage of the oscillator to increase.

This invention belongs to the field of power equipment monitoring technology, specifically relating to a non-intrusive monitoring system and method for switchgear fault indicators. The system includes: a non-contact optical sensing unit, installed on the outside of the switchgear panel via a magnetic structure, for acquiring the brightness timing signal of the fault indicator light; an electrical parameter acquisition unit, for acquiring the electrical parameter timing signal of the circuit associated with the fault indicator light; and an edge computing unit, deploying a fault diagnosis neural network model with a hybrid neural network architecture, for performing feature fusion processing on the two time-aligned signals, outputting a status recognition result to distinguish between correct alarms caused by line faults and false alarms caused by abnormalities in the indicator light itself. This invention achieves non-intrusive retrofitting of fault indicators in old switchgear, converting local light signals into remotely transmittable digital quantities without dismantling or modifying the cabinet or electrical circuits, and effectively identifying true and false alarms through multi-source signal fusion analysis.

The invention discloses a silo material opening discharging device and an anti-blocking method based on dredging monitoring. The discharging device comprises a discharging barrel, a dredging executing mechanism, an annular sensor matrix and a control center. The anti-blocking method comprises the following steps: acquiring a pressure signal of a flowing material; the edge computing gateway decouples and preprocesses the pressure signal, and outputs a standardized time sequence data sequence; the AI analysis unit is used for extracting spatial features, time domain features and frequency domain features of the multi-dimensional monitoring data, inputting an attention mechanism for fusion, and inputting a fusion feature vector into a blockage prediction model for state reasoning; controlling a hierarchical grooming action according to a reasoning result; according to the anti-blocking method based on monitoring and dredging of the discharging device, sensing, calculation, AI reasoning and intelligent execution are integrated, an intelligent control closed loop is formed, manual experience and intermittent operation can be replaced, and continuous, autonomous and intelligent anti-blocking guarantee in the discharging process is achieved.

The invention provides a physiological signal monitoring method and device and electronic equipment. The method can be applied to the electronic equipment and comprises the steps that a processor outputs a first output signal to an ambient light sensor; based on different signal edges in the first output signal, the processor periodically triggers the first light source to emit a first light source signal and periodically triggers the second light source to emit a second light source signal, and the triggering moments of the first light source signal and the second light source signal are different; the ambient light sensor collects and processes the first light source signal and the second light source signal so as to send the processed first light source signal and the processed second light source signal to the processor; and the processor monitors the physiological signal of the user according to the processed first light source signal and the processed second light source signal. In this way, the problem that at present, most non-wearable electronic devices do not have the function of monitoring physiological signals such as blood oxygen and heart rate can be solved.

The invention relates to a multi-phase power supply system with self-current balancing capability. An apparatus includes a power converter controller. A power converter controller receives the first input. The amplitude of the first input is derived from a combined output current supplied to the load by the plurality of power converters. The power converter controller also receives a second input indicative of an amplitude of a first output current supplied from a first power converter of the plurality of power converters to the load. The combined output current includes a first output current supplied from the first power converter to the load. The power converter controller adjusts a leading edge and / or a trailing edge of the first pulse width modulation control signal based on a comparison of the second input and the first input. Additional examples to support signal edge control are discussed herein.

The invention provides a railway perimeter intrusion detection system and method based on multi-modal fusion. Comprising a front-end multi-mode detection module used for acquiring a vibration optical fiber detection signal, a video image signal and a radar detection signal; the edge computing terminal comprises a visual analysis unit which is used for detecting a long-distance small target and a short-distance target by using a detection head formed by an additional detection branch and a high-level detection branch arranged on a shallow feature map of the target detection network; the equipment state monitoring unit is used for generating equipment state data; the multi-modal fusion unit is used for generating perimeter intrusion event data and equipment abnormal event data; and the communication unit is connected with the multi-mode fusion unit and is used for receiving the perimeter intrusion event data and the equipment abnormal event data and packaging the data to generate an alarm message. According to the method and the device, the remote small target detection precision can be improved, the multi-modal fusion robustness under the abnormal condition of the equipment is improved, and the accuracy of determining and reporting the perimeter intrusion and the equipment abnormality is improved.

The invention discloses a vehicle-mounted module GCK signal edge synchronization EMC noise suppression method, which comprises the following steps: S1, GCK drive timing optimization: modifying a timing GCK driven by a liquid crystal screen GCK from min1.6 us to min0us, so that a rising edge and a falling edge of a GCK signal are synchronized to offset energy generated by the signal during rising and falling, and the noise of the vehicle-mounted module in a low-frequency band of 0.52 Mhz-1. 73Mhz in an RE experiment of an EMC experiment is reduced; and S2, comprehensive performance verification: after GCK driving timing optimization is implemented, comprehensive performance and reliability experimental verification is performed on the module, including testing multiple aspects of electrical performance, optical performance and stability of the module, and no obvious change influence is generated on each performance and reliability of the module while an RE experiment is converted from FAIL to PASS. According to the vehicle-mounted module, related standard requirements are met, the long-term EMC problem of the vehicle-mounted module in the frequency band is solved, the electromagnetic compatibility of the product is improved, it is ensured that the vehicle-mounted module can stably operate in a complex electromagnetic environment, and interference to other electronic equipment is reduced.

The invention discloses a baud rate self-adaptive switching system of low-power-consumption slave equipment, and relates to the technical field of embedded communication, the baud rate self-adaptive switching system comprises an initialization module, a communication monitoring module, a baud rate switching module, a low-power-consumption management module and a wake-up module, when effective communication signals are monitored, the transmission state of the communication signals is continuously tracked, and when the effective communication signals are monitored, the communication signals are switched to the low-power-consumption slave equipment, and the low-power-consumption slave equipment is switched to the low-power-consumption slave equipment. Recording baud rate information of successful communication, and resetting a communication timeout timer; the communication timeout timer is used for receiving a communication timeout timer, calling a baud rate sequence and sequentially switching the current baud rate of the slave equipment when the timing of the communication timeout timer reaches a first preset threshold value, and triggering the slave equipment to enter a deep sleep mode when the timing of the communication timeout timer reaches a second preset threshold value, and the awakening module is used for awakening the slave equipment when the slave equipment is in the deep sleep mode. And detecting the signal edge change of the communication interface in real time, and triggering the slave equipment to wake up from the deep sleep mode when detecting that a preset signal edge feature is met. The method and the device have the effect of improving the baud rate switching efficiency of the slave equipment.

The invention relates to the field of civil engineering, and discloses a deep foundation pit monitoring system, method and device and a storage medium, and the system comprises a data sensing module which collects the displacement of an enclosing structure, the internal force of a supporting structure and the underground water level parameter through a sensor group disposed in a foundation pit, and transmits an original monitoring signal through a wireless communication link; the edge processing module is used for receiving the original monitoring signal through a wireless gateway, carrying out digital conversion and critical safety judgment on the original monitoring signal and generating preprocessed data; the cloud analysis module is used for integrating the multi-source preprocessed data to carry out space-time fusion and risk probability prediction; and an early warning feedback module. According to the method, the LSTM-CNN network weight is updated through incremental training, the risk feature weight distribution is optimized through historical events, the three-level alarm threshold value is dynamically adjusted through the real-time working condition, the early warning strategy online evolution capability is constructed, the false alarm rate is reduced, and the working condition adaptability is improved.

In an embodiment a method for processing a detector signal by a signal chain includes detecting, by a detector, a plurality of detection events, increasing an output voltage of an amplifier after each detection event, and resetting the output voltage of the amplifier when the output voltage exceeds a threshold due to a threshold event, wherein the threshold is smaller than a maximum voltage value determined by an overdrive value of an input voltage of a signal processor to which the output voltage of the amplifier is connected, wherein resetting is determined by processing of the threshold event only irrespective of other detection events, and wherein a reset is triggered by a signal edge of a reset pulse.

A control device (1) for controlling an RMS value of an electrical load current (5) at a time-varying load (2), characterized in that the control device (1) is configured to provide a voltage pulse train (4) having a predetermined duty cycle (10) at the time-varying load (2) and in at least one pulse phase (8) of the voltage pulse train (4): - to detect a respective sample value (16) of the electrical load current at the time-varying load (2), wherein the control device (1) is configured to detect the sample value (16) of the electrical load current in a last tenth of the pulse phase (8) and / or during a falling signal edge of a pulse of the voltage pulse train (4), - to determine an actual RMS value (11) of the electrical load current assigned for the sample value (16) of the electrical load current by means of a dependency (17) stored in the control device (1).- to determine a difference value (25) between the actual RMS value (11) of the electrical load current and a target RMS value (6) of the electrical load current, - to determine an adapted duty cycle (26) of the voltage pulse train from the difference value (25) of the electrical load current according to a predetermined procedure, and - to provide an adapted voltage pulse train (27), having the adapted duty cycle (26), to the time-varying load (2).

The present application relates to the technical field of display, and provides a touch panel, a display apparatus, and a display driving method. The touch panel comprises: a display panel and a touch sensor layer arranged on the light exit side of the display panel. The display panel comprises a gate driving circuit and a plurality of control signal lines. The control signal lines are electrically connected to the gate driving circuit. A first control signal line is used for receiving a first control signal sent by a timing control circuit at a first moment, and a second control signal line is used for receiving a second control signal sent by the timing control circuit with a delay relative to the first moment. The first control signal and the second control signal are gate driving control signals of the same type. The moment at which the control signal lines receive first signal edges is earlier than the moment at which the control signal lines receive second signal edges. Each first signal edge of the second control signal is aligned with one second signal edge of the first control signal. The noise of the touch panel can be reduced, thereby improving the touch effect of the touch panel.

This invention discloses a brain-computer interface (BCI) interactive control device and method based on multimodal brain signal fusion. The device includes a perception acquisition layer, an edge processing layer, a fusion decoding layer, a control application layer, and a closed-loop optimization cloud platform. The perception acquisition layer synchronously acquires multimodal brain signals; the edge processing layer uses a conditionally aligned temporal diffusion model for signal enhancement and completion; the fusion decoding layer uses a lightweight graph neural network to achieve multimodal feature fusion and intent decoding; the control application layer provides adaptive control mapping and multimodal feedback; and the closed-loop optimization cloud platform achieves continuous performance optimization through federated learning and incremental learning. This invention effectively solves the problems of single signal, insufficient accuracy, and poor practicality in traditional BCIs, significantly improving the system's decoding accuracy, real-time performance, and personalization capabilities. It can be widely applied in fields such as smart home control, medical rehabilitation training, and industrial control.

The invention discloses a mine panoramic monitoring system based on array type hundred-million-level pixel image intelligent perception. The mine panoramic monitoring system comprises an array image acquisition module which acquires multiple paths of original video signals of a mine scene through a plurality of hundred-million-level pixel cameras which are spatially arranged; the edge preprocessing module receives multiple paths of original video signals and generates preprocessed video signals and preliminary target signals; the panoramic splicing module receives the preprocessed video signals and fuses multiple paths of video streams through a real-time image splicing algorithm to generate unified panoramic video signals; the intelligent sensing module receives the panoramic video signal and the preliminary target signal and generates an intelligent analysis result signal; and the early warning and interaction module receives an intelligent analysis result signal so as to realize alarm output and user operation feedback. According to the mine panoramic monitoring system based on array type hundred million-level pixel image intelligent perception, the problem that view, precision and real-time intelligent analysis cannot be considered in mine panoramic monitoring can be solved.

The invention relates to a side suppression circuit, a signal processing apparatus, and an image processing apparatus. The side suppression circuit comprises a suppression unit sequence for carrying out side suppression processing on a plurality of input signals which are sequentially adjacent in the one-dimensional direction or a suppression unit array for carrying out side suppression processing on a plurality of input signals which are arranged in a two-dimensional dot matrix mode, and three suppression units which are sequentially arranged in the same direction. The grid electrodes of the two PMOS transistors in the middle suppression unit are respectively coupled with the output ends of the suppression units on the two sides, the grid electrodes of the two PMOS transistors respectively belonging to the suppression units on the two sides are coupled with the output end of the middle suppression unit, the side suppression effect of edge enhancement can be achieved, a hardware circuit is adopted in the side suppression circuit, and the side suppression circuit is simple in structure and low in cost. And compared with the situation of realizing side suppression based on an algorithm, the dependence on a processor can be reduced, and the computing power consumption can be reduced. The signal processing device and the image processing device comprise the side suppression circuit, and signal edge enhancement can be achieved.