221 results about "Digital sensors" patented technology

A physiological patient monitor can include a front end conditioner that can receive analog sensor signal from a sensor responsive to a person's physiology. The patient monitor can further include an analog-to-digital converter that can convert analog sensor signal to a digital sensor information. The patient monitor can determine one or more patient specific physiological parameters. The patient monitor can further determine a physiological condition of a patient based on processing multiple physiological parameters. The patient monitor can generate a user interface that can included a visual representation of the patient's physiological condition.

The invention provides a test risk digital twinning early warning method based on multi-domain cooperative monitoring, and belongs to the technical field of virtual-real fusion test and digital twinning, and the method comprises the steps: firstly, building a fine finite element simulation model which comprises a digital tool system, a digital sensor and a test piece and considers nonlinearity; secondly, performing nonlinear finite element simulation analysis, and constructing a multi-level mechanical response field inversion reduced-order model; thirdly, completing the construction of a complete sensor data set through a data filling algorithm, and carrying out the failure judgment of the first hierarchical structure based on the complete sensor data set; and finally, carrying out future loading level sensor data prediction and completing failure judgment of a second hierarchical structure. Carrying out full-field mechanical response inversion and online real-time correction; and performing response inversion of the region of interest to realize failure judgment of the third hierarchical structure. According to the invention, real-time dynamic monitoring and early warning of the structure test risk can be realized, the real-time performance, the robustness and the accuracy are high, and a powerful guarantee is provided for the safety and the reliability of the structure test.

The invention discloses a ternary internet-of-things battery management system, particularly relates to the technical field of lithium battery management, realizes lithium battery thermal safety closed-loop management through multi-sensor fusion, and comprises the following steps: deploying a digital sensor array to obtain time-space associated data; constructing a spatio-temporal feature vector including fusion of a local temperature gradient, a neighborhood temperature gradient and a stress coupling ratio; a density clustering algorithm is adopted to dynamically divide spontaneous heating, radiant heat and stress coupling clusters, and cluster boundaries are updated in real time; calculating a dual thermal coupling coefficient based on a clustering result, and eliminating the interference of temperature reading through a dual temperature compensation formula; a three-level alarm mechanism of a radiant heat proportion, a stress coupling degree and a compensation error is established, a side gateway is linked to realize parameter adaptive optimization, and the thermal runaway early warning precision and the structural failure detection rate are improved; strain monitoring resource optimization is realized through physically-driven key point screening and dynamic graph neural network prediction.

Embedded sensor structures and stretchable embedded sensor films including a plurality of embedded sensor packages are described. An embedded sensor structure may include a sensor package including an integrated circuit (IC) die and sensor die bonded to a front side of the IC die, with the sensor die including a diaphragm that is deflectable toward a cavity. A planarization layer laterally surrounds the sensor package, and metal routing is formed on a top side of the sensor die and spanning over the planarization layer. Other aspects are also described and claimed.

The invention relates to an automatic calibration method for an inertial MEMS sensor. The sensor module includes a pattern generator configured to generate a variable frequency self-test signal. The sensor module includes an inertial sensor including a self-test electrode that receives a frequency sweep self-test signal. The inertial sensor generates an analog sensor signal based on the self-test signal. The sensor module includes: an analog-to-digital converter that generates a digital sensor signal based on an analog sensor signal; and a demodulator including a first input to receive the digital sensor signal, a second input to receive the self-test signal, and an output to output a demodulated signal. The sensor module includes a first low pass filter coupled to an output of the demodulator and configured to generate a baseband signal. The sensor module includes a calibration circuit configured to identify different MEMS characteristics, such as resonant frequency, Q factor, or sensitivity, based on the baseband signal.

The present invention provides a pipeline potential safety hazard intelligent identification system and method integrating power frequencies, pressures and temperatures and belongs to the technical field of intelligent monitoring. A monitoring system includes temperature sensors, pressure sensors, an Internet of Things (IoT) electricity meter, a PLC, an IoT DTU and a remote server. The present invention has the advantages of reading and analyzing pipeline operating state parameters in real time via digital sensors, and realizing remote real-time monitoring by uploading data via the IoT DTU; acquiring a leakage transient temperature by performing energy analysis on fluid at a leakage location of a pipeline, deducing a variation of pressure gradients from a variation of temperature gradients, performing two-parameter linkage leakage analysis, and positioning a leakage point with higher accuracy; and realizing the control logic through the PLC, and being easy to operate and high in applicability. The present invention further has the advantages of forming a pressure-temperature dataset and a power frequency dataset, analyzing an operating state of a heating pipeline in real time, integrally setting a leakage threshold value in conjunction with a variation of device power frequencies and reducing false alarm frequencies.

The invention relates to a flexible deployment type global full-duration partial discharge detection system and method, the system comprises a signal acquisition module, a power frequency synchronization module, a power supply communication module and an analysis and diagnosis module, the power frequency synchronization module obtains the real-time power frequency of a power grid by using a UDP power frequency synchronization device, and sends the real-time power frequency to a digital sensor; the signal processing module digitizes the ultrahigh frequency signal on site, converts the ultrahigh frequency signal into continuous real-time monitoring data and transmits the continuous real-time monitoring data to the power supply communication module; the power supply communication module is used for providing a stable power supply capable of continuously working for a long time for the digital sensor and transmitting continuous real-time monitoring data to the analysis and diagnosis module; and the analysis and diagnosis module is used for receiving the continuous real-time monitoring data and carrying out partial discharge detection. Compared with the prior art, the method has the advantages that a large amount of on-site deployment working hours are saved, the requirements of rapid deployment, full-station coverage and reliable discovery of accidental intermittent signals can be met, and synchronous long-time continuous monitoring of partial discharge of the GIS equipment in the full station is realized.

A sensor module includes a pattern generator configured to generate a variable frequency self-test signal. The sensor module includes an inertial sensor including a self-test electrode configured to receive the frequency sweep self-test signal. The inertial sensor is configured to generate an analog sensor signal based on the self-test signal. The sensor module includes an analog to digital converter configured to generate a digital sensor signal based on the analog sensor signal and a demodulator including a first input configured to receive the digital sensor signal, a second input configured to receive the self-test signal, and an output configured to output a demodulated signal. The sensor module includes a first low pass filter coupled to the output of the demodulator and configured to generate a baseband signal. The sensor module includes a calibration circuit configured to identify different MEMS characteristics, like resonance frequency, Q-factor, or sensitivity based on the baseband signal.

The invention provides an intelligent blowout preventer, a wellhead device and a blowout prevention method. The intelligent blowout preventer is applied to the same-well injection-production process of a horizontal well containing an oil well controller. The device comprises a shell with a cross-shaped channel, the cross-shaped channel is composed of horizontal channels and a vertical channel for a polish rod to penetrate through, and the device further comprises two flashboards which are symmetrically installed in the horizontal channels on the two sides relative to the vertical channel. The two hydraulic cylinders are mounted on the shell and are used for pushing and pulling to enable the two gate plates to face each other to seal the polish rod or to deviate from each other to be separated from the polish rod; a locking structure is mounted on a cylinder barrel of the hydraulic cylinder; a digital sensor used for receiving instructions of an oil well controller is arranged on the locking structure, and the digital sensor drives the hydraulic cylinder to open or cut off the vertical channel. When high-pressure water in a casing pipe flows into a low-pressure oil pipe, the digital sensor can cut off a channel where a polish rod is located in time, and a horizontal well is stopped immediately; during normal production, the intelligent blowout preventer can ensure that a channel where the polish rod is located is kept unblocked.

Improved surface acoustic wave structures (or elements) that can be used to realize any of a wide variety of dispersive or non-dispersive transversal SAW filters that are distinct from prior known means for producing such filters are disclosed. The devices and structures may include stepped acoustic wave delay modification elements that can be used to implement transversal filter impulse response functions in a manner analogous to the use of interdigital transducers. The structures disclosed are of particular usefulness to implement SAW devices at high frequencies where normal photolithographic resolution would prove limiting. Aspects and embodiments of the present invention would be useful to produce SAW devices for use in a wide variety of applications, including as components in cell phones, in radar and other communications and electronic systems, and as wired or wireless sensors or sensor-tags.

The invention provides a die head coating control device and method, and relates to the technical field of perovskite coating machine coating, and the die head coating control device is characterized in that lifting devices are arranged in two gantry seats; the lifting devices of the two gantry seats are connected with the first connecting plate; the first connecting plate is perpendicular to the platform deck plane; the second connecting plate comprises a first vertical plate and a second vertical plate which are vertical to each other; the first connecting plate is fixedly connected with the first vertical plate; a die head beam is fixed between the second vertical plates corresponding to the two gantry seats; a die head is fixed below the die head beam; the die head is perpendicular to the glass substrate; the gantry seat is used for driving the die head to move along one side of the plane of the carrying table to the other side opposite to the side, so that the die head completes coating of a glass substrate; the front of the advancing direction of the die head serves as the front side; a spectrum confocal sensor is fixed on the front side of the die head beam; a contact type digital sensor is arranged on the rear side of the carrying table. The time for detecting the coating uniformity can be greatly saved, and the coating convenience and operability are improved.

The present invention relates to the technical field of rice yield prediction. Disclosed is a rice yield prediction method based on unmanned aerial vehicle remote sensing image processing. In the method, vegetation indices (VIs), spectral indices, and color indices of rice at different growth stages are collected by an unmanned aerial vehicle, and the rice yield is predicted by using single-date VIs and multi-date VIs based on multispectral (MS) and digital (RGB) images. Both MS and RGB digital sensors on an unmanned aerial vehicle are reliable platforms for rice growth and yield prediction, and it is feasible to estimate the rice yield on the basis of dual-sensor data and temporal accumulation across different growth stages, so that full-growth-stage monitoring of rice can be performed, the influence of spectral indices and color indices at different growth stages on the rice yield can be evaluated, and the pre-harvest grain yield can be predicted in a timely and accurate manner, thereby facilitating rice production management and grain trade.

The invention discloses a carbon dioxide emission monitoring system and a control method thereof, belongs to the technical field of digital monitoring control, and aims to solve the problems of localization, large abnormal recognition deviation and regulation and control lag of traditional monitoring. The method comprises the following steps of: acquiring production parameters and carbon flow characteristic variables of each production link through a multi-dimensional sensing network constructed by a digital sensor, and constructing a time-space association data set according to a time-space association mapping system of the production parameters and the carbon flow characteristic variables; constructing a carbon flow association rule base based on historical data mining association rules and identification common association rules, embedding a multi-level carbon flow model to construct a hierarchical digital twinborn model, and correcting deviation in combination with current data; the model is utilized to periodically predict carbon flow, acquire carbon flow four-element distribution data to judge emission abnormity, construct a reference variable sequence to identify abnormal production links and production equipment, generate target production parameters and execute feedback, and complete-flow carbon flow accurate control is realized.

The invention discloses an all-digital PVT sensor based on a ring oscillator, and relates to the field of PVT sensors, the all-digital PVT sensor comprises a process sensing circuit, a voltage sensing circuit and a temperature sensing circuit, the process sensing circuit comprises a process detection ring oscillator, the voltage sensing circuit comprises a voltage detection ring oscillator, and the temperature sensing circuit comprises a temperature detection ring oscillator. The temperature sensing circuit comprises a temperature sensitive ring oscillator; under the control of an enable signal, the process detection ring oscillator, the voltage detection ring oscillator and the temperature-sensitive ring oscillator start oscillation, and the process corner, the temperature and the power supply voltage of the detected chip are determined based on the oscillation frequencies of the process detection ring oscillator, the voltage detection ring oscillator and the temperature-sensitive ring oscillator. The PVT sensor is completely realized based on a digital circuit, an additional analog module does not need to be introduced, the area overhead is greatly reduced, and the PVT sensor has remarkable area advantage and structural simplicity while the high-precision detection capability is maintained.

According to the automatic driving simulation test method, device, equipment and medium provided by the invention, a vehicle digital sensor module can provide physically accurate sensor sensing capability including noise and error modeling, so that simulation is closer to an actual driving scene, and the sensing performance of an automatic driving system in various complex environments can be tested; according to the invention, a closed loop of the digital sensor, the automatic driving, the vehicle dynamics model, the environment simulation module and the digital sensor is formed, the whole process test of the automatic driving system from sensing, decision making to control is realized, the system performance can be continuously iteratively optimized, and the stability, safety and reliability of the system under different working conditions are comprehensively verified.

The invention provides a sensor array data transmission method which is applied to an FPGA, the FPGA is provided with a PDM digital interface and a DVP digital interface, multichannel PDM signal streams output by a digital sensor array are received through the PDM digital interface, the multichannel PDM signal streams are converted into multichannel PCM data streams in a synchronous digital modulation mode, and the multichannel PCM data streams are transmitted to the FPGA through the DVP digital interface. Dynamic fragmentation compression processing is carried out on the multi-channel PCM data flow through an equal probability sampling method; the method comprises the following steps: receiving a video data stream output by an image sensor through a DVP digital interface, and compressing the video data stream through a H264-like video data compression method; the multi-channel PCM data stream is subjected to combined coding, the coded PCM data stream is interspersed in the compressed video data stream through an interpolation method, and the coded PCM data stream and the compressed video data stream keep time synchronization; and packaging and uploading the interspersed and mixed data flow to a cloud server through a gigabit network communication protocol.

The invention discloses a digital silicon photomultiplier tube, comprising: a pixel array module, a logic circuit module, a counter / time digital converter, a counting rate comparison and judgment module and an enable control module; the digital SiPM sensor of the invention can compare and judge the current counting rate with the rated threshold counting rate, and feed back the comparison result to the enable control module, and the enable control module outputs an enable for adjusting the number n of effective pixels receiving photons to the pixel array module, thereby changing the probability of the effective pixel array in the pixel array module receiving photons to adjust the current counting rate of the counter / time digital converter, so that the current counting rate is within a suitable range, avoiding the occurrence of pile-up distortion, improving the accuracy of distance measurement, and reducing the power consumption required under the same detection effect.

Systems and methods for metering consumption of a resource include: a sensor comprising a display and configured to: sense a consumption of the resource; display said consumption on the display; and convert said consumption into digital sensor data; an imaging device configured to capture images of the display of the sensor; and a communications interface configured to transmit the digital sensor data and data describing one or more of the images of the display to a remote server.

In one embodiment, a method for authenticating a user with an electronic device is disclosed. The method incudes receiving digital sensor data from a motion sensor over a signal acquisition time period; deleting a beginning portion of the digital sensor data prior to the signal acquisition time period; suppressing signal components in the data associated with voluntary movement of the user; signal processing the suppressed digital sensor data to extract signal features representing neuro muscular tone of the user; tabulating the extracted signal features over periods of time into a feature vector table; executing a predictive model with the feature vector table; generating a numerical degree of matching level based on the feature vector table and the user parameter set; and making a determination to either authorize the user or not based on the numerical degree of matching level. The predictive model is trained by a user parameter set.

A high lift system monitoring arrangement (24) includes: a sensor (32), a monitoring unit (34) connected to the sensor (32), wherein the monitoring unit (34) includes: an acquisition module (46), that acquires an analog sensed information (AI) from the sensor (32), a processing module (48) having a first processing circuitry (48A) and a second processing circuitry (48B), different from the first circuitry, wherein the first processing circuitry (48A) processes the analog sensed information (AI) into a first digital sensor data (DD1), the second processing circuitry (48B) processes the analog sensed information (AI) into a second digital sensor data (DD2).

A device for protecting an integrated circuit from a disturbance attack is provided. The device comprises a sensing unit (30) configured to detect a disturbance attack, the sensing unit comprising a group of digital sensors, the group of digital sensors comprising at least two sensors, the sensors being arranged in parallel. Each digital sensor provides a digitized bit output having a binary value in response to input data, the sensing unit being configured to transmit at least one binary vector comprising a multi-bit value, the multi-bit value comprising at least two bit outputs provided by the group of digital sensors. The sensing device (3) further comprises an analysis unit (31), the analysis unit being configured to receive at least one binary vector provided by the sensing unit (30), the analysis unit being configured to detect a disturbance attack based on the at least one binary vector.

The function extension device includes: a first connection end portion connected to the digital sensor; a second connection end that is connected to a higher-level device that communicates with the digital sensor; an unvarnished transmission part for transmitting a signal between the first connection end part and the second connection end part; and an additional function unit that provides an additional function for executing a predetermined process with respect to the digital sensor, the upper-level device, or the signal.

The present invention is related to an IoT-enabled automatic fan speed regulation system that adjusts fan speed according to ambient temperature using a digital sensor (DHT11 / DHT22) and a microcontroller (ESP8266 / ESP32). The system employs PWM-based control for energy efficiency and integrates with IoT platforms (Blynk, ThingSpeak, Firebase) for real-time monitoring and remote override. This solution enhances comfort, reduces manual intervention, and conserves energy, making it suitable for homes, offices, institutions, and industries.

The processing board (2) for a sensor (1) includes: - an interface (5) comprising at least a first set (5a) of terminals configured to be connected to a set of terminals (10a) of an analog sensor board (3a) that provides an analog signal, and at least a second set (5b) of terminals configured to be connected to a set (10b) of terminals of a digital sensor board (3b) that provides a first digital signal, and - a processing module (6) connected to the second set (5b) of terminals and configured to be connected to the first set (5a) of terminals.

The invention provides a digital sensor for measuring air pressure parameters. The digital sensor comprises a waterproof sealing gasket, an electric connector, a shell, a wire, a digital circuit board, a hexagonal copper column, an analog circuit board, an adapter, a sensitive element and a connecting nozzle. An anti-aliasing design and a temperature compensation design are adopted on the circuit. The pressure sensor has the advantages of supporting low-voltage power supply, being miniaturized, high in precision, high in reliability, high in environmental adaptability and the like, and lays a technical foundation for subsequent signal acquisition and analysis and localization technical research of the pressure sensor.

The application provides a data acquisition method, system and storage medium. The data acquisition method comprises: in response to compensation sensing initialization, sampling a reference channel to obtain a compensation reference value; calculating a difference between half of a maximum sampling range voltage and the compensation reference value to obtain a sampling voltage compensation value; connecting an N+1 channel and / or an N-1 channel to a maximum range voltage, where N is a positive integer; and sampling an N channel based on the sampling voltage compensation value to obtain analog-to-digital conversion sampling data of the N channel. The application uses a compensation sensing mode to reduce the error between the voltage value read by a register and the actual voltage value, uses adjacent channels connected to a maximum range voltage, reduces the crosstalk influence of an analog-to-digital sensor, and minimizes the influence of adjacent enabled channels.

A compact inspection assembly comprising digital sensors and / or laser measurement systems to measure and validate attributes of pipe and associated threaded connections. A custom designed end-effector sensor assembly is selectively attached to a robotic arm having software and control systems. An automated sensor assembly, selectively positioned relative to a pipe section, measures data regarding the pipe and associated threaded connections. The measured and recorded data can be inspected for defects and / or compared to predetermined standards (such as, for example, original equipment manufacturer and / or end user specifications or requirements) to verify pipe / connection compliance with desired standards.

This invention discloses a wireless distributed networking test system and method for climate environment testing, relating to the field of wireless distributed networking test technology. The system includes at least one environmental chamber for placing the product under test (DUT), which is located within a pre-constructed distributed wireless local area network (WLAN). The WLAN includes a wireless base station and at least one wireless node, with one wireless node installed in each environmental chamber. At least one type of digital sensor is also installed in each environmental chamber. Each type of digital sensor is used to collect at least one type of parameter to be measured within the environmental chamber. The digital sensors transmit the collected parameters to the wireless node within their respective environmental chamber via a digital bus. The wireless node transmits the parameters to be measured within its environmental chamber to a test control terminal via the wireless base station. This invention solves the problem of low testing efficiency caused by complex cable laying in existing systems by constructing a distributed wireless local area network to transmit test data during the testing process.

The invention relates to phase-coherent read-out of sensor nodes (3) of a magnetic resonance imaging system (1) with a digital serial communication network (2). According to the invention, the network (2) comprises multiple sensor nodes (3) for detecting a radio frequency signal from a patient who is under examination by the magnetic resonance imaging system (1), and a host node (4) which is connected to the sensor nodes (3) via a network link (5) for merging and processing digital sensor data received from the sensor nodes (3), wherein the host node (4) comprises a receiver (6) connected to the network link (5) for receiving data over the network link (5), and a transmitter (7) connected to the network link (5) for transmitting data over the network link (5), the sensor nodes (3) each comprise an analog-to-digital converter (8) for converting the detected radio frequency signal to the digital sensor data, a receiver (9) connected to the network link (5) for receiving data over the network link (5), a transmitter (10) connected to the network link (5) for transmitting data over the network link (5), and a clock and data recovery unit (11) with a clock device which is configured for miming on a preset free-running frequency, the frequency of the data transmission over the network link (5) is set to a fixed frequency relative to the preset free-running frequency of the clock devices, and the clock and data recovery units (11) are configured for generating a recovered clock signal for controlling the analog-to-digital converter (8) of their sensor node by regulating the frequency of the clock device of their sensor node (3) to lock to the frequency of the data transmission over the network link (5). In this way, the possibility of phase coherent sensory data acquisition with a magnetic resonance imaging system (1) is provided in a robust and cost-efficient way.

Measuring device (1) for process measurement technology, comprising: - a number n of sensors (2_1 to 2_n), wherein each sensor (2_i) of the number n of sensors (2_1 to 2_n) is configured to provide associated sensor data (x i ) to generate a total of n sensor data (x1, ..., x n ) is generated using the number n of sensors (2_1 to 2_n), - a learning unit, wherein the learning unit is trained to calculate values ​​of a number d of parameters of a hypothesis function based on training data, and - a measuring instrument diagnostic unit (4) designed to measure a number m of diagnostic values ​​(ŷ1, ..., ŷ m ) depending on the number n of sensor data (x1, ..., x n ) based on the hypothesis function and the calculated values ​​of the number d of parameters of the hypothesis function.