1816results about "Acceleration measurement" patented technology

An all-terrain vehicle may include a frame and a plurality of ground-engaging members supporting the frame. The all-terrain vehicle may further include a powertrain assembly supported by the frame and shiftable transmission supported by the frame and operably coupled to the powertrain assembly. The all-terrain vehicle may also include a display, a back-up camera, and a controller supported by the frame. The controller may be configured to receive a signal from the shiftable transmission corresponding to the shiftable transmission being in a gear of the plurality of gears other than a reverse gear. Further, the controller may be configured to determine the all-terrain vehicle is moving backwards and send an activation signal to the back-up camera to display images of the back-up camera on the display.

The invention discloses a backfill soil foundation compaction quality on-site detection method and system. The method comprises the steps that instantaneous acceleration signals of a vibrating wheel in the soil compaction construction process are collected in real time through a three-axis acceleration sensor; the acceleration signal comprises a three-axis acceleration component; recording the number of construction times through construction equipment, collecting position information of a construction area by using a GPS (Global Positioning System), and synchronously binding the acceleration signal with the number of construction times and the position information through timestamps to form a data set corresponding to the position of the construction area; performing spectral analysis on the acceleration signal in the data set, and extracting a dominant frequency amplitude and a first harmonic amplitude to generate a filtered acceleration signal; the filtered acceleration signals are input into a training single-hidden-layer BP neural network, and the soil dry density is calculated in combination with the number of construction times; based on the ratio of the calculated soil dry density to the standard maximum dry density, the soil compactness in the construction area is determined in combination with the position information, and a construction area compactness distribution diagram is generated through the upper computer to optimize the construction strategy.

The invention relates to a shear-based acceleration and pressure composite sensor and an assembly method thereof, and belongs to the field of composite sensors. According to the technical scheme of the acceleration and pressure composite sensor based on the shear type structure, an acceleration detection module comprises a mass block of a regular polygon prism structure, and each side face of the mass block is provided with an acceleration sensitive ceramic piece; the pressure detection module comprises a force transmission column of a regular polygon prism structure, and each side face of the force transmission column is provided with a pressure sensitive ceramic piece, an electrode piece and an insulation block. According to the scheme, the sensitive elements of the acceleration sensor and the pressure sensor core are arranged in a polygonal mode to form a spatial three-dimensional structure, the effective area of the sensitive elements in unit volume is increased, the multiple sensitive elements act together to form superposition of pressure signals, the detection precision and sensitivity of the two are guaranteed, and the detection precision is improved. Therefore, the overall size of the composite sensor is greatly reduced on the premise that the original precision is maintained, and the composite sensor is miniaturized.

The invention provides a ground mechanical property parameter interpretation method based on impact penetration sounding, which comprises the following steps of: carrying an impact penetrometer by an unmanned aerial vehicle to carry out remote survey on a target ground, and carrying out data interpretation on dynamic response data acquired by the penetrometer by utilizing a radial basis function neural network model and a multi-target genetic algorithm; therefore, the mechanical characteristic parameters of the ground can be quickly and accurately obtained. The method is reasonable in conception, the ground mechanical property parameters of the soil can be rapidly and accurately interpreted, and the parameters can be used for equipment trafficability evaluation in a complex geological environment, so that the capability of coping with the complex geological environment is improved.

The invention discloses a pump set vibration monitoring method and system based on distributed sensing. The method comprises the steps that vibration collection signals and real-time working condition parameters of distributed sensing nodes are obtained, multi-node clock synchronization correction is executed, and synchronous vibration data frames are formed; time-frequency feature extraction is carried out on the multi-channel vibration data set, abnormal channels are identified through inter-channel consistency analysis, a local fault correlation frequency band is extracted, and a vibration feature vector is constructed; associating the vibration feature vector with a real-time working condition parameter to form a working condition-feature mapping table, identifying a feature mutation rotating speed point for the feature baseline, adaptively dividing a rotating speed interval to generate an adaptive working condition threshold value, and implementing out-of-limit detection to generate an abnormal trigger identifier; determining a traceability analysis window based on the abnormal trigger identifier, and executing multi-measuring-point coherence calculation and energy attenuation gradient analysis to construct an energy transfer link diagram; and finally, vibration source position positioning is performed to form fault source probability distribution, a fault mode label is matched, pump set vibration monitoring is completed, and quantitative positioning of a fault source is realized.

Embodiments disclosed herein relate to electronic devices, and more particularly to estimating a damage risk level for an electronic device. A method disclosed herein includes measuring motion parameters of the electronic device, on the electronic device being dropped on a surface. The method further includes classifying the surface into at least one type by processing the measured motion parameters using a classifier module. The method further includes estimating a damage risk score depicting the damage risk level for the electronic device based on the classified surface, the measured motion parameters of the electronic device, and a usage history of the electronic device.

Systems, devices, methods, and implementations related to contact detection are described herein. In one aspect, a system is provided. The system includes a first piezoelectric microelectromechanical systems (MEMS) transducer coupled to configured to generate a first analog signal when the first analog signal is transduced from vibrations propagating through the object. The system includes a second piezoelectric MEMS transducer having configured to generate a second analog signal transduced from acoustic vibrations at a location of the object, and classification circuitry coupled to the output of first piezoelectric MEMS transducer and the output of the second piezoelectric MEMS transducer, where the classification circuitry is configured to process data from the first analog signal and data from the second analog signal, and to categorize combinations of the first analog signal and the second analog signal received during one or more time frames.

The invention discloses a low-coupling biaxial silicon micro-resonant accelerometer. The low-coupling biaxial silicon micro-resonant accelerometer comprises an upper-layer micro-accelerometer structure and a lower-layer glass substrate with a signal lead, the micro-accelerometer structure is composed of two separated mass blocks, two pairs of identical tuning fork resonators and eight identical primary amplification levers. The two separated mass blocks are fixed on the same group of anchor points through U-shaped beams in different directions and are respectively used for measuring the acceleration of X / Y axes, and the whole structure is in a symmetrical figure. The four tuning fork resonators are distributed in a central symmetry mode and used for detecting the acceleration of the X axis and the acceleration of the Y axis. The X-axis and the Y-axis adopt the separated mass blocks, the sensitive mass blocks of the X-axis and the Y-axis are not connected, complete decoupling of the two detection axes is achieved, the lever structure can effectively amplify inertia force generated by the mass blocks, the sensitivity of the accelerometer is improved, and high-precision double-axis acceleration measurement is easy to achieve.

A finger-worn wearable ring device may include a ring-shaped housing, a printed circuit board, and a sensor module that includes one or more light-emitting components and one or more light-receiving components. The wearable ring device may further include a communication module configured to wirelessly communicate with an application executable on a user device.

The invention provides a seismic fracture fault model and co-seismic displacement field construction method and system, and relates to the technical field of seismic data processing, and the method comprises the steps: obtaining GNSS data, strong-motion seismograph data and accelerometer data of a preset region, and carrying out the fusion processing of the data, and obtaining the multi-source seismic data of the preset region; performing seismic waveform inversion on the multi-source seismic data to obtain related earth crust parameters of the preset area; calculating a Green function by using a hierarchical plane dislocation model according to the multi-source seismic data in combination with the related earth crust parameters to obtain a seismic fracture fault model of the preset region; performing inversion on the seismic fracture fault model through a gradient algorithm to obtain a seismic fracture surface of the preset area; and analyzing the seismic fracture surface to obtain a co-seismic displacement field. According to the method, multi-source data fusion is combined with an algorithm, the influence of noise interference and data errors is effectively reduced, and an earthquake occurrence mechanism and earth surface deformation characteristics are accurately revealed.

The invention provides a large-angle zero-gravity seat damage risk assessment method, and the method comprises the following steps: S1, collecting the pressure and comfort data of a dummy at different angles and under different supporting point configurations through an experiment, and building a dummy simulation model suitable for a large-angle zero-gravity seat; s2, on the basis of the dummy simulation model of the large-angle zero-gravity seat, vehicle collision and impact tests are added, acceleration and impact force data under different seat adjusting angles are obtained, a large-angle zero-gravity seat passenger injury prediction simulation model is established, and therefore a injury prediction value is obtained; and S3, calculating a damage risk score according to the damage predicted value.

The invention relates to the technical field of bridge health monitoring, and discloses a method for monitoring the bearing capacity state of a bridge latticed column structure. The method comprises the following steps: constructing an original monitoring field according to a sensor time sequence signal, and generating a state evolution sequence representing the overall dynamic evolution of the bridge latticed column through multi-dimensional space reconstruction, so as to capture the nonlinear characteristics of the structure behavior and provide a basis for anomaly detection. And positioning a potential abnormal region based on the deviation degree from the reference model, and extracting a time-varying characteristic spectrum of the potential abnormal region to drive the digital twin model to perform simulation so as to obtain a simulation response spectrum. The simulation response spectrum and the actual measurement state evolution sequence are subjected to space-time fusion, a mixed state field fusing real data and physical mechanism inference is generated, a monitoring blind area is made up, and the data reliability is improved. And by performing multi-scale decomposition on the mixed state field, the specific state mode of the bearing capacity of the bridge latticed column is identified, and more accurate and more complete evaluation of the bearing capacity abnormity is realized.

A smart ring includes a curved housing having a U-shape interior storing components including: a curved battery approximately conforming to the curved housing, a semi-flexible PCB approximately conforming to the curved housing and having mounted theron: a motion sensor for generating motion data from physical perturbations of the smart ring, a memory for storing executable instructions, a transceiver for sending data to a client computer, a temperature sensor, and a processor for receiving motion data and performing executable instructions in response thereto, and a potting material disposed in the interior, forming an interior wall of the smart ring, wherein the potting material encapsulates the components and is substantially transparent to visible light, infrared light, and / or ultraviolet light.

A finger-worn wearable ring device may include a ring-shaped housing, a printed circuit board, and a sensor module that includes one or more light-emitting components and one or more light-receiving components. The wearable ring device may further include a communication module configured to wirelessly communicate with an application executable on a user device.

The invention discloses a method for simultaneously monitoring particle sorting and bubble movement behaviors based on fluorescence tracing. Comprising the following steps: placing heavy particles in a two-dimensional fluidized bed; putting a fluorescent particle after the fluidized bed starts fluidization; shooting the two-dimensional fluidized bed by using an image acquisition module, and capturing images of fluorescent particles and bubbles; an MATLAB image acquisition tool box is utilized to process image areas of shot pictures frame by frame, motion attributes of fluorescent particles and motion attributes of bubbles are obtained, the processed pictures are superposed and recombined into a new picture, and interaction of coal and bubbles in the gas-solid separation fluidized bed is researched. According to the invention, the interaction of particles and bubbles in the gas-solid separation fluidized bed is researched by utilizing a fluorescent tracing technology, so that the fine particle separation effect in the gas-solid separation fluidized bed is improved.

The present invention features a micrometer-scale torsion balance device comprising a rigid mass and two or more nanoribbons attached to the rigid mass. The rigid mass may be suspended by the two or more nanoribbons. The two or more nanoribbons may be placed under tensile stress. A local acceleration value may be derived from a torsional stiffness of the two or more nanoribbons. In some embodiments, the rigid mass may comprise silicon. In some embodiments, the two or more nanoribbons may comprise silicon nitride. In some embodiments, the rigid mass may have a polygon shape, the polygon shape having four or more sides. A side of the four or more sides may be longer than all others.

Exemplary system, method and computer-accessible medium for selecting at least one location of (i) at least one receiver or transceiver or (ii) at least one transmitter or transceiver can be provided. For example, it is possible to facilitate a receipt, from the at least one transmitter or transceiver, of a plurality of signals by the receiver(s) or transceiver(s). Each of the signals has a multipath component. Then, it is possible to determine time of flight (ToF) information and angle of arrival (AoA) information of the multipath components present in the signals. Further, it is possible to determine one or more possible locations of (i) the receiver(s) or transceiver(s) or (ii) the transmitter(s) or transceiver(s) based on the ToF information, the AoA information, and a model of physical surroundings. The location(s) of (i) the receiver(s) or transceiver(s), or (ii) the transmitter(s) or transceiver(s) can be selected based on the one or more possible locations and an extended Kalman filter (“EKF”).

The invention discloses a collision sensing intelligent guardrail system and method based on Beidou positioning, and the method comprises the following steps: S1, collecting sensor data along a guardrail, and carrying out the preprocessing; s2, transmitting the preprocessed sensor data to an edge server, and forwarding the preprocessed sensor data to a cloud server through a cellular network; s3, constructing a gated convolutional network based on two channels, and inputting the state vector sequence into the gated convolutional network; s4, performing multi-layer nested coding and decoding operation on the collision feature vector, constructing a collision judgment function, and judging whether collision abnormity is triggered or not; s5, generating a collision early warning data packet when the collision level label is in an activated state; and S6, transmitting the collision alarm data packet to a road traffic command center for road maintenance personnel to quickly respond and deal with the collision alarm data packet. According to the invention, high-precision real-time perception and intelligent early warning of the collision state of the road guardrail are realized, and the automation level and response efficiency of traffic safety monitoring are obviously improved.

The invention discloses a handheld security check imaging method based on MEMS assistance, and aims to combine an MEMS sensor with an MIMO radar plate to form a handheld convenient security check imaging method with high precision and low cost according to the rapid and fine security check requirement of people in a security check place with dense people. Firstly, the radar board transmits a linear frequency modulation signal and receives an echo signal reflected by a target, and during the period, the MEMS sensor feeds back the motion track and position information of the handheld security check system in real time, and provides accurate attitude and position information. And secondly, position calibration is carried out on the track information of the MIMO radar antenna through the data of the MEMS sensor, and the zero drift of the accelerometer is compensated based on the wavelet packet change, so that the error caused by the system motion and the position change is reduced. And finally, residual phase errors are estimated and eliminated based on a particle swarm algorithm, non-contact three-dimensional imaging of the target is realized in combination with a wavenumber domain imaging algorithm on this basis, and hazardous article inspection is realized in combination with technologies such as deep learning and image recognition.

A finger-worn wearable ring device may include a ring-shaped housing, a printed circuit board, and a sensor module that includes one or more light-emitting components and one or more light-receiving components. The wearable ring device may further include a communication module configured to wirelessly communicate with an application executable on a user device.

A finger-worn wearable ring device may include a ring-shaped housing, a printed circuit board, and a sensor module that includes one or more light-emitting components and one or more light-receiving components. The wearable ring device may further include a communication module configured to wirelessly communicate with an application executable on a user device.

The invention discloses a trajectory prediction method and system for a bucket of a backhoe dredger, the next position of the bucket is predicted according to an observation model, a translational motion model and an external disturbance model, and the observation model, the translational motion model and the external disturbance model are introduced. The observation model, the translational motion model and the external disturbance model are integrally considered, and multiple interactions of the observation model, the translational motion model and the external disturbance model are realized, so that the prediction accuracy of the next position of the bucket is ensured. Further, the next position of the bucket is corrected, and a corresponding correction value is output; the translation transformation vector of the backhoe dredger is defined on the basis of real-time updating of the correction value, the position prediction value of the bucket is defined according to the translation transformation vector of the backhoe dredger and the bucket, the corresponding track is defined on the basis of the multiple position prediction values, association of the multiple position prediction values is achieved, and track prediction accuracy is guaranteed.

The invention discloses a testing method for sensing the running position and speed of a plunger, which comprises the following steps: synchronously acquiring pressure, temperature and acceleration data by sensing the plunger, and acquiring the data with time scales; filtering high-frequency signals from the collected acceleration data by using a low-pass filter; an acceleration curve after filtering is drawn, an optimal pulse peak point is selected for a double-pulse peak signal appearing at the hoop position through an algorithm, the number of the optimal pulse peaks is recorded as K, and the number of the hoop points is the same as the number of the optimal pulse peaks; according to the well depth structure, the average speed vn of the plunger passing through the nth oil pipe and the position depth Sn corresponding to the nth coupling point are calculated; according to the method, the influence of the double-pulse peak signal can be eliminated, and the operation position and speed of the plunger can be accurately calculated, measured and sensed.

The invention discloses an asymmetric coupling rigidity disturbance type MEMS modal localization accelerometer and a detection method. The accelerometer comprises an upper signal conversion layer and a lower glass substrate layer. The upper signal conversion layer comprises a sensitive mass block, a supporting structure and asymmetrical coupled resonator pairs which are symmetrically distributed. According to the asymmetric coupling resonator pair, a first type resonator and a second type resonator form a weak coupling system through electrostatic coupling, the first type resonator is fixed to a glass substrate layer through anchor points, the second type resonator is fixed to a sensitive mass block, and the first type resonator and the second type resonator meet the mass and rigidity asymmetric relation. When being subjected to the acceleration effect, the sensitive mass block generates micro displacement, changes the static coupling rigidity and triggers the modal localization effect, so that the amplitude ratio of the two resonators is changed, and acceleration measurement is realized by detecting the amplitude ratio change. By adopting the asymmetric structure, the sensitivity of the accelerometer is doubled compared with that of a symmetric structure, and meanwhile, the accelerometer has good linearity and anti-interference capability.

The invention relates to a method (100) for drift correction in a sensor system (200), comprising: Determining (101) values ​​of an operating parameter (201) of the sensor system (200); Executing (103) a correction model (203) taking into account the values ​​of the operating parameter (201) and determining a correction value (205) of a sensor value (227) of the sensor system (200), wherein the correction model (203) represents a model description of an operating state of the sensor system (200) as a function of the operating parameter (201) and describes a relation between values ​​of the operating parameter (201) and corrected sensor values ​​(207) of the sensor system (200); Performing (105) a correction of sensor values ​​(227) of the sensor system (200) taking into account the correction values ​​(205) of the correction model (203); and Providing (107) sensor values ​​(207) corrected with respect to the correction values ​​(205).

The invention relates to the technical field of geotechnical engineering monitoring, in particular to a soil erosion and particle migration prediction method and system based on acoustic emission monitoring, and the method comprises the following steps: obtaining a soil mass ratio parameter, and preparing a soil sample based on the soil mass ratio parameter to obtain a test soil sample; constructing a multi-field coupling test mechanism to perform a multi-field coupling soil body test on the test soil sample; establishing a soil sample data acquisition device to obtain soil sample monitoring data in the multi-field coupling soil body test process; obtaining acoustic emission characteristic parameters of the test soil body according to the soil sample monitoring data, and establishing a multivariate nonlinear regression model; and constructing a soil body prediction model to realize prediction of soil body erosion and particle migration. Through fusion of multi-field coupling monitoring and machine learning, limitation of a traditional empirical model is broken through, high-precision dynamic prediction of soil erosion and particle migration is realized, a scientific basis is provided for stability evaluation of roadbed engineering, and prediction reliability and engineering applicability are remarkably improved.

The invention belongs to the technical field of sensors, and particularly relates to a TSV-based MEMS capacitive accelerometer wafer-level packaging structure and packaging method. A gold-silicon bonding and TSV (Through Silicon Via) combined technology is adopted, and a gold layer is used as a bonding medium and a sensor capacitor polar plate, so that the problem of integration of a polar plate structure and signal lead-out in an MEMS sensor is solved, the design that an independent electrode layer or an additional polar plate is needed in traditional packaging is avoided, and the packaging complexity is reduced. Meanwhile, the gold layer has low resistance and good conductivity, compared with a traditional electrode material, signals can be better transmitted, and the electrical performance of the MEMS sensor is improved. After the TSV technology is combined, short-path signal extraction can be realized in the wafer, signal attenuation and interference are reduced, and signal integrity and precision are improved.

The invention belongs to the technical field of inertial sensors, and particularly discloses an MEMS accelerometer with low parasitic capacitance and a preparation method. According to the invention, the hollow area is formed at the position directly facing the back of the pickup electrode, so that the directly facing area between the pickup electrode and the upper cover silicon substrate is reduced, and the parasitic capacitance is reduced. In addition, a grounding polar plate is arranged between the pickup electrodes, so that the relative movement between the excitation electrode and the silicon substrate of the upper cover plate is shielded, and the influence of stray capacitance between the excitation electrode and the silicon substrate is further reduced. The hollow area is formed on the back of the pickup electrode of the MEMS accelerometer through the thin film supporting structure in combination with plasma dry etching, and the preparation method is simple in process, suitable for various capacitive MEMS accelerometers or gravimeters and good in compatibility and practicability.

A finger-worn wearable ring device may include a ring-shaped housing, a printed circuit board, and a sensor module that includes one or more light-emitting components and one or more light-receiving components. The wearable ring device may further include a communication module configured to wirelessly communicate with an application executable on a user device.