32 results about "Stress estimation" patented technology

The invention discloses an aero-engine part fatigue crack propagation identification method based on machine vision. The method comprises the following steps: S1, obtaining an image block sequence; s2, inputting each image block into a pseudo stress estimation network to generate an image block pseudo stress diagram; s3, inputting the image block and the image block pseudo-stress diagram into an image feature decoupling coding module, and outputting a fusion feature vector; s4, inputting the fusion feature vector into an improved fox algorithm, and generating a crack path guide map and a direction vector field; s5, inputting the image block pseudo-stress diagram, the crack path guide diagram, the direction vector field and the fusion feature vector into a crack mask generation module, and outputting an image block crack mask; s6, splicing the image block crack masks according to the positions of the image blocks in the surface image to generate a complete crack structure diagram; and S7, outputting a crack propagation result based on the complete crack structure chart. According to the method, machine vision and an evolutionary path optimization method are fused, and accurate recognition of aero-engine crack propagation is achieved.

The invention discloses a tire pressure monitoring device and method based on a passive RFID temperature tag. The tire pressure monitoring device comprises the passive RFID temperature tag, a reader-writer module and a data processing unit. And the passive RFID temperature measurement tag is fixed on the inner wall of the tire, receives the radio frequency energy sent by the reader-writer module, and collects the internal temperature of the tire in real time. The reader-writer module is fixed near a hub of a vehicle, performs polling communication with the passive RFID temperature measurement tag through a multi-band radio frequency technology, and transmits tire internal temperature data returned by the passive RFID temperature measurement tag to the data processing unit. And the data processing unit indirectly derives the tire pressure by utilizing a thermodynamic equation and combining parameters such as tire structure change, vehicle speed and load, so that high-precision and low-power-consumption tire pressure monitoring is realized. According to the method, the tire structure does not need to be damaged, non-contact pressure estimation and dynamic modeling can be achieved, and the method has the advantages of being simple in structure, high in reliability, wide in applicability and the like.

To provide an abnormality diagnostic system of an object structure capable of accurately and stably performing an abnormality diagnosis of the object structure.SOLUTION: An abnormality diagnostic system performs eigenvalue analysis with respect to a shape model obtained by modeling a structure of an object structure 200, and constructs a degradation model based on a result of the eigenvalue analysis. The system includes: an estimation section 420 for estimating, based on the degradation model and an acceleration measurement value 11, an acceleration estimation value and a stress estimation value at at least one evaluation object point being a part of the object structure 200 and also estimating an estimation value of a natural vibration number and an estimation value of an attenuation ratio which are a vibration parameter of the object structure 200; and an abnormality determination section 430 for determining a normal / abnormal state of the object structure 200 by machine learning based on the acceleration estimation value, the stress estimation value, the estimation value of the natural vibration number, and the estimation value of the attenuation ratio.SELECTED DRAWING: Figure 1

A stress estimating device 100 of the present invention includes: a first calculating unit 121 that calculates a first stress value by inputting, to a first stress calculation model, first data based on biometric data obtained by measurement from a target person; and a second calculating unit 122 that calculates a second stress value by inputting, to a second stress calculation model, the first stress value, and second data based on stress-related subjective data acquired from the target person, in which the second stress calculation model is generated in advance by learning using the first stress value and the second data about a predetermined person acquired in the past.

The invention provides a seamless track blow-off locking miniaturized high-precision measurement method and device, and the method comprises the steps: collecting the rail seam opening degree and steel rail temperature data in real time, and constructing a state input vector; calculating the strain and equivalent stress of the steel rail based on the state input vector, and introducing a structural position sensitive correction term to improve the accuracy of stress estimation; the locking state in the rail seam diffusion process is identified through the lightweight gated loop network model by utilizing the time sequence data of the strain and the corrected stress, and a state classification label is output; and according to the state classification label and the corrected stress value, generating a locking operation suggestion, and providing a visual prompt for construction personnel through terminal equipment. According to the method, a stress estimation method is combined with a time sequence analysis algorithm, so that state judgment is converted from a static index to a dynamic trend, and the locking decision-making efficiency and reliability in the construction process are remarkably improved.

The stress estimating device 1X mainly includes a division means 15X, a first feature value calculation means 16X, a second feature value calculation means 17X, and a stress estimation means 18X. The division means 15X is configured to divide observation data representing chronological states of a subject. The first feature value calculation means 16X is configured to calculate first feature values, which are feature values of divided observation data, based on a learned feature extraction model. The second feature value calculation means 17X is configured to calculate a second feature value based on a plurality of the first feature values. The stress estimation means 18X is configured to estimate a stress of the subject based on the second feature value.

The invention relates to the technical field of coal mine safety, and provides a multi-factor impact risk evaluation method and system for instability of a super-thick surface soil-coal pillar structure. According to the evaluation method, when a target stope is of an extremely thick surface soil structure, stress factor impact evaluation is carried out on the target stope according to superposed stress borne by the target stope, and micro-seismic factor impact evaluation is carried out on the target stope based on micro-seismic monitoring of the target stope; and then coupling a stress factor impact evaluation result and a micro-seismic factor impact evaluation result of the target stope to realize impact risk evaluation of the target stope. Therefore, the overall impact risk of the stope is comprehensively evaluated by combining the stress factor impact risk evaluation result and the micro-seismic factor impact risk evaluation result, the impact risk identification of the island working face under the condition of extremely thick surface soil is perfected, and the deficiency of an island working face bearing stress estimation method is made up; and rock burst accidents caused by blind mining of the island working face under the condition of extremely thick surface soil are avoided.

The present invention discloses a method for predicting formation pressure based on seismic data, and relates to the field of petroleum geological exploration and seismic data inversion technology. The method comprises the following steps: S1, determining a prediction formula for formation pressure; S2, preprocessing of seismic velocity data bodies; S3, calculation and normalization of various parameter data bodies; S4, optimization and adjustment of core parameters; S5, verification and improvement of prediction results. The present invention provides a method for predicting formation pressure based on seismic data. The method can be used efficiently over a large area with only seismic velocity data, is suitable for estimating the pressure of dense layers, is simple and efficient, can obtain the trend of pressure changes, and is conducive to the exploration and development of oil and gas resources.

The stress estimation device acquires the awakening degree of the subject and calculates the feature amount of the acquired awakening degree. The feature amount of the awakening degree is, for example, a ratio at which the temporal change of the awakening degree is within a predetermined range, information defining a histogram showing the distribution of the temporal change of the awakening degree, and the like. Then, the stress estimation device estimates the stress from the calculated feature amount using the stress model.

The invention discloses a zinc oxide arrester resistor disc temperature rise and stress estimation method considering a temperature coefficient and a skin effect, and belongs to the technical field of zinc oxide arrester resistor disc temperature rise and stress estimation. In order to solve the defect of large simulation result difference under different initial conditions, the influence of the temperature coefficient and the skin effect on temperature rise and stress is considered, the temperature difference of all positions of the lightning arrester resistor disc under the lightning impulse can be reflected, stress estimation is achieved, and compared with a traditional model only calculating the overall temperature rise, the method has the advantage that the calculation efficiency is improved. According to the invention, the local temperature difference and the stress breaking probability of the resistor disc can be obtained, the aging state evaluation precision of the lightning arrester is improved, and the reliability of the lightning arrester and the operation of a power grid is improved.

An ophthalmic surgical system (100) includes an ophthalmic microscope (102) including a first camera (204a) and a second camera (204b). A controller (214) coupled to the first camera and the second camera receives a current pair of images including a current representations of a retina (300) of a patient; obtains a current three- dimensional representation of the retina from the current pair of images; determines deformation of the retina by evaluating the current three-dimensional representation relative to a reference representation of the retina; determines (414) stress on the retina according to the deformation; and outputs (418) guidance according to the stress. Stress may be determined using FEM and may use velocity and acceleration of the deformation. Guidance may include a graphical representation of the stress or a vector along which force should be exerted. Deformation may be detected (412) using a mesh (312) projected (406) onto the retina.

To realize more precise control of an actuator device based on a static frictional force taking into account an equilibrium of force.SOLUTION: A control device for an actuator device that operates using a motor, comprises: a disturbance observer; disturbance torque estimating means for estimating a disturbance torque for the actuator device by using an intermediate parameter of the disturbance observer and a Kalman filter; and reaction force estimation means for estimating a reaction force acting on the actuator device based on a model in which the disturbance torque estimated by the disturbance torque estimation means, the motor torque, the static friction, and the reaction force are in balance.SELECTED DRAWING: Figure 2

A learning device 1X mainly includes a classifying means 14X and a learning means 17X. The classification means 14X classifies observed feature values of subjects so that an index representing a correlation between the observed feature values and a stress value becomes higher than the correlation before the classification, wherein the stress value is a correct answer corresponding to the observed feature values. The learning means 17X trains, based on the observed feature values and the stress value which is the correct answer, stress estimation models for respective classes divided at least by the classification, wherein the stress estimation models each estimates a relation between the observed feature values and the stress value.

An ophthalmic surgical system includes an ophthalmic microscope including a first camera and a second camera. A controller coupled to the first camera and the second camera receives a current pair of images including a current representations of a retina of a patient; obtains a current three-dimensional representation of the retina from the current pair of images; determines deformation of the retina by evaluating the current three-dimensional representation relative to a reference representation of the retina; determines stress on the retina according to the deformation; and outputs guidance according to the stress. Stress may be determined using FEM and may use velocity and acceleration of the deformation. Guidance may include a graphical representation of the stress or a vector along which force should be exerted. Deformation may be detected using a mesh projected onto the retina.

The present invention provides a method for estimating the stress of a mechanical structure and a method for monitoring the mechanical structure, which can grasp the state of the evaluation object position of the mechanical structure during the operation of the mechanical structure without stopping the operation of the mechanical structure. The stress estimation method of the mechanical structure according to the embodiment includes a calculation process for calculating the relationship between the stress generated at the evaluation object position during the excitation of the mechanical structure and the physical quantity including sound pressure or vibration generated at a detection position different from the evaluation object position. In addition, the stress estimation method of the mechanical structure includes a detection process for detecting the physical quantity generated at the detection position during the operation of the mechanical structure. In addition, the stress estimation method of the mechanical structure includes an estimation process for estimating the stress generated at the evaluation object position during the operation of the mechanical structure based on the relationship calculated in the calculation process and the physical quantity detected in the detection process.

The invention discloses an interventional operation continuum catheter tail end stress estimation method and a force feedback system, and aims to solve the problem that catheter tail end force feedback lags behind or is low in accuracy in the interventional operation process. The continuum catheter tail end stress estimation method comprises the following steps: applying a beam theory to elastic mechanical modeling of a catheter, and performing force / moment balance analysis on a model under the condition of considering tail end external force so as to establish an elastic mechanical model of the catheter; a plurality of data sets of external force, internal force and joint configuration are obtained through an elastic mechanical model to form a training set and a test set of a BP neural network model, the BP neural network model is trained to obtain constant parameters of a nonlinear mapping function with the internal force and instantaneous joint configuration as variables and the external force as a dependent variable, and estimation of the external force borne by the catheter is achieved. Simulation test results show that the continuum catheter tail end stress estimation method has good reliability and feasibility.

The application discloses a wheel cylinder pressure estimation method of a vehicle body electronic stability control system and relates to the technical field of wheel cylinder pressure, which comprises the following steps: S1, a wheel cylinder pressure determination method, S2, wheel cylinder pressure estimation, S3, wheel cylinder pressure control and S4, PID control simulation verification. The application analyzes the wheel cylinder pressure reduction process: in order to avoid frequent opening and closing of the electromagnetic valve, a step-by-step pressure reduction method of pressure reduction-pressure maintenance-pressure reduction is adopted, when the wheel cylinder pressure and the target pressure difference is greater than the set threshold 1MPA, the electromagnetic valve is fully opened, the wheel cylinder starts to reduce pressure, until the wheel cylinder pressure and the target pressure difference is less than -1MPA, the electromagnetic valve is fully closed, the wheel cylinder enters the pressure maintenance state, when the wheel cylinder pressure and the target pressure difference reaches 1MPA again, the pressure reduction is continued, so that the purpose of following pressure reduction is achieved, and the pressure control is realized.

The present invention discloses a method for identifying fatigue crack growth in aircraft engine components based on machine vision, comprising the following steps: S1, acquiring a sequence of image blocks; S2, inputting each image block into a pseudo-stress estimation network to generate an image block pseudo-stress map; S3, inputting the image block and the image block pseudo-stress map into an image feature decoupling encoding module to output a fused feature vector; S4, inputting the fused feature vector into an improved Fox algorithm to generate a crack path guidance map and a direction vector field; S5, inputting the image block pseudo-stress map, the crack path guidance map, the direction vector field, and the fused feature vector into a crack mask generation module to output an image block crack mask; S6, splicing the image block crack masks according to the positions of the image blocks in the surface image to generate a complete crack structure map; S7, outputting crack growth results based on the complete crack structure map. The present invention integrates machine vision with an evolutionary path optimization method to achieve accurate identification of aircraft engine crack growth.

The invention discloses a method for calculating crack stress in a self-balancing repair process and a terminal. A first trend of crack expansion depth and width is obtained according to the insertion depth of an expansion assembly; obtaining a second trend according to the clamping assembly bearing data and the first trend; and the pressure borne by the crack part is calculated by combining the first trend, the second trend and pressure data applied by the expansion assembly. According to the method, the double dimensions of the expansion assembly insertion behavior and the clamping assembly stress feedback are introduced, more accurate modeling and stress estimation of the crack expansion behavior are achieved, a scientific basis is provided for follow-up glue injection amount control and anchoring point arrangement, and the repairing efficiency and the quality stability are improved.

An estimation system (100) comprises: a position detection unit for detecting the position of a user; a work estimation unit for estimating candidates for a work performed by the user on the basis of the position of the user; a displayed work setting unit for displaying the work candidates estimated by the work estimation unit on a screen of a wearable device used by the user; a vital data acquisition unit that identifies the work selected by the input operation by the user among the work candidates displayed on the screen of the wearable device as the work performed by the user, and acquires information of the identified work and vital data of the user in association with each other; and a stress estimation unit that estimates the user's stress on the basis of the vital data of the user, and stores a stress estimation result and the work selected by the input operation by the user in the storage unit in association with each other.

This learning device 1X mainly has a classification means 14X and a learning means 17X. The classification means 14X classifies an observed feature quantity pertaining to a subject such that an index representing a correlation between the observed feature quantity and a correct stress value corresponding to the observed feature quantity becomes higher than before the classification. The learning means 17X trains a stress estimation model for estimating the relationship between observed feature quantity and stress value, for at least each class categorized by classification, on the basis of the observed feature quantity and the correct stress value.

The stress estimation device acquires the awakening degree of the subject and calculates the feature amount of the acquired awakening degree. The feature amount of the awakening degree is, for example, a ratio at which the temporal change of the awakening degree is within a predetermined range, information defining a histogram showing the distribution of the temporal change of the awakening degree, and the like. Then, the stress estimation device estimates the stress from the calculated feature amount using the stress model.

To easily identify a work performed by a user and associate the work with a stress estimation result.SOLUTION: An estimation system comprises: a position detection section for detecting a position of a user; a work estimation section for estimating candidates for a work performed by the user on the basis of the position of the user; a displayed work setting section for displaying the work candidates estimated by the work estimation section on a screen of a wearable device used by the user; a vital data acquisition section that identifies the work selected by input operation by the user among the work candidates displayed on the screen of the wearable device as the work performed by the user, and acquires information of the identified work and vital data of the user in association with each other; and a stress estimation section that estimates stress of the user on the basis of the vital data of the user, and stores a stress estimation result and the work selected by the input operation by the user in a storage section in association with each other.SELECTED DRAWING: Figure 1

To provide an elastic wave velocity evaluation method, an elastic wave velocity distribution evaluation method, a stress estimation method and a stress distribution estimation method that reduce time and labor of installing an apparatus for a concrete structure.SOLUTION: An elastic wave velocity evaluation method is an elastic wave velocity evaluation method evaluating an elastic wave velocity in a concrete structure 1, the method comprising: a vibration detection step of installing an optical fiber 3 on the concrete structure 1 and setting a measurement point P1, a measurement point P2, and an excitation point R substantially in a straight line in a Y axis direction along an installation place of the optical fiber 3, and detecting by the optical fiber 3 respective vibrations which are generated at the measurement point P1 and the measurement point P2 by excitation at the excitation point R; and an elastic wave velocity calculation step of calculating the elastic wave velocity V1 in a region A1 between the measurement point P1 and the measurement point P2 on the basis of a difference ΔT1 between generation times of the vibrations at the measurement point P1 and the measurement point P2 detected in the vibration detection step and a distance L1 between the measurement point P1 and the measurement point P2.SELECTED DRAWING: Figure 1

According to one embodiment, a stress estimation apparatus includes a processing circuit and an acquirer. The processing circuit detects at least one of a work start time and a work end time for a user performing work during working hours. The processing circuit calculates, based on the detected result, a short-term stress value from a biometric waveform of the user acquired by the acquirer. The processing circuit calculates a baseline based on at least the working-hours short-term stress value. The processing circuit calculates a stress fluctuation range of the user by removing the baseline from the short-term stress value. The processing circuit estimates, based on the stress fluctuation range, a magnitude of long-term stress of the user.

To improve the estimation accuracy of an air pressure of a wheel.SOLUTION: An air pressure estimation apparatus comprises an execution device and a storage device. The storage device stores a relationship regulation model that outputs an index value indicating an air pressure of a wheel of a vehicle when a plurality of types of input data is input. Here, the relationship regulation model is generated in advance by machine learning. The plurality of types of input data includes unsprung acceleration, which is acceleration in a vertical direction to the wheel, and position coordinates, which are coordinates of a point at which the vehicle is located. The execution device acquires the plurality of types of input data (S11). The execution device outputs the index value by inputting the acquired plurality of types of input data to the relationship regulation model (S13).SELECTED DRAWING: Figure 2

A tire pressure estimation device and a tire pressure estimation method are provided that can estimate tire air pressure with high accuracy. [Solution] Tire pressure estimation device 1 is a tire pressure estimation device that estimates the air pressure of a vehicle tire. Tire pressure estimation device 1 includes extraction means 9 that extracts rotation-synchronous components from a wheel speed signal while the vehicle is running, frequency analysis means 10 that performs a predetermined frequency analysis on the output from the wheel speed signal after the rotation-synchronous components have been removed, and air pressure value acquisition means 11 that inputs vibration components in a predetermined frequency band obtained by the frequency analysis to relationship setting means 12 to acquire an air pressure value. Extraction means 9 calculates the rotation-synchronous components by averaging the wheel speed signal divided for each tire rotation.

The stress estimation device acquires the awakening degree of the subject and calculates the feature amount of the acquired awakening degree. The feature amount of the awakening degree is, for example, a ratio at which the temporal change of the awakening degree is within a predetermined range, information defining a histogram showing the distribution of the temporal change of the awakening degree, and the like. Then, the stress estimation device estimates the stress from the calculated feature amount using the stress model.

The application discloses an integrated flue template construction process abnormality detection method based on visual identification, which comprises the following steps: performing multi-person posture estimation and action recognition on a plurality of video streams of a construction site to generate a construction action event sequence; constructing a multi-person action interaction graph and detecting a process conflict by using a space-time graph attention network; processing a double-mode video stream to generate a temperature field time sequence of each supporting rod; extracting a dynamic thermal feature vector; fusing the action event sequence and the dynamic thermal feature space-time to generate an action-thermal combined time sequence feature; inputting the combined time sequence feature into a causal time sequence graph neural network to output a stress estimation value, a stress prediction trajectory and a causal contribution score; performing overload early warning analysis; and generating an integrated construction process abnormality detection report by fusing all the results.

The invention relates to the technical field of ocean energy development, in particular to a rock-soil stress analysis method for corner piles in a seabed mixed type foundation. The method comprises the following steps: collecting seabed geological data and design parameters of a pile foundation, analyzing lateral pile-soil interaction of a steel corner pile in the seabed mixed pile foundation in a complex layered sea soil environment by adopting a finite difference method, and setting reasonable boundary conditions and initial conditions according to actual engineering conditions, and the model can accurately reflect actual conditions. According to the method, a corner pile analysis algorithm is provided, the corner pile analysis algorithm can quickly and effectively complete lateral deformation and stress estimation of a corner pile of a mixed pile foundation in sea soil, the limitation of a conventional estimation calculation method is broken through, a finite difference method is used for carrying out difference on a complex flexural differential equation, a foundation is laid for subsequent programming design, and the calculation efficiency is improved. Therefore, the problem of time consumption of traditional manual calculation is solved, and the application range is expanded.