Mitsubishi Electric Corporation

Johns Hopkins University

The Circle for the Promotion of Science and Engineering

Kenji Amaya

Masao Akiyoshi

Norihiko Hana

Katsuyuki Taguchi

Masashi Ueshima

Kento Nakada

Masaki Umeda

Provided are a shape model setting circuitry for setting a shape model of a target structure, a crack candidate plane in the shape model, and an observation plane of the shape model, an estimation model generator for generating an estimation model obtained from a numerical analysis of a structural analysis model by sequentially changing a boundary condition of the crack candidate plane in the structural analysis model generated from the shape model, and a crack state analyzer for estimating a position and a size of the crack by obtaining a distribution of load and displacement in the crack candidate plane at the same time by probabilistic inference through the application of an observation plane deformation vector indicating deformation of the observation plane obtained from measurement values, the estimation model, and a latent variable indicating presence or absence of the crack in the crack candidate plane.

Crack estimation device, failure diagnosis device, crack estimation method, and failure diagnosis method for rotating machine

A crack estimation device which accurately estimates a crack inside a structure is provided. The crack estimation device includes: a measurement unit which measures deformation of a measurement plane as a measurement plane deformation vector; a model generation unit which sets deformation of the measurement plane when a crack is generated in a crack generation plane, as a measurement plane estimated change vector for multiple types of crack candidates; and a crack state analysis unit which obtains a similarity between the measurement plane deformation vector and the measurement plane estimated change vector, normalizes the similarity, and estimates the crack generated in the crack generation plane from a result obtained by multiplying a vector of a state quantity indicating a state of the crack generation plane by the normalized similarity for each crack candidate, and adding together results of the multiplication for all the crack candidates.

Crack estimation device and crack estimation method

The present invention is directed to a new joint estimation framework employing MAP estimation based on pixel-based latent variables for tissue types. The method combines the geometrical information described by latent MRF, statistical relation between tissue types and P-C coefficients, and Poisson noise models of PCD data, and makes possible the continuous Baysian estimation from detected photon counts. The proposed method has better accuracy and RMSE than the method using FBP and thresholding. The joint estimation framework has the potential to further improve the accuracy by introducing more information about tissues in human body, e.g., the location, size, and number of tissues, or limited variation of neighboring tissues, which will be easily formulated by pixel-based latent variables.

Joint estimation of tissue types and linear attenuation coefficients for computed tomography

A provided optical-phase-distribution measuring method, by which optical phase distribution is identified at high speed and with high accuracy from information on light-intensity distribution without using a special measuring device, comprises steps: for inputting light to be measured to optical systems, respectively, modulating the intensity and the phase, detecting the output light to be measured with CCD, and measuring the intensity distribution of detected light to be measured as an image with an optical-phase-distribution measuring system provided with the two different optical systems; for setting an observation equation, based on the intensity distribution and on the optical characteristics of the optical systems; for setting a phase-distribution identification inverse-problem from the observation equation, and formulating the set phase-distribution identification inverse-problem as a first nonlinear optimization problem in which complex amplitude representing the light to be measured is assumed to be a design variable; for converting the first nonlinear optimization problem to a second nonlinear optimization problem, in which expansion coefficients in a series expansion are assumed to be design variables, by series expansion of the phase distribution of the light to be measured; and for identifying the phase distribution of the light to be measured by solving the second nonlinear optimization problem.

Growing community of inventors

Tokyo, Japan

Kenji Amaya