Mitsubishi Electric Research Laboratories, Inc.

Mitsubishi Electric Corporation

Other

Dehong Liu

Petros T Boufounos

Hassan Mansour

Ulugbek Kamilov

Yanting Ma

Philip Orlik

Anthony Vetro

Koon Hoo Teo

Bingnan Wang

Chungwei Lin

Retsu Sugawara

Zafer Sahinoglu

Masao Akiyoshi

Yebin Wang

Yuichi Taguchi

Hiroyuki Handa

Norihiko Hana

Lei Zhou

Makoto Kanemaru

Siheng Chen

Bihan Wen

Muhammad Lodhi

Suhas Lohit

Varun Kelkar

Kevin Degraux

Zemin Zhang

Ajinkya Kadu

Li Li

Shen Zhang

Lantao Yu

Zhe Zhang

Laixi Shi

Xiangtian Zheng

Youye Xie

Muhammad Asad Lodhi

A computer-implemented method is provided for detecting broken bar faults of an induction motor during operations. The method includes steps of injecting a frequency modulation continuous wave (FMCW) voltage signal to the voltage source to power the motor, acquiring, in a time domain, a signal of a stator current powering the induction motor via an interface, performing Fourier Transform (FT) on the stator current and the injected FMCW signal to get spectra of the stator current and the injected signal, computing cross correlation between the spectrum of injected signal and the spectrum of stator current, extracting a fault signature at frequency f=±2(1−s)fin the cross-correlation function, and detecting a broken-bar fault in the induction motor if the fault signature magnitude is greater than a threshold.

System and method for detecting broken-bar fault in squirrel-cage induction motors

A fault detection system of eccentricity severity of an induction machine including a rotor and stator is provided. The fault detection system includes a sensor interface configured to acquire sensor signals from sensors arranged at predetermined positions of the induction machine, wherein the sensor signals are indicative of an eccentricity level of a rotor of the induction machine, a memory coupled with a processor. The memory stores training data sets and instructions implementing a learning-based fault detection method for the induction machine. The instructions include steps of generating an eccentricity feature matrix from the sensor signals, where in the sensor signals include load torque, rotor speed, vibration acceleration of the rotor, vibration speed of the rotor, and current spectral of the stator or the induction machine, determining an eccentricity level of the induction machine based on the eccentricity feature matrix using the learning-based fault detection method, wherein the learning-based fault detection method is configured to find the eccentricity level from learning-based eccentricity feature matrix data sets.

System and method for eccentricity severity estimation of induction machines using a sparsity-driven regression model

A controller is provided for generating carrier signals controlling a pulse width modulation (PWM) inverter driving an electric actuator. The controller includes an interface configured to connect to a victim circuit via sensors, wherein the victim circuit includes the power system or the electric actuator or a combination of the power system and the electric actuator, wherein the sensors are configured to measure an electromagnetic-interference (EMI) spectrum, a memory configured to store modulation frequency ranges, the measured electromagnetic-interference (EMI) spectral data of different frequency carriers, a desired EMI spectrum and a learning-based carrier design program, and a processor, in connection with the memory, configured to perform generating a frequency modulation (FM) carrier signal by solving an optimization problem, wherein the optimization problem is generated regarding a sweep time for a predetermined frequency by the learning-based carrier design program, and a PWM generator configured to generate PWM signals based on the FM carrier signal.

Electromagnetic interference (EMI) mitigation in pulse width modulation (PWM) inverters using learning-based frequency modulated carriers

A fault detection system is provided to extract fault signature from the time-domain stator current signal of a motor under varying load operations by solving a joint blind deconvolution-demodulation problem, where the stator current of a motor under varying operating conditions is modeled as a stator current of a steady operating condition influenced by the system response vector and a load modulation vector. A proximal alternating linearized minimization-type method is used to solve the joint blind deconvolution-demodulation problem, assuming that the spectrum of the sought-after signal is sparse. Motor fault detection is then performed using the recovered stator current of a steady operating condition.

System and method of extracting motor fault signature using sparsity-driven joint blind deconvolution and demodulation

An image forming system for constructing a whole large image of an object is provided. The image forming system includes an interface configured to sequentially acquire images of partial areas of the object obtained by a camera, wherein two adjacent images of the partial areas include overlap portions, wherein the sequential images correspond to a three dimensional (3D) surface of the object, wherein the geometrical information (geometrical parameters) of the object is provided, wherein an initial pose of the camera is provided. The system further includes a memory to store computer-executable programs including a pose estimation method and a stitching method, and an image stitching processor configured to perform steps of estimating camera poses with respect to the sequential images by the robust camera pose estimation method which imposes low-rankness and joint sparsity of relative pose matrices, projecting the sequential images into a 3D surface based on the camera pose estimations, and constructing a two-dimensional (2D) image of the object by interpolating projected surface images; outputting the constructed 2D image via the interface.

System and method of image stitching using robust camera pose estimation

A computer-implemented method is provided for detecting broken bar faults of an induction motor during operations. The method includes steps of acquiring, in a time domain, a signal of a stator current powering the induction motor with a fundamental frequency via an interface, wherein the induction motor is under a varying speed operation; converting the stator current to a complex space vector; transforming the complex vector to a transformed stator current by referencing to synchronous reference frame; performing Short time Fourier Transform (STFT) on the transformed stator current to get spectrogram matrix; removing a DC component from the spectrogram matrix; determining, in a frequency domain, sparse and smooth frequency components in the spectrogram matrix, wherein the determining includes a graph-based method by imposing a smoothness constraint and a sparsity constraint on the frequency component; and detecting a fault in the induction motor if the frequency component includes a continuously changing and sparse fault frequency component in the spectrogram matrix.

System for broken-rotor bar detection in inverter-fed induction motors using graph-based motor current signature analysis

Systems and methods for image processing for determining a registration map between a first image of a scene with a second image of the scene, include solving an optimal transport (OT) problem to produce the registration map by optimizing a cost function that determines a minimum of a ground cost distance between the first and the second images modified with an epipolar geometry-based regularizer including a distance that quantifies the violation of an epipolar geometry constraint between corresponding points defined by the registration map. The ground cost compares a ground cost distance of features extracted within the first image with a ground cost distance of features extracted from the second image.

Systems and methods for image processing based on optimal transport and epipolar geometry

A radar image processing device is provided for generating a radar image from a region of interest (ROI). The radar image processing device receives transmitted radar pulses and radar echoes reflected from the ROI at different positions along a path of a moving radar platform and stores computer-executable programs including a range compressor, a graph modeling generator, a signal aligner, a radar imaging generator and a focused image generator. The radar image processing device performs range compression on the radar echoes by deconvolving the transmitted radar pulses and a radar measurement to obtain frequency-domain signals, generate a graph model represented by sequential positions of the moving radar platform and a graph shift matrix computed using the frequency-domain signals, iteratively denoise and align the frequency-domain signals to obtained denoised data and time shifts by solving a graph-based optimization problem represented by the graph model, wherein the approximated time shifts compensate phase misalignments caused by perturbed positions of the moving radar platform, and perform radar imaging based on the denoised data and the estimated time shifts to generate focused radar images.

Graph-based array signal denoising for perturbed synthetic aperture radar

A permittivity sensor, for determining an image of a distribution of permittivity of a material of an object in a scene, comprising an input interface, a hardware processor, and an output interface is provided. The input interface is configured to accept phaseless measurements of propagation of a known incident field through the scene and scattered by the material of the object in the scene. The hardware processor is configured to solve a multi-variable minimization problem over unknown phases of the phaseless measurements and unknown image of the permittivity of the material of the object by minimizing a difference of a nonlinear function of the known incident field and the unknown image with a product of known magnitudes of the phaseless measurements and the unknown phases. Further, the output interface is configured to render the permittivity of the material of the object provided by the solution of the multi-variable minimization problem.

Sensing using inverse multiple scattering with phaseless measurements

A motor comprising a shaft, an array of stator assemblies rigidly attached to the shaft, each stator assembly includes a stator yoke having a toroid shape fixed around the shaft and having a number of slots at radial and axis directional faces with windings within the slots of the stator yoke, and a rotor assembly rotatively attached to the shaft to enclose the array of stator assemblies, the rotor assembly has a rotor drum with sections, each section embraces one stator assembly, each section has two axial-flux permanent magnet arrays attached on axial-directional inner surfaces of the section and has one radial-flux permanent magnet array attached on a radial-directional inner surface of the section furthest from the shaft, wherein the axial-flux and the radial-flux permanent magnet arrays with the number of pole pairs equals the number of the stator slots plus or minus the number of stator winding pole pair.

Multi-layer axial and radial flux vernier permanent magnet motor

Systems, methods and apparatus for image processing for reconstructing a super resolution image from multispectral (MS) images. Receive image data and initialize a fused image using a panchromatic (PAN) image, and estimate a blur kernel between the PAN image and the MS images as an initialization function. Iteratively, fuse a MS image with an associated PAN image of a scene using a fusing algorithm. Each iteration includes: update the blur kernel based on a Second-Order Total Generalized Variation function to regularize a kernel shape; fuse the PAN image and MS images with the updated blur kernel based on a local Laplacian prior function to regularize the high-resolution information to obtain an estimated fused image; compute a relative error between the estimated fused image of the current iteration and a previous estimated fused image from a previous iteration, to a predetermined threshold, to stop iterations stop, to obtain a PAN-sharpened image.

Systems and methods for blind multi-spectral image fusion

A measurement device is configured to set an observation surface on a surface of a structure as a measurement surface to measure a change of the measurement surface as a measurement surface change vector. An estimator is configured to generate an estimation model based on a shape model obtained by modeling a shape of the structure. The estimator is configured to acquire a coefficient vector by solving a norm minimization problem by setting, as parameters, a measurement surface change vector and a part of the estimation model. The coefficient vector forms a sparse solution. The estimator is configured to estimate a change of a crack occurrence surface by determining a candidate surface, which is inside the structure and assumed to have a crack, as the crack occurrence surface, based on the coefficient vector and another part of the estimation model.

Estimation device and estimation method

A controller is provided for generating carrier signals for a PWM generator controlling an inverter driving an electric actuator to reduce the EMI level of the inverter. The controller includes an interface configured to connect to the inverter, a memory configured to store a measured electromagnetic-interference (EMI) spectrum, a desired EMI spectrum and an EMI suppression rate program, and a processor. The processor is, in connection with the memory, configured to computing EMI suppression rates for a frequency range, wherein the EMI suppression determined adaptively by the measured EMI spectrum and the desired EMI spectrum, computing sweep duration of discrete frequency, wherein the sweep duration is determined by the EMI suppression rate of the discrete frequency, and a modulator configured to modulate the carrier signals based on the sweep durations of carrier frequencies and to transmit the modulated carrier signals to the PWM generator to generate PWM signals for the inverter.

EMI reduction in PWM inverters using adaptive frequency modulated carriers

A tomographic imaging system receives measurements at a set of frequencies of a wavefield scattered by an internal structure of an object, recursively reconstructs an image of the internal structure of the object until a termination condition is met, and renders the reconstructed image. For a current iteration, the system adds a frequency to a previous set of frequencies used during a previous iteration to produce a current set of frequencies, such that the added frequency is higher than any frequency in the previous set of frequencies, and reconstructs a current image of the internal structure of the object that minimizes a difference between a portion of the scattered wavefield measured at the current set of frequencies and a wavefield synthetized from the current image. A previous image determined during the previous iteration initializes the reconstruction of the current image.

Tomographic imaging system

A system for estimating a severity of a bearing fault in an induction motor, uses a set of filters and a set of quantitative models designed for a set of fault frequencies. The system, upon receiving the measurements of the stator current, extracts the first fault current from the stator current using the first filter, determine the first mutual inductance variation from the first fault current using the first quantitative model, and classify the first mutual inductance variation with the fault severity classifier to determine the severity of a first type of fault in the induction motor. Similarly, the system classifies a second type of fault using the second filter and the second quantitative model. The system outputs one or combination of the severity of the first type of fault in the induction motor and the severity of the second type of fault in the induction motor.

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Lexington, MA, United States of America

Dehong Liu