[go: up one dir, main page]

Mishra et al., 2016 - Google Patents

Remaining useful life estimation with lamb-wave sensors based on wiener process and principal components regression

Mishra et al., 2016

View PDF
Document ID
1748364665920214786
Author
Mishra S
Vanli O
Publication year
Publication venue
Journal of Nondestructive Evaluation

External Links

Snippet

This paper proposes a new approach for predicting the remaining useful life of a structure from Lamb wave sensor data using principal component regression and Wiener process degradation modeling. Principal component regression is used for extracting damage …
Continue reading at www.researchgate.net (PDF) (other versions)

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2291/00Indexing codes associated with group G01N29/00
    • G01N2291/02Indexing codes associated with the analysed material
    • G01N2291/028Material parameters
    • G01N2291/02827Elastic parameters, strength or force
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2291/00Indexing codes associated with group G01N29/00
    • G01N2291/02Indexing codes associated with the analysed material
    • G01N2291/025Change of phase or condition
    • G01N2291/0258Structural degradation, e.g. fatigue of composites, ageing of oils
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/44Processing the detected response signal, e.g. electronic circuits specially adapted therefor
    • G01N29/46Processing the detected response signal, e.g. electronic circuits specially adapted therefor by spectral analysis, e.g. Fourier analysis or wavelet analysis
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/22Details, e.g. general constructional or apparatus details
    • G01N29/24Probes
    • G01N29/2493Wheel shaped probes
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2291/00Indexing codes associated with group G01N29/00
    • G01N2291/04Wave modes and trajectories
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/44Processing the detected response signal, e.g. electronic circuits specially adapted therefor
    • G01N29/4409Processing the detected response signal, e.g. electronic circuits specially adapted therefor by comparison
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2291/00Indexing codes associated with group G01N29/00
    • G01N2291/10Number of transducers
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/04Analysing solids
    • G01N29/07Analysing solids by measuring propagation velocity or propagation time of acoustic waves
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2291/00Indexing codes associated with group G01N29/00
    • G01N2291/01Indexing codes associated with the measuring variable
    • G01N2291/014Resonance or resonant frequency
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/02Analysing fluids
    • G01N29/036Analysing fluids by measuring frequency or resonance of acoustic waves
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by the preceding groups
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2203/00Investigating strength properties of solid materials by application of mechanical stress

Similar Documents

Publication Publication Date Title
Mishra et al. Remaining useful life estimation with lamb-wave sensors based on wiener process and principal components regression
Nguyen et al. Deep learning-based autonomous damage-sensitive feature extraction for impedance-based prestress monitoring
Boškoski et al. Bearing fault prognostics using Rényi entropy based features and Gaussian process models
Saxena et al. Accelerated aging experiments for prognostics of damage growth in composite materials
Li et al. Damage identification in civil engineering structures utilizing PCA‐compressed residual frequency response functions and neural network ensembles
US8494810B2 (en) Component adaptive life management
Xi et al. A copula-based sampling method for data-driven prognostics
Shuai et al. Fault identification using piezoelectric impedance measurement and model-based intelligent inference with pre-screening
Nichols et al. Use of data-driven phase space models in assessing the strength of a bolted connection in acomposite beam
Meeker et al. Statistical methods for probability of detection in structural health monitoring
Fakih et al. Symbolic dynamics time series analysis for assessment of barely visible indentation damage in composite sandwich structures based on guided waves
Soofi et al. Output-only entropy-based damage detection using transmissibility function
Bandara et al. Structural health assessment of timber utility poles using stress wave propagation and artificial neural network techniques
Lakshmi et al. Structural damage detection using ARMAX time series models and cepstral distances
Zhang et al. Guided wave-hidden Markov model for on-line crack evaluation of a full-scale aircraft
Camacho-Navarro et al. Ensemble learning as approach for pipeline condition assessment
Schackmann et al. A unified CNN approach for guided wave-based damage detection, damage size estimation and reliability assessment demonstrated on a complex composite structure
Mishra et al. A multivariate cumulative sum method for continuous damage monitoring with lamb-wave sensors
Shinagam et al. Development of a machine learning algorithm for efficient localization of damage in a composite structure using random forest technique
Duong et al. Pipeline fault diagnosis using wavelet entropy and ensemble deep neural technique
CN118190074B (en) Multi-parameter on-line monitor for tank farm storage tank
Khan et al. Damage assessment of laminated composites using unsupervised autonomous features
US11086750B2 (en) Systems and methods for determination of health indicators using rank correlation analysis
Torres‐Arredondo et al. Signal‐based nonlinear modelling for damage assessment under variable temperature conditions by means of acousto‐ultrasonics
Kong Chen et al. Reducing false damage detections in guided ultrasonic wave monitoring systems using a denoising autoencoder