Structural damage diagnosis under varying environmental conditions—part II: local PCA for non-linear cases

Yan, Aimin; Kerschen, Gaëtan; Boe, Pascal De; Golinval, Jean‐Claude

doi:10.1016/j.ymssp.2004.12.003

Cited by 239 publications

(156 citation statements)

References 13 publications

Supporting

Mentioning

155

Contrasting

Unclassified

Order By: Relevance

“…If these principle components are removed, one should be left with a dataset representing the true behaviour of only the bridge. Yan et al [103] implemented this technique using simulated linear data and, later, pricewise linear data [104], by increasing the PCA model order to account for the nonlinear response to sub-zero temperatures. The premise of this technique lies in utilising PCA's dimensionality reduction capabilities in a novel way.…”

Section: Pattern Recognition Methodsmentioning

confidence: 99%

A State of the Art Review of Modal-Based Damage Detection in Bridges: Development, Challenges, and Solutions

2017

View full text Add to dashboard Cite

Abstract:Traditionally, damage identification techniques in bridges have focused on monitoring changes to modal-based Damage Sensitive Features (DSFs) due to their direct relationship with structural stiffness and their spatial information content. However, their progression to real-world applications has not been without its challenges and shortcomings, mainly stemming from: (1) environmental and operational variations; (2) inefficient utilization of machine learning algorithms for damage detection; and (3) a general over-reliance on modal-based DSFs alone. The present paper provides an in-depth review of the development of modal-based DSFs and a synopsis of the challenges they face. The paper then sets out to addresses the highlighted challenges in terms of published advancements and alternatives from recent literature.

show abstract

Section: Pattern Recognition Methodsmentioning

confidence: 99%

A State of the Art Review of Modal-Based Damage Detection in Bridges: Development, Challenges, and Solutions

2017

View full text Add to dashboard Cite

show abstract

“…The effect of environmental conditions has been investigated [49] and various methods are adopted to remove this effect, such as principal component analysis (PCA) [50,51], factor analysis [52], nonlinear PCA based on unsupervised support vector machine [53], the Cointegration concept for non-stationary time series [54], PCA method in time-varying systems [55], etc. Moreover, the novelty detection and outlier analysis are used to perform the lowest level of damage identification in operational conditions [56,57], and the multivariate statistical analysis method becomes popular for automatically revealing the damage existence using vibration data under changing environmental and operational conditions [58][59][60].…”

Section: Methods For Changing Environmental Conditionsmentioning

confidence: 99%

The State-of-the-Art on Framework of Vibration-Based Structural Damage Identification for Decision Making

2017

View full text Add to dashboard Cite

Abstract:Research on detecting structural damage at the earliest possible stage has been an interesting topic for decades. Among them, the vibration-based damage detection method as a global technique is especially pervasive. The present study reviewed the state-of-the-art on the framework of vibration-based damage identification in different levels including the prediction of the remaining useful life of structures and the decision making for proper actions. This framework consists of several major parts including the detection of damage occurrence using response-based methods, building reasonable structural models, selecting damage parameters and constructing objective functions with sensitivity analysis, adopting optimization techniques to solve the problem, predicting the remaining useful life of structures, and making decisions for the next actions. For each part, the commonly used methods were reviewed and the merits and drawbacks were summarized to give recommendations. This framework is aimed to guide the researchers and engineers to implement step by step the structure damage identification using vibration measurements. Finally, the future research work in this field is recommended.

show abstract

“…This technique is used many times in the literature due to its easy way of programming. Some of the applications of this technique are to achieve objectives such as surface roughness [14], structural damage diagnosis [15], multi-objective optimization [13].…”

Section: Experimentationmentioning

confidence: 99%

Stability Analysis of Radial Turning Process for Superalloys

Jiménez

Boto

Irigoien

et al. 2017

Management Systems in Production Engineering

View full text Add to dashboard Cite

Abstract:Stability detection in machining processes is an essential component for the design of efficient machining processes. Automatic methods are able to determine when instability is happening and prevent possible machine failures. In this work a variety of methods are proposed for detecting stability anomalies based on the measured forces in the radial turning process of superalloys. Two different methods are proposed to determine instabilities. Each one is tested on real data obtained in the machining of Waspalloy, Haynes 282 and Inconel 718. Experimental data, in both Conventional and High Pressure Coolant (HPC) environments, are set in four different states depending on materials grain size and Hardness (LGA, LGS, SGA and SGS). Results reveal that PCA method is useful for visualization of the process and detection of anomalies in online processes.

show abstract

Structural damage diagnosis under varying environmental conditions—part II: local PCA for non-linear cases

Cited by 239 publications

References 13 publications

A State of the Art Review of Modal-Based Damage Detection in Bridges: Development, Challenges, and Solutions

A State of the Art Review of Modal-Based Damage Detection in Bridges: Development, Challenges, and Solutions

The State-of-the-Art on Framework of Vibration-Based Structural Damage Identification for Decision Making

Stability Analysis of Radial Turning Process for Superalloys

Contact Info

Product

Resources

About