Predicting remaining life by fusing the physics of failure modeling with diagnostics

Kacprzynski, Gregory J.; Sarlashkar, Avinash; Roemer, Michael; Hess, Andrew; Hardman, Bill

doi:10.1007/s11837-004-0029-2

Cited by 104 publications

(58 citation statements)

References 6 publications

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“…Physics-based (i.e., model-based) approaches make use of the system models to estimate the RUL or other relevant metrics, which rely on relatively accurate physics-based models for prediction, such as physical failure models [206], filtering models [207], and statistical models. The advantage of physics-based approaches is that the physical knowledge of the system is incorporated into the monitoring process, which is especially useful for predicting system responses to new loading conditions and system configurations such as the damage status.…”

Section: Damage Prognosis Methodologiesmentioning

confidence: 99%

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

2017

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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.

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Section: Damage Prognosis Methodologiesmentioning

confidence: 99%

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

2017

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“…The strain-life method was used to determine the time required for crack initiation, while Paris' law was used to obtain the time required for the crack to grow from initial crack size to the critical value. Kacprzynksi et al [15] developed a prognostic tool which predicts gear failure probability by fusing physics-of-failure models and diagnostics information. The results showed variance reduction in failure probability when diagnostics information was present.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Prognostic algorithms have been proposed in a large number of publications for various industrial applications. Those algorithms are mostly either data-driven [3][4][5][6][7], physically motivated [8][9][10][11][12][13][14][15][16] or model and data integrated [17][18][19][20][21][22][23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Integrated Equipment Health Prognosis Considering Crack Initiation Time Uncertainty and Random Shock

Zhao

Xie

Tian

et al. 2017

Chin. J. Mech. Eng.

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With integrated equipment health prognosis, both physical models and condition monitoring data are utilized to achieve more accurate prediction of equipment remaining useful life (RUL). In this paper, an integrated prognostics method is proposed to account for two important factors which were not considered before, the uncertainty in crack initiation time (CIT) and the shock in the degradation. Prognostics tools are used for RUL prediction starting from the CIT. However, there is uncertainty in CIT due to the limited capability of existing fault detection tools, and such uncertainty has not been explicitly considered in the literature for integrated prognosis. A shock causes a sudden damage increase and creates a jump in the degradation path, which shortens the total lifetime, and it has not been considered before in the integrated prognostics framework either. In the proposed integrated prognostics method, CIT is considered as an uncertain parameter, which is updated using condition monitoring data. To deal with the sudden damage increase and reduction of total lifetime, a virtual gradual degradation path with an earlier CIT is introduced in the proposed method. In this way, the effect of shock is captured through identifying an appropriate CIT. Examples of gear prognostics are given to demonstrate the effectiveness of the proposed method.

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“…A general method was purposed by Chelidze and Cusumano [108] for tracking the evolution of hidden damage process in the situation that a slowly evolving damage process is coupled to a fast, directly observable dynamical system. Some different approaches used model-based techniques for prognosis were proposed in [109][110][111][112][113][114]. However, model-based techniques are merely applied for some specific components and each requires a different mathematical model.…”

Section: Model-based Approachesmentioning

confidence: 99%

“…Model-based approaches [104][105][106][107][108][109][110][111][112][113][114] • Can be highly accurate • Require less data then data-driven approaches…”

Section: Approachesmentioning

confidence: 99%

Machine Fault Diagnosis and Prognosis: The State of The Art

Tran¹,

Yang²

2009

International Journal of Fluid Machinery and Systems

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Machine fault diagnostic and prognostic techniques have been the considerable subjects of condition-based maintenance system in the recent time due to the potential advantages that could be gained from reducing downtime, decreasing maintenance costs, and increasing machine availability. For the past few years, research on machine fault diagnosis and prognosis has been developing rapidly. These publications covered in the wide range of statistical approaches to model-based approaches. With the aim of synthesizing and providing the information of these researches for researcher's community, this paper attempts to summarize and classify the recent published techniques in diagnosis and prognosis of rotating machinery. Furthermore, it also discusses the opportunities as well as the challenges for conducting advance research in the field of machine prognosis.

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Predicting remaining life by fusing the physics of failure modeling with diagnostics

Cited by 104 publications

References 6 publications

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

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

Integrated Equipment Health Prognosis Considering Crack Initiation Time Uncertainty and Random Shock

Machine Fault Diagnosis and Prognosis: The State of The Art

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