Model-Aided Diagnosis of Mechanical Systems

Natke, H. G.; Cempel, Czeslav

doi:10.1007/978-3-642-60413-3

Cited by 90 publications

(53 citation statements)

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“…[9], is based on an approximation of the change of the eigenvalues and eigenvectors (due to the damage) by a linear Taylor expansion depending on the correction parameters Da j :…”

Section: Inverse Eigensensitivity Methods (Iesm)mentioning

confidence: 99%

Global Damage Identification of the ‘Steelquake’ Structure Using Modal Data

Fritzen

Bohle

2003

Mechanical Systems and Signal Processing

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“…[9], is based on an approximation of the change of the eigenvalues and eigenvectors (due to the damage) by a linear Taylor expansion depending on the correction parameters Da j :…”

Section: Inverse Eigensensitivity Methods (Iesm)mentioning

confidence: 99%

Global Damage Identification of the ‘Steelquake’ Structure Using Modal Data

Fritzen

Bohle

2003

Mechanical Systems and Signal Processing

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“…A greater number of places where the signal is recorded, results in wider possibilities to make conclusions in relation to the whole object (Dąbrowski et al, 2007a). However, not always the increase in number of measuring points is purposeful, since it inevitably leads to an uncontrolled increase in the number of obtained information, whose multidimensionality will result in small usefulness in implementation of established goals (Natke, Cempel, 1997). During the analysis of mutual relations, each subsequent recorded signal increases dimensionality of observation space, which consequently leads to information chaos (Bolc et al, 1991).…”

Section: Comments On the Use Of Vibroacoustic Signalmentioning

confidence: 99%

Indicator of Vibroacoustic Energy Propagation as a Selection Criterion of Design Solution

Klekot¹

2013

Archives of Acoustics

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Contemporary tools which help to design technical objects refer to the conclusions drawn from studying the changes of physical processes accompanying the exploitation, especially to vibroacoustic processes. The main problem is to define such vibroacoustic measures, where their changes would model the analyzed physical phenomena in the best way. Basing on simple indicators which refer to occurring phenomena, it is possible to obtain accurate solutions with a satisfactory reliance level without using complex computing techniques needing detailed descriptors. According to the author, the indicators which are based on the analysis of vibroacoustic energy propagation are very useful in solving engineering problems. These indicators are useful while diagnosing the condition of technical systems, identifying and minimizing the vibroacoustic risks. The possibilities of using such indicators in order to find design solution are illustrated by sample results of the research of the structures with vibroacoustic elements which reduce the noise of rail vehicles by the rail vibration damping.

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“…So, we should determine the symptom limit value S l which enables us to do this safely. This limit value can base on some experimental practice, some standards (e.g., ISO), or it can be assessed by the new concept of symptom reliability R(S) (Natke, 1997;Cempel, 2000). Figure 7 shows this possibility of assessing the symptom limit value S l (the bottom-right panel), combined with another possibility of optimizing the dimension of the primary symptom observation space.…”

Section: Examples Of Simple and Advanced Svd Decomposition Of Real DImentioning

confidence: 99%

“…The application of singular value decomposition (SVD) to this set of diagnostic data enables us to observe the evolution of a few generalized faults of the diagnosed machine, starting from the fault of maximal severity. Applying next the concept of symptom reliability (Cempel et al 2000;Natke et al 1997;Cempel, 1991) to the so extracted generalized fault symptoms, one can calculate the symptom limit value S l , the basis for any diagnostic decision. However, the loadings of machines by production processes (or the environment) are not constant, so that the resulting symptom readings may have some disturbances influencing the assessment of the machine condition.…”

Section: Introductionmentioning

confidence: 99%

Decomposition Of The Symptom Observation Matrix And Grey Forecasting In Vibration Condition Monitoring Of Machines

Cempel¹

2008

International Journal of Applied Mathematics and Computer Science

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With the tools of modern metrology we can measure almost all variables in the phenomenon field of a working machine, and many of the measured quantities can be symptoms of machine conditions. On this basis, we can form a symptom observation matrix (SOM) intended for condition monitoring and wear trend (fault) identification. On the other hand, we know that contemporary complex machines may have many modes of failure, called faults. The paper presents a method of the extraction of the information about faults from the symptom observation matrix by means of singular value decomposition (SVD), in the form of generalized fault symptoms. As the readings of the symptoms can be unstable, the moving average of the SOM is applied with success. An attempt to assess the diagnostic contribution of a primary symptom is made, and also an approach to assess the symptom limit value and to connect the SVD methodology with neural nets is considered. Finally, a condition forecasting problem is discussed and an application of grey system theory (GST) to symptom prognosis is presented. These possibilities are illustrated by processing data taken directly from the machine vibration condition monitoring area.

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Model-Aided Diagnosis of Mechanical Systems

Cited by 90 publications

References 0 publications

Global Damage Identification of the ‘Steelquake’ Structure Using Modal Data

Global Damage Identification of the ‘Steelquake’ Structure Using Modal Data

Indicator of Vibroacoustic Energy Propagation as a Selection Criterion of Design Solution

Decomposition Of The Symptom Observation Matrix And Grey Forecasting In Vibration Condition Monitoring Of Machines

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