Vibrant Technology Inc

Scotts Valley, CA, United States

Vibrant Technology Inc

Scotts Valley, CA, United States

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Ganeriwala S.N.,Spectra Quest Inc. | Yang J.,Spectra Quest Inc. | Richardson M.,Vibrant Technology Inc.
Sound and Vibration | Year: 2011

The structural integrity of blades is critical to the continued operation of a wind turbine. Resonant or modal properties of a mechanical structure are directly influenced by its physical properties. So any change in the physical properties of a structure should cause a change in its modal parameters. In this article, we present test results from a wind turbine blade with different induced cracks. Each result shows that some of the modes of the blade are significantly affected by a crack and that the modal parameters change more significantly with a more severe crack.


Ganeriwala S.N.,Spectra Quest Inc. | Kanakasabai V.,Spectra Quest Inc. | Richardson M.,Vibrant Technology Inc.
Conference Proceedings of the Society for Experimental Mechanics Series | Year: 2011

On-line surveillance of the structural integrity of wind turbines is a critical need in this currently fast growing industry. The structural integrity of the turbine blades themselves is critical to the continued operation of a wind turbine. It is well known that the resonant or modal properties of a mechanical structure are directly influenced by its physical properties. Hence, any change in the physical properties of a structure should cause a change in its modal parameters. One question is always apparent though; "Do structural faults cause significant changes in a structure's modal parameters?" In this paper, we present test results from a wind turbine blade with different cracks induced in it. Each result shows that some of the modes of the blade are significantly affected by a crack, and that the modal parameters change more significantly with a more severe crack. Changes in modal frequency, damping, and mode shape are considered. Using changes in modal parameters to indicate physical damage to turbine blades should be implemented in the online continuous monitoring of wind turbines. In such a system, differences between monitored modal parameters and their base-line values could be compared to both absolute and percentage difference warning levels. Comparing changes between operating and baseline modal parameters with warning levels will indicate when the blades of a wind turbine have undergone physical damage.


Richardson S.,Vibrant Technology Inc. | Richardson M.,Vibrant Technology Inc. | Tyler J.,Vibrant Technology Inc. | McHargue P.,Vibrant Technology Inc.
Conference Proceedings of the Society for Experimental Mechanics Series | Year: 2016

In a previous paper entitled Using Operating Deflection Shapes to Detect Unbalance in Rotating Equipment [Ganeriwala, S.N.,Schwarz, B.,Richardson, M.: Using operating deflection shapes to detect unbalance in rotating equipment. In: IMAC XXVII, Orlando, February 2009], we introduced the idea of numerically comparing currently acquired operating data with archived data to identify unbalances in rotating machinery. In a follow-up paper [Richardson, S.,Tyler, J.,McHargue, P.,Richardson, M.: A new measure of shape difference. In: IMAC XXXII, 3–6 February 2014], we introduced a new metric for comparing two deflection shapes called the Shape Difference Indicator or SDI. In this paper, we introduce a refined version of the SDI algorithm, and present new results to verify its utility for locating and quantifying unbalance in rotating machinery. We make two underlying assumptions about rotating machines; (1) all rotating machines are excited by inherent unbalance forces which cannot be directly measured, and (2) order-related vibration levels acquired from multiple locations on a machine can be directly correlated with specific unbalance conditions. We show that by comparing current with archived ODS data, specific unbalance conditions can be pinpointed. © The Society for Experimental Mechanics, Inc. 2016.


Schwarz B.,Vibrant Technology Inc | Richardson S.,Vibrant Technology Inc | Richardson M.,Vibrant Technology Inc
Conference Proceedings of the Society for Experimental Mechanics Series | Year: 2016

In this paper, we employ the fact that all experimental vibration data, whether in the form of a set of FRFs or a set of output-only spectra, is a summation of resonance curves, each curve due to a mode of vibration. We also use this superposition property of modes to calculate a modal participation matrix, a measure of the participation of each mode in the experimental vibration data. First we show how this superposition property can be used to curve fit a set of FEA mode shapes to EMA mode shapes or ODS’s. The modal participation matrix is calculated as a least-squared-error solution, so any number of FEA mode shapes can be curve fit to any number of EMA mode shapes or ODS’s. Next we show how an expanded and enhanced set of FRFs, Cross spectra or ODS FRFs is obtained by curve fitting FEA mode shapes to experimental data. This approach in an alternative to FEA Model Updating, where an FEA model is modified so that its modes more closely correlate with experimental data. By curve fitting FEA shapes to experimental data, an extending and enhanced dynamic model is obtained which is more suitable for machinery & structural health monitoring, and for troubleshooting noise & vibration problems using SDM and MIMO methods. © The Society for Experimental Mechanics, Inc. 2016.


Schwarz B.J.,Vibrant Technology Inc | Richardson M.H.,Vibrant Technology Inc
Conference Proceedings of the Society for Experimental Mechanics Series | Year: 2014

Modes of vibration are defined as solutions to a set of linear differential equations which characterize the resonant dynamic behavior of structures. One of the properties of these linear equation solutions is superposition. That is, the overall structural response can be represented as a summation of contributions from all of the modes. In this paper, it is shown how the superposition property of mode shapes can be used to; • Decompose a set of Operating Deflection Shapes (ODS’s) into a summation of mode shape contributions. • Expand a set of shapes using another set of shapes with more DOFs in them. • Decompose a set of frequency or time domain waveforms into a summation of resonance waveforms. • Scale a set of operational mode shapes or ODS’s so they can be used as a modal model for modeling& simulation studies. • Derive the Modal Assurance Criterion (MAC) as a measure of the correlation between a pair of shapes. All of these applications lend more meaning to the term modal participation, which is commonly used to characterize structural vibration as a summation of resonant contributions. This new definition of modal participation is illustrated with several examples. © The Society for Experimental Mechanics, Inc. 2014.


Richardson S.,Vibrant Technology Inc | Tyler J.,Vibrant Technology Inc | McHargue P.,Vibrant Technology Inc | Richardson M.,Vibrant Technology Inc
Conference Proceedings of the Society for Experimental Mechanics Series | Year: 2014

The Modal Assurance Criterion (MAC) is currently the most popular method for measuring whether or not two mode shapes are strongly correlated. In fact, MAC can be applied to any two sets of data that can be defined as a shape, e.g. mode shapes, Operating Deflection Shapes (ODS’s), or two time or frequency domain waveforms. When applied to two Frequency Response Functions (FRFs) MAC has been renamed FRAC (Allemang RJ, The modal assurance criterion (MAC): twenty years of use and abuse. In: Proceedings of the international modal analysis conference, 2002). MAC values range between 0 and 1. If MACD1, the two shapes are identical. A “rule of thumb” is that two shapes are similar or strongly correlated if MAC>0.9, and they are different or weakly correlated if MAC<0.9. MAC is a measure of the co-linearity of two shapes. That is, it measures whether or not two shapes lie together on the same straight line. MAC has two limitations however; 1. MAC does not measure the difference in values of two shapes. 2. MAC requires at least two shape components. The MAC value for two shapes with one component, i.e. two scalars, is always 1. In this paper, a new measure, called the Shape Difference Indicator (SDI), is introduced which overcomes the two limitations of MAC. This new measure is more useful for machinery and structural health monitoring applications where, for instance, changes in vibration levels or temperatures are typically used to detect a fault. An example is given showing how SDI indicates that shape pairs are different even when their MAC values indicate that they are the same, i.e. they are co-linear. A second example shows how SDI can be used not only to detect a fault, but also to correctly identify the fault by comparing its shape values with those in a database of known fault conditions. © The Society for Experimental Mechanics, Inc. 2014.


Schwarz B.,Vibrant Technology Inc | Richardson S.,Vibrant Technology Inc | Richardson M.,Vibrant Technology Inc
Conference Proceedings of the Society for Experimental Mechanics Series | Year: 2015

In a rotating machine, the dominant forces are applied at multiples of the machine running speed, called orders. An order-tracked ODS is assembled from the peaks at one of the order frequencies in a set of response frequency spectra of a machine. An order-tracked ODS is a convenient way to visualize and monitor the health of the machine. In this paper, it is shown how modes participate in an order-tracked ODS of a rotating machine, and how they participate differently at different operating speeds. It is also shown how the modal participation can be used to expand an order-tracked ODS so that it is suitable for display on a model of the machine. With an animated ODS display, changing vibration levels and vibration hot spots can be observed while the machine is running. © The Society for Experimental Mechanics, Inc. 2015.


Schwarz B.,Vibrant Technology Inc. | Richardson M.,Vibrant Technology Inc.
Conference Proceedings of the Society for Experimental Mechanics Series | Year: 2014

Damping forces are typically ignored during the Finite Element Analysis (FEA) of mechanical structures. In most real structures, it can be assumed that there are several damping mechanisms at work, but they may be difficult to identify, and even more difficult to model. Since both mass & stiffness matrices are available during an FEA, a common method of modeling viscous damping is with a proportional damping matrix. That is, the viscous damping matrix is assumed to be a linear combination of the mass & stiffness matrices. Therefore, in order to model viscous damping with a proportional damping matrix, the two constants of proportionality must be determined. In this paper, a least-squared-error relationship between experimental modal frequency & damping and the proportional damping constants of proportionality is developed. An example is included in which experimental modal parameters are used to calculate the constants of proportionality. The modal parameters of an FEA model with proportional damping are then compared with the original experimental modal parameters. © The Society for Experimental Mechanics 2014.


Schwarz B.,Vibrant Technology Inc | Richardson S.,Vibrant Technology Inc | Richardson M.,Vibrant Technology Inc
Conference Proceedings of the Society for Experimental Mechanics Series | Year: 2015

In this paper it is shown how a Finite Element Analysis (FEA) model can be used together with experimental Operating Deflection Shape (ODS) data to calculate stresses & strains in a machine or mechanical structure. This allows for the on-line monitoring of structural stress & strain, which can be compared with prescribed warning levels to insure that dangerous levels are not exceeded. Examples are included to illustrate how ODS data measured with multiple accelerometers can be used to calculate stress & strain. Also, when this data is displayed together an ODS in animation on a 3D model of the machine or structure, high levels of stress or strain, or “hot spots”, are quickly observed. © The Society for Experimental Mechanics, Inc. 2015.


Schwarz B.,Vibrant Technology Inc. | Richardson S.,Vibrant Technology Inc. | Richardson M.,Vibrant Technology Inc.
Sound and Vibration | Year: 2016

A finite-element analysis (FEA) model can be used together with experimental operating deflection shape (ODS) data to calculate stresses and strains in a machine or mechanical structure. This allows for the on-line monitoring of structural stress and strain, which can be compared with prescribed warning levels to ensure that dangerous levels are not exceeded. Examples are included to illustrate how ODS data measured with multiple accelerometers can be used to calculate stress and strain. Also, when these data are displayed together, an ODS in animation on a 3D model of the machine or structure, high levels of stress or strain, or "hot spots," are quickly observed.

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