Oleg V. Shiryayev

Detection of Fatigue Cracks Using Random Decrement Signatures

Damage in structural members usually causes stiffness changes that could be linear or nonlinear. Opening and closing fatigue cracks are usually represented by a bilinear stiffness characteristic. This work describes damage identification approach that is based on the changes in statistical properties of randomdec signatures caused by the onset of nonlinearity. The approach is applied to acceleration data collected from a cracked beam. The results suggest that the method allows to detect the crack if excitation level is high enough. Practical difficulties encountered during implementation are also discussed.

Structural Damage Identification Using Random Decrement Signatures from Experimental Data

This article describes detection of structural damage using random decrement signatures from experimental data. The evaluated technique is model-free and does not require measurements of system inputs. Damage detection is based on detecting changes in the statistical properties of the signatures due to the onset of nonlinearity caused by the damage. Experimental results presented in this article are obtained from an aluminum beam mounted on the shaker. The damage in the beam was in the form of a fatigue crack. The results indicated that the method allows detection of damage if excitation level is high enough. Practical issues encountered during implementation are discussed.

Application of the Random Decrement Technique to a Nonlinear Dynamic System

The majority of structural health monitoring techniques are based on detection of significant variation in vibration parameters. The random decrement technique allows estimation of modal parameters without having direct measurements of the inputs. The technique has been successfully applied for modal analysis and health monitoring of various structures. However, application of the technique requires the assumption of linearity of the system under consideration, which is not always true in reality. In fact, real structural deterioration usually causes nonlinear responses. In this work, random decrement signatures are obtained from systems with dierent types of nonlinearities. It is found that unlike in the linear case, the signatures from nonlinear systems are not equivalent to free responses. Variation of identified modal parameters is investigated with respect to the types and strength of nonlinearities. In addition statistical features of the signatures are considered for use in detection, location, and classification of structural damage.

Sensitivity Studies of Nonlinear Vibration Features For Detection of Cracks in Turbomachinery Components

Detection of fatigue cracks in turbomachinery components is an important and costly task. This work focuses on nonlinearities in the system dynamics resulting from the opening and closing of cracks that causes super-harmonic and sub-harmonic resonances due to harmonic excitations. Preliminary analytical results for a hypothetical compressor disk model are presented. The results suggest that the magnitude of the harmonics caused by the nonlinearity is strongly aected by the size of the crack. Identication of sensitive vibration features is expected to contribute to the development of automated monitoring techniques for aircraft engine disks and other turbomachinery components susceptible to fatigue damage.

Corrosivity Sensor for Exposed Pipelines Based on Wireless Energy Transfer

External corrosion was identified as one of the main causes of pipeline failures worldwide. A solution that addresses the issue of detecting and quantifying corrosivity of environment for application to existing exposed pipelines has been developed. It consists of a sensing array made of an assembly of thin strips of pipeline steel and a circuit that provides a visual sensor reading to the operator. The proposed sensor is passive and does not require a constant power supply. Circuit design was validated through simulations and lab experiments. Accelerated corrosion experiment was conducted to confirm the feasibility of the proposed corrosivity sensor design.

Fatigue Crack Modeling and Analysis in Beams

Fatigue crack detection in aircraft engine bladed disk assemblies is slow, costly and imperfect, but developing an automated Structural Health Monitoring (SHM) system can help to reduce cost and improve detection probability. However, current methods for modeling nonlinear structural response are also too slow to generate suciently large data libraries for automation. In an eort to develop a faster method, fatigue cracks in beams are modeled by modifying the inputs to the structure rather than the structure model itself to produce a closed-form solution for the total response. With this approach, the time to produce data sets is reduced from days to seconds. Crack identication methods are then demonstrated using the data produced by the closed-form approach to correctly identify fatigue cracks in data generated by a more traditional bilinear model. Although the method investigated is orders of magnitude faster and can successfully identify fatigue cracks over certain regions, limitations are observed that require more investigation to resolve. Overall, the proposed method for modeling and identifying fatigue cracks in beams shows promise but will require more development before being used on more complicated structures such as bladed disks.

Investigation of Candidate Features For Crack Detection in Fan and Turbine Blades and Disks

of fatigue cracks in turbo-machinery components is a vital but costly eort. This work focuses on nonlinearities in the response behavior resulting from the opening and closing of cracks that results in super-harmonic resonances due to harmonic excitations. Experimental results for a cracked cantilever beam are presented as well as the results from numerical simulations of an integrally bladed compressor disk FE model. Identication of sensitive vibration features is expected to contribute to the development of automated crack detection techniques for aircraft engine disks.

Aeroelastic System Identification Using the Minimum Model Error Method

The minimum model error method is applied to identify models of a panel undergoing limit-cycle oscillations. This work is focused on identification using free-response position and velocity measurements. The response of the panel was obtained using two discretization approaches: through the use of finite differences and by Galerkins method. Data from both transient and steady-state parts of the response are used for identification. The models obtained using the steady-state part of the free response were not able to capture the behavior of the true system. The models obtained using the transient part of the free response were able to capture the behavior of the panel very accurately. Accuracy of identified models of various model orders is also discussed.

Panel Flutter Model Identification Using the Minimum Model Error Method on the Forced Response Measurements

This work illustrates application of the minimum model error system identification method to obtain the nonlinear state space models of a fluttering panel. Identification using position and velocity data from forced response of the panel is presented here. The response was numerically simulated using two different discretization approaches: through finite differences and using the Galerkins method. Data from two different parts of response time history were considered. First, data where transients due to initial conditions and the forcing were present were used for identification. Then, data when only transients due to forcing were present were used for identification. The models obtained using the forced response of the panel were able to capture the behavior of the true system relatively accurately. Identification of models of different sizes is also discussed. Reduced size models can be successfully created from the forced response data using the minimum model error method. It is demonstrated that the number of degrees of freedom in the model attempted to be identified should be consistent with the number modes observed in the measurements. The response surface method was successfully applied to generate models for various flow regimes.

Analytical Modeling Tool for Design of Hydrocarbon Sensitive Optical Fibers

Pipelines are the main transportation means for oil and gas products across large distances. Due to the severe conditions they operate in, they are regularly inspected using conventional Pipeline Inspection Gages (PIGs) for corrosion damage. The motivation for researching a real-time distributed monitoring solution arose to mitigate costs and provide a proactive indication of potential failures. Fiber optic sensors with polymer claddings provide a means of detecting contact with hydrocarbons. By coating the fibers with a layer of metal similar in composition to that of the parent pipeline, corrosion of this coating may be detected when the polymer cladding underneath is exposed to the surrounding hydrocarbons contained within the pipeline. A Refractive Index (RI) change occurs in the polymer cladding causing a loss in intensity of a traveling light pulse due to a reduction in the fiber’s modal capacity. Intensity losses may be detected using Optical Time Domain Reflectometry (OTDR) while pinpointing the spatial location of the contact via time delay calculations of the back-scattered pulses. This work presents a theoretical model for the above sensing solution to provide a design tool for the fiber optic cable in the context of hydrocarbon sensing following corrosion of an external metal coating. Results are verified against the experimental data published in the literature.