Structural Health Management Research Articles

Gradient enhanced damage sizing for structural health management

A gradient enhanced method is proposed to extract a probability distribution of damage size based on damage images from structural health monitoring. The method provides comprehensive information about damage size and enables prediction of remaining useful life (RUL) of aircraft plate-like structures. A three-step procedure is designed to construct a likelihood function about damage size from intensity image, and a gradient function is employed a priori to obtain a narrow distribution of damage size in the Bayesian framework, providing the empirical probability density function of damage size, from which the probability of damage size larger than critical crack size can be calculated. RUL of plate-like structures can be obtained by calculating the cycles after which the crack size would reach a critical value by a damage growth model. The proposed method converts an ultrasonic damage imaging result to probability density function of damage size, with potential to provide accurate and precise estimation of RUL.

Novel Real-Time Nondestructive Technology for Chemical and Structural Health Management of Solid Rocket Propellants


 
 
 
 
 
 An innovative prognostics and chemical health management (CHM) technique was developed, for quantifying and characterizing health status of a CL-01 composite solid rocket propellant of tactical rocket motors. The technique is a cutting-edge real-time nondestructive technology approach which utilizes Near Infrared (NIR) spectra (M. Blanco, and I. Villarroya, 2002) emitted by microPHAZIRTM NIR miniature handheld platform, developed by Thermo Fisher Scientific. Benchtop high-performance liquid chromatography (HPLC) and ion chromatography (IC) were utilized as baseline reference techniques for correlation to TM microPHAZIR NIR measurements.To build a quantitative calibration model, near infrared spectra were acquired for twenty freshly manufactured mixes of CL-01 propellant formulae, which were iterated using a D-Optimal full-factorial design of experiment (DOE). Four-hundred eighty measurements were recorded and analyzed using Partial Least Squares (PLS) regression analysis for model building and method development (Schreyer, 2012). NIR results were correlated to spectra, which were produced using HPLC and IC reference techniques and were determined to be in precise agreement. All recorded measurements that were performed using microPHAZIRTM handheld platform were successfully validated with HPLC and IC measurements. An algorithm was developed for microPHAZIRTM NIR thus qualifying the platform as a real-time nondestructive test (NDT)/ nondestructive evaluation (NDE) tool for quantification of primary chemical constituents of CL-01 composite solid rocket propellant. Primary chemical constituents of CL-01 comprise a binder, oxidizer, plasticiser, and antioxidant/stabilizer.Data sets for Shore-A hardness of each of the twenty DOE mixes were collected and used to calculate elastic modulus, tensile strength and percent strain. Calculated results conformed to specification requirements for CL-01 solid rocket propellant, henceforth confirming use of Shore A hardness as a real-time nondestructive test technique for validation of structural health of a solid rocket propellant. This teaming effort between Raytheon Missile Systems (RMS), United Kingdom Ministry of Defence (UK MoD), Alliant Techsystems Launch systems (ATK LS), and Thermo Fisher Scientific demonstrated outstanding ability to utilize miniature cutting-edge technology to perform real- time NDT of CL-01 composite solid rocket propellant without generating chemical waste and residue and to ameliorate RMS technology base to capture incipient failures before the fact. The new technique will further be adapted for use to measure primary chemical constituents of other solid rocket propellants, liquid propellants, and composite explosives. The new technique will significantly reduce costs associated with surveillance and service life extension programs (SLEPs), which are often destructive and requires use of lengthy and expensive test techniques described in North Atlantic Treaty Organization (NATO) Standardization Agreement (ST ANAG)-4170 and Allied Ordnance Publication (AOP)-7 manuals.
 
 
 
 
 

High-fidelity Modeling of Local Effects of Damage for Derated Offshore Wind Turbines

Offshore wind power production is an attractive clean energy option, but the difficulty of access can lead to expensive and rare opportunities for maintenance. As part of the Structural Health and Prognostics Management (SHPM) project at Sandia National Laboratories, smart loads management (controls) are investigated for their potential to increase the fatigue life of offshore wind turbine rotor blades. Derating refers to altering the rotor angular speed and blade pitch to limit power production and loads on the rotor blades. High- fidelity analysis techniques like 3D finite element modeling (FEM) should be used alongside beam models of wind turbine blades to characterize these control strategies in terms of their effect to mitigate fatigue damage and extend life of turbine blades. This study will consider a commonly encountered damage type for wind turbine blades, the trailing edge disbond, and show how FEM can be used to quantify the effect of operations and control strategies designed to extend the fatigue life of damaged blades. The Virtual Crack Closure Technique (VCCT) will be used to post-process the displacement and stress results to provide estimates of damage severity/criticality and provide a means to estimate the fatigue life under a given operations and control strategy.

Special Issue: International Conference on Advances in Structural Health Management and Composite Structures (ASHMCS 2012)

Special Issue: International Conference on Advances in Structural Health Management and Composite Structures (ASHMCS 2012)

Advances in Structural Health Management and Composite Structures 2012

1 School of Mechanical Engineering, Chonnam National University, Gwangju, Republic of Korea 2Department of Aerospace Engineering and Department of Mechatronics Engineering and LANL-CBNU Engineering Institute Korea, Chonbuk National University, Jeonju, Chonbuk, Republic of Korea 3 Aeronautical Technology Directorate (7-2), Aircraft System R&D Institute, Agency for Defense Development, Daejeon, Republic of Korea

Guided Wave Damage Characterization via Minimum Variance Imaging with a Distributed Array of Ultrasonic Sensors

Guided wave imaging with a distributed array of inexpensive transducers offers a fast and cost-efficient means for damage detection and localization in plate-like structures such as aircraft and spacecraft skins. As such, this technology is a natural choice for inclusion in condition-based maintenance and integrated structural health management programs. One of the implementation challenges results from the complex interaction of propagating ultrasonic waves with both the interrogation structure and potential defects or damage. For example, a guided ultrasonic wave interacts with a surface or sub-surface defect differently depending on the angle of incidence, defect size and orientation, excitation frequency, and guided wave mode. However, this complex interaction also provides a mechanism for guided wave imaging algorithms to perform damage characterization in addition to damage detection and localization. Damage characterization provides a mechanism to help discriminate actual damage (e.g. fatigue cracks) from benign changes, and can be used with crack propagation models to estimate remaining life. This work proposes the use of minimum variance imaging to perform damage detection, localization, and characterization. Scattering assumptions used to perform damage characterization are obtained through both analytical and finite element models. Experimental data from an in situ distributed array are used to demonstrate feasibility of this approach using a through-hole and two through-thickness notches of different orientations to simulate damage in an aluminum plate.

International Conference on Advances in Structural Health Management and Composite Structures – ASHMCS 2012

International Conference on Advances in Structural Health Management and Composite Structures – ASHMCS 2012

Structural health and prognostics management for the enhancement of offshore wind turbine operations and maintenance strategies

ABSTRACTOffshore wind turbines are an attractive source for clean and renewable energy for reasons including their proximity to population centers and higher capacity factors. One obstacle to the more widespread installation of offshore wind turbines in the USA, however, is that recent projections of offshore operations and maintenance costs vary from two to five times the land‐based costs. One way in which these costs could be reduced is through use of a structural health and prognostics management (SHPM) system as part of a condition‐based maintenance paradigm with smart loads management. This paper contributes to the development of such strategies by developing an initial roadmap for SHPM, with application to the blades. One of the key elements of the approach is a multiscale simulation approach developed to identify how the underlying physics of the system are affected by the presence of damage and how these changes manifest themselves in the operational response of a full turbine. A case study of a trailing edge disbond is analysed to demonstrate the multiscale sensitivity of damage approach and to show the potential life extension and increased energy capture that can be achieved using simple changes in the overall turbine control and loads management strategy. The integration of health monitoring information, economic considerations such as repair costs versus state of health, and a smart loads management methodology provides an initial roadmap for reducing operations and maintenance costs for offshore wind farms while increasing turbine availability and overall profit. Copyright © 2013 John Wiley & Sons, Ltd.

On the Integration of Real-Time Diagnosis and Prognosis for Scheduled Maintenance Optimization

Helicopters are very critical aircrafts from the point of view of fatigue loads. A structural damage could grow fast to critical size because of the wide range of manoeuvre loads. As a consequence, scheduled maintenance is a major cost during the operative life of the aircraft. The most advanced methodologies for Structural Health Monitoring and Prognostic Health Management available today are aimed to provide a real-time structural diagnosis, thus maximizing the availability of the helicopter and reducing the maintenance costs. However, on-board diagnostic systems might be gradually introduced in the current maintenance procedures, trying to minimize the risk associated to these newly developed technologies. The work presented inside this paper is about the simulation of the integration of real-time diagnosis and prognosis into a typical scheduled maintenance procedure. A diagnostic unit is capable for anomaly detection and damage quantification (in terms of crack length). It is trained with Finite Element simulated damages and tested with real experimental data. The diagnostic output is then processed in a particle filter algorithm, based on sequential importance sampling technique, aimed at refining the estimation of the structural condition as well as to update the inference on the residual useful life distribution. The coupling of real-time diagnosis with off-line measures (taken during scheduled maintenance stops) is analyzed and applied to a damage tolerant structure, trying to outline the advantages and drawbacks of the proposed approach.

Repeat scanning technology for laser ultrasonic propagation imaging

Laser ultrasonic scanning in combination with contact or non-contact sensors provides new paradigms in structural health management (SHM) and non-destructive in-process quality control (IPQC) for large composite structures. Wave propagation imaging technology based on laser ultrasonic scanning and fixed-point sensing shows remarkable advantages, such as minimal need for embedded sensors in SHM, minimum invasive defect visualization in IPQC and general capabilities of curved and complex target inspection, and temporal reference-free inspection. However, as with other SHM methods and non-destructive evaluation based on ultrasound, the signal-to-noise ratio (SNR) is a prevalent issue in real structural applications, especially with non-contact thin-composite sensing or with thick and heterogeneous composites. This study proposes a high-speed repeat scanning technique for laser ultrasonic propagation imaging (UPI) technology, which is realized with the scanning speed of 1 kHz of a Q-switched continuous wave laser, and precise control of the laser beam pulses for identical point scanning. As a result, the technique enables the achievement of significant improvement in the SNR to inspect real-world composite structures. The proposed technique provides enhanced results for impact damage detection in a 2 mm thick wing box made of carbon-fiber-reinforced plastic, despite the low sensitivity of non-contact laser ultrasonic sensing. A field-applicable pure laser UPI system has been developed using a laser Doppler vibrometer as the non-contact ultrasonic sensor. The proposed technique enables the visualization of the disbond defect in a 15 mm thick wind blade specimen made of glass-fiber-reinforced plastic, despite the high dissipation of ultrasound in the thick composite.

Quantitative methods for structural health management using in situ acoustic emission monitoring

This paper presents an end-to-end approach for structural health management using acoustic emission (AE) monitoring. Three quantitative methods are proposed to utilize the information obtained from in situ AE monitoring to improve structural integrity assessment. Fatigue crack growth tests with real-time acoustic emissions monitoring are conducted on CT specimens made of 7075-T6 aluminum. Proper filtration of the resulting AE signals reveals a log-linear relationship between fracture parameters (e.g. crack growth rate) and select AE features; a flexible statistical model is developed to describe the relationship between these parameters. Bayesian inference is used to estimate the model parameters from experimental data. The model is then used to calculate two important quantities that can be used for structural health management: (a) an AE-based instantaneous damage severity index, and (b) an AE-based estimate of the crack size distribution at a given point in time, assuming a known initial crack size distribution. Finally, recursive Bayesian estimation is used for online integration of the structural health assessment information obtained from AE monitoring, with crack size estimates obtained from empirical crack growth model. The data used in Bayesian updating includes observed crack sizes and/or crack growth rate observations.

A recursive Bayesian framework for structural health management using online monitoring and periodic inspections

The necessary information for developing a structural health diagnostic and prognostic solution is often obtained from various sources. This paper presents a Bayesian framework for online integration of the structural health assessment information obtained from empirical crack growth models, structural health monitoring and periodic inspections. The data used in Bayesian updating could be direct damage observations (e.g., observed crack sizes) and/or damage growth rate estimates (e.g., crack growth rate observations). An AE-based monitoring approach is used to obtain the crack growth rate observations in this paper. The outcome of this approach is updated crack size distribution as well as updated parameters for an empirical crack growth model. The model with updated parameters is used for prognosis given an assumed future usage profile.

Real-Time Corrosion Monitoring of Aircraft Structures with Prognostic Applications

This paper presents the theory and experimental validation of a Structural Health Management (SHM) system for monitoring corrosion. Corrosion measurements are acquired using a micro-sized Linear Polarization Resistance (μLPR) sensor. The μLPR sensor is based on conventional macro-sized Linear Polarization Resistance (LPR) sensors with the additional benefit of a reduced form factor making it a viable and economical candidate for remote corrosion monitoring of high value structures, such as buildings, bridges, or aircraft.A series of experiments were conducted to evaluate the μLPR sensor for AA 7075-T6, a common alloy used in aircraft structures. Twelve corrosion coupons were placed alongside twenty-four μLPR sensors in a series of accelerated tests. LPR measurements were sampled once per minute and converted to a corrosion rate using the algorithms presented in this paper. At the end of the experiment, pit-depth due to corrosion was computed from each μLPR sensor and compared with the control coupons.The paper concludes with a feasibility study for the μLPR sensor in prognostic applications. Simultaneous evaluation of twenty-four μLPR sensors provided a stochastic data set appropriate for prognostics. RUL estimates were computed a-posteriori for three separate failure thresholds. The results demonstrate the effectiveness of the sensor as an efficient and practical approach to measuring pit-depth for aircraft structures, such as AA 7075-T6, and provide feasibility for its use in prognostic applications.

A probabilistic approach for estimating defect size and density considering detection uncertainties and measurement errors

Every structural component has some form and amount of hidden defects, however small it might be. These defects should be detected and characterized in order to ensure reliability of safety-critical structures. Test equipment is often used to inspect and gather data from probable defect sites in structural components during in-service inspections for maintenance purposes. This data is then analyzed and processed to measure the defect size and density. In-service inspection data may be highly uncertain in nature owing to detection uncertainties and measurement errors typically associated with the testing and evaluation process. These uncertainties and errors, if not properly accounted for, can result in defect size and density estimates not representative of the true state of degradations. In this article we first provide a description of the detection uncertainties and measurement errors in the context of nondestructive testing and evaluation. We then propose a Bayesian approach that updates prior knowledge of defect size and density with uncertain nondestructive evaluation data, accounting for detection uncertainties, measurement errors, and other associated uncertainties, to infer the posterior estimates of true size and number of defects. An example application of the proposed approach is then presented for estimating true defect size and density in nuclear reactor piping welds using ultrasonic evaluation data. The Bayesian approach presented in this article fills a critical gap in health management and reliability prognosis of structures, thereby enhancing the overall structural safety and operability.

Theoretical and Experimental Evaluation of a Real-Time Corrosion Monitoring System for Measuring Pitting in Aircraft Structures

This paper presents the theory and experimental validation of Analatom’s Structural Health Management (SHM) system for monitoring corrosion. Corrosion measurements are acquired using a micro-sized Linear Polarization Resistance (uLPR) sensor. The uLPR sensor is based on conventional macrosized Linear Polarization Resistance (LPR) sensors with the additional benefit of a reduced form factor making it a viable and economical candidate for remote corrosion monitoring of high value structures, such as buildings, bridges, or aircraft. A series of experiments were conducted to evaluate the uLPR sensor for AA 7075-T6. Test coupons were placed alongside Analatom’s uLPR sensors in a series of accelerated tests. LPR measurements were sampled at a rate of once per minute and converted to a corrosion rate using the algorithms presented in this paper. At the end of the experiment, pitdepth due to corrosion was computed for each sensor from the recorded LPR measurements and compared to the average pit-depth measured on the control coupons. The results demonstrate the effectiveness of the sensor as an efficient and practical approach to measuring pit-depth for AA 7075-T6.

Structural health monitoring of fatigue crack growth in plate structures with ultrasonic guided waves

Fatigue crack growth in plate structures is monitored with ultrasonic guided waves generated from piezoelectric transducers. Cracks initiate in the vicinity of fastener holes due to cyclic in-plane loading. Ultrasonic guided waves that are partially obstructed by the fastener holes are investigated. Since fatigue crack growth increases the obstruction, these waves are effective for monitoring fatigue crack growth in a pitch-catch mode. The transmission coefficient (TC), which is defined essentially as the current-to-baseline amplitude ratio, and the transmission coefficient ratio (TCR), which is based on amplitude ratios from a single wave, are signal features used for crack characterization. The TCR is well suited for structural health monitoring. The excellent agreement between experimental results and finite element analysis of wave propagation corroborates the experiments. A sparse array of transducers is shown to effectively monitor a multifastener joint. The approach using obstructed ultrasonic guided waves has strong potential for prognostics-based structural health management due to the linear relationship between crack size and the TC.

Experimental Investigations on Effect of Damage on Vibration Characteristics of a Reinforced Concrete Beam

Need for developing efficient non-destructive damage assessment procedures for civil engineering structures is growing rapidly towards structural health assessment and management of existing structures. Damage assessment of structures by monitoring changes in the dynamic properties or response of the structure has received considerable attention in recent years. In the present study, damage assessment studies have been carried out on a reinforced concrete beam by evaluating the changes in vibration characteristics with the changes in damage levels. Structural damage is introduced by static load applied through a hydraulic jack. After each stage of damage, vibration testing is performed and system parameters were evaluated from the measured acceleration and displacement responses. Reduction in fundamental frequencies in first three modes is observed for different levels of damage. It is found that a consistent decrease in fundamental frequency with increase in damage magnitude is noted. The beam is numerically simulated and found that the vibration characteristics obtained from the measured data are in close agreement with the numerical data.

Structural Integrity Assessment Using In-Situ Acoustic Emission Monitoring

The work presented in this paper is focused on monitoring fatigue crack growth in metallic structures using acoustic emission (AE) technology. Three different methods are proposed to utilize the information obtained from in-situ monitoring for structural health management. Fatigue crack growth tests with real-time acoustic emissions monitoring are conducted on CT specimens made of 7075 aluminum. Proper filtration of the resulting AE signals reveals a log-linear relationship between fracture parameters ( da⁄dN and ΔK ) and select AE features; a flexible statistical model is developed to describe the relationship between these parameters.Bayesian inference is used to estimate the model parameters from experimental data. The model is then used to calculate two important quantities that can be used for structural health management: (a) an AE-based instantaneous damage severity index, and (b) an AE-based estimate of the crack size distribution at a given point in time, assuming a known initial crack size distribution. Finally, recursive Bayesian estimation is used for online integration of the structural health assessment information obtained from AE monitoring with crack size estimates obtained from empirical crack growth model. The evidence used in Bayesian updating includes observed crack sizes and/or crack growth rate observations

Laser ultrasonic anomalous wave propagation imaging method with adjacent wave subtraction: Application to actual damages in composite wing

Laser ultrasonic wave propagation imaging methods have great potential for integrated structural health management and non-destructive evaluation. However, application of these techniques to complex structures in the field is difficult because they give rise to complicated wave propagation patterns. We developed an anomalous wave propagation imaging method with adjacent wave subtraction using laser ultrasonic scanning to solve this problem. The proposed method is suitable for non-destructive evaluation of complex structures because it highlights the propagation of anomalous waves related to structural discontinuities, and suppresses complex incident waves without the need of pre-stored reference data. In this study, the method was applied to a real composite wing subjected to bending and impact tests. The method enhanced the visibility of the anomalous waves related to damages such as stringer tip debonding, skin-spar debonding, and invisible impact damage. Based on these anomalous waves, variable time window amplitude mapping was performed to show the damage location, size, and shape resemble to the actual damage. Comparisons showed that the methods performed better than the ultrasonic A-scan in terms of damage detection and sizing accuracy. The presence of structural elements such as spars, stringers, ribs, and surface-mounted PZT elements did not adversely affect the inspection. The proposed wing test setup with a built-in ultrasonic propagation imaging system for automatic NDE could be easily expanded throughout a hanger for maintenance inspection.

Analysis of Aircraft Composite Structural Health Monitoring and Life Prediction Technology

Along with the constantly updated aircraft structure design, higher performance and reliability design indexes as well as usage of a large portion of new materials especially lightweight composite materials put forward higher requirements for aircraft structure safety. The damage detection, diagnosis, forecast and management become an important part of aircraft Prognostics and Health Management(PHM).In order to better build the Structural Prognostics and Health Management system of a new generation aircraft for the improvement of security, task reliability and economy, this paper introduced the development situation of aircraft composite structural health monitoring and life prediction technologies, classified the existing technologies, and then discussed the principle, quality point, applicability and application situation, finally, pointed out several critical issues which still need further study.