SEARCH · Engineering Papers

Results for “structural health monitoring”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

All sources NASA NTRS DOE OSTI

NASA NTRS2018

A Versatile Simulation Framework for Elastodynamic Modeling of Structural Health Monitoring

Structural health monitoring (SHM) has the capacity to reduce failure by detecting damage during service life, by periodic, automated monitoring. Guided Wave (GW) Ultrasound is a common SHM approach for aerospace structures. Modelling the physics of GW SHM systems provides a route for understanding system dependencies, capabilities and limitations as damage evolves during service life. Such a toolset can strengthen the understanding of the connection between GW SHM results and the true material state. The most useful modelling tools are those that provide versatile solutions with respect to the simulated component geometry and computational grid connectivity. This work details a versatile application programming interface (API) for the elastodynamic finite integration technique for modelling GW SHM of metals. The custom code implementation, EFIT-CompCell, allows for the modelling of diverse geometries by automatically balancing the message passing interface parallelization layout. The user provides the basic parameters of the simulation and the software automatically performs an initial balancing based on anticipated computational loads, and establishes the CPU communication patterns for any geometry. This work describes the programming philosophy and code structure used to create EFIT-CompCell and compares its performance and capacity to simulation tools that are more specialized for specific architectures. Results are presented for a simulation of GW SHM of an aluminum fuselage section being tested by the FAA. The simulation consists of 733M voxels which took approximately 70 hours to complete 25000 time steps using 40 Intel Xeon E5-4650v2 Ivy Bridge processor cores.

Gregory, Elizabeth D.↗

NASA NTRS2010

Acoustic Emission Measurement with Fiber Bragg Gratings for Structure Health Monitoring

Structural Health monitoring (SHM) is a way of detecting and assessing damage to large scale structures. Sensors used in SHM for aerospace structures provide real time data on new and propagating damage. One type of sensor that is typically used is an acoustic emission (AE) sensor that detects the acoustic emissions given off from a material cracking or breaking. The use of fiber Bragg grating (FBG) sensors to provide acoustic emission data for damage detection is studied. In this research, FBG sensors are used to detect acoustic emissions of a material during a tensile test. FBG sensors were placed as a strain sensor (oriented parallel to applied force) and as an AE sensor (oriented perpendicular to applied force). A traditional AE transducer was used to collect AE data to compare with the FBG data. Preliminary results show that AE with FBGs can be a viable alternative to traditional AE sensors.

Banks, Curtis E.↗

NASA NTRS2010

Acoustic Emission Measurement with Fiber Bragg Gratings for Structure Health Monitoring

Banks, Curtis E.↗

NASA NTRS2011

3D Ultrasonic Wave Simulations for Structural Health Monitoring

Structural health monitoring (SHM) for the detection of damage in aerospace materials is an important area of research at NASA. Ultrasonic guided Lamb waves are a promising SHM damage detection technique since the waves can propagate long distances. For complicated flaw geometries experimental signals can be difficult to interpret. High performance computing can now handle full 3-dimensional (3D) simulations of elastic wave propagation in materials. We have developed and implemented parallel 3D elastodynamic finite integration technique (3D EFIT) code to investigate ultrasound scattering from flaws in materials. EFIT results have been compared to experimental data and the simulations provide unique insight into details of the wave behavior. This type of insight is useful for developing optimized experimental SHM techniques. 3D EFIT can also be expanded to model wave propagation and scattering in anisotropic composite materials.

Campbell, Leckey Cara A/↗

DOE OSTI2014

A vibro-haptic human-machine interface for structural health monitoring

The structural health monitoring (SHM) community’s goal has been to endow physical systems with a nervous system not unlike those commonly found in living organisms. Typically the SHM community has attempted to do this by instrumenting structures with a variety of sensors, and then applying various signal processing and classification procedures to the data in order to detect the presence of damage, the location of damage, the severity of damage, and to estimate the remaining useful life of the structure. This procedure has had some success, but we are still a long way from achieving the performance of nervous systems found in biology. This is primarily because contemporary classification algorithms do not have the performance required. In many cases expert judgment is superior to automated classification. This work introduces a new paradigm. We propose interfacing the human nervous system to the distributed sensor network located on the structure and developing new techniques to enable human-machine cooperation. Results from the field of sensory substitution suggest this should be possible. This study investigates a vibro-haptic human-machine interface for SHM. The investigation was performed using a surrogate three-story structure. The structure features three nonlinearity-inducing bumpers to simulate damage. Accelerometers are placed on each floor to measure the response of the structure to a harmonic base excitation. The accelerometer measurements are preprocessed. As a result, the preprocessed data is then encoded encoded as a vibro-tactile stimulus. Human subjects were then subjected to the vibro-tactile stimulus and asked to characterize the damage in the structure.

42 ENGINEERING↗

DOE OSTI2020

Application and Certification of Comparative Vacuum Monitoring Sensors for Structural Health Monitoring of 737 Wing Box Fittings

Multi-site fatigue damage, hidden cracks in hard-to-reach locations, disbonded joints, erosion, impact, and corrosion are among the major flaws encountered in today's extensive fleet of aging aircraft and space vehicles. The use of in-situ sensors for real-time health monitoring of aircraft structures are a viable option to overcome inspection impediments stemming from accessibility limitations, complex geometries, and the location and depth of hidden damage. Reliable, structural health monitoring systems can automatically process data, assess structural condition, and signal the need for human intervention. Prevention of unexpected flaw growth and structural failure can be improved if on-board health monitoring systems are used to continuously assess structural integrity. Such systems are able to detect incipient damage before catastrophic failures occurs. Condition-based maintenance practices could be substituted for the current time-based maintenance approach. Other advantages of on-board distributed sensor systems are that they can eliminate costly, and potentially damaging, disassembly, improve sensitivity by producing optimum placement of sensors and decrease maintenance costs by eliminating more time- consuming manual inspections. This report presents a Sandia Labs-aviation industry effort to move SHM into routine use for aircraft maintenance. This program addressed formal SHM technology validation and certification issues so that the full spectrum of concerns, including design, deployment, performance and certification were appropriately considered. The Airworthiness Assurance NDI Validation Center (AANC) at Sandia Labs, in conjunction with Boeing, Delta Air Lines, Structural Monitoring Systems Ltd., Anodyne Electronics Manufacturing Corp. and the Federal Aviation Administration (FAA) carried out a certification program to formally introduce Comparative Vacuum Monitoring (CVM) as a structural health monitoring solution to a specific aircraft wing box application. Validation tasks were designed to address the SHM equipment, the health monitoring task, the resolution required, the sensor interrogation procedures, the conditions under which the monitoring will occur, the potential inspector population, adoption of CVM into an airline maintenance program and the document revisions necessary to allow for routine use of CVM as an alternate means of performing periodic structural inspects. To carry out the validation process, knowledge of aircraft maintenance practices was coupled with an unbiased, independent evaluation. Sandia Labs designed, implemented, and analyzed the results from a focused and statistically-relevant experimental effort to quantify the reliability of the CVM system applied to the Boeing 737 Wing Box fitting application. All factors that affect SHM sensitivity were included in this program: flaw size, shape, orientation and location relative to the sensors, as well as operational and environmental variables. Statistical methods were applied to performance data to derive Probability of Detection (POD) values for CVM sensors in a manner that agrees with current nondestructive inspection (NDI) validation requirements and also is acceptable to both the aviation industry and regulatory bodies. This report presents the use of several different statistical methods, some of them adapted from NDI performance assessments and some proposed to address the unique nature of damage detection via SHM systems, and discusses how they can converge to produce a confident quantification of SHM performance An important element in developing SHM validation processes is a clear understanding of the regulatory measures needed to adopt SHM solutions along with the knowledge of the structural and maintenance characteristics that may impact the operational performance of an SHM system. This report describes the major elements of an SHM validation approach and differentiates the SHM elements from those found in NDI validation. The activities conducted in this program demonstrated the feasibility of routine SHM usage in general and CVM in particular for the application selected. They also helped establish an optimum OEM-airline-regulator process and determined how to safely adopt SHM solutions. This formal SHM validation will allow aircraft manufacturers and airlines to confidently make informed decisions about the proper utilization of CVM technology. It will also streamline the regulatory actions and formal certification measures needed to assure the safe application of SHM solutions.

42 ENGINEERING↗

DOE OSTI2024

In-Process Monitoring and Structural Health Monitoring of Large-Scale Additive Manufacturing Using Acoustic Emission Technique

ORNL collaborated with MISTRAS Group, Inc. to investigate acoustic emission (AE) as a structural health monitoring (SHM) method for large-scale additive manufacturing (AM). Large-scale AM is being adapted as method of producing large structures in a short lead time and cost-effective way. With the growing advancement in AM techniques and application, machine monitoring and part qualification is highly needed. There has been leading research focused on the manufacturing, feedstock material but minimum research on the SHM, defect detection, and nondestructive evaluation (NDE) for AM. Scanning large structure using conventional nondestructive testing (NDT) techniques, such as ultrasound or X-ray, and searching for potential defects can be very time consuming, challenging and cost prohibitive. AE is a passive technique that can be used to monitor and locate defect progression in large structure by distributing group of sensors around the part. This project utilized AE technique and system manufactured/designed by MISTRAS Group to monitor large-scale AM equipment (i.e. Big Area Additive Manufacturing (BAAM) system located at the Oak Ridge National Laboratory – Manufacturing Demonstration Facility (ORNL-MDF) and the printed parts it produces. The AE system provided valuable insight on defect development/progression during and post-printing process.

36 MATERIALS SCIENCE↗

NASA NTRS2005

Piezoelectric Sensor Evaluation for Structural Health Monitoring of Cryogenic Structures

This viewgraph presentation provides an overview of Structural Health Monitoring (SHM), and profiles piezoelectric sensors useful for SHM of cryogenic structures. The presentation also profiles impedance tests and other SHM tests conducted at Marshall Space Flight Center (MSFC).

Lassiter, John↗

DOE OSTI2016

Structural health monitoring of engineered structures using a space-borne synthetic aperture radar multi-temporal approach: from cultural heritage sites to war zones

Typically, structural health monitoring (SHM) of engineered structures consists of an automated or semi-automated survey system that seeks to assess the structural condition of an anthropogenic structure. The aim of an SHM system is to provide insights into possible induced damage or any inherent signals of deformation affecting the structure in terms of detection, localization, assessment, and prediction. During the last decade there has been a growing interest in using several remote sensing techniques, such as synthetic aperture radar (SAR), for SHM. Constellations of SAR satellites with short repeat time acquisitions permit detailed surveys temporal resolution and millimetric sensitivity to deformation that are at the scales relevant to monitoring large structures. The all-weather multi-temporal characteristics of SAR make its products suitable for SHM systems, especially in areas where in situ measurements are not feasible or not cost effective. To illustrate this capability, we present results from COSMO-SkyMed (CSK) and TerraSAR-X SAR observations applied to the remote sensing of engineered structures. We show how by using multiple-geometry SAR-based products which exploit both phase and amplitude of the SAR signal we can address the main objectives of an SHM system including detection and localization. We highlight that, when external data such as rain or temperature records are available or simple elastic models can be assumed, the SAR-based SHM capability can also provide an interpretation in terms of assessment and prediction. We highlight examples of the potential for such imaging capabilities to enable advances in SHM from space, focusing on dams and cultural heritage areas.

47 OTHER INSTRUMENTATION↗

NASA NTRSDate not supplied

Structural Health Monitoring of Vertical Lift Structures Operating in an Urban Environment

Verifying the structural integrity of aeronautical vehicles is of critical importance for the safety of passengers and crew. When operating in a densely populated urban area, pedestrian safety and collateral damage to buildings and other infrastructure also become important concerns. Damage modes, including fatigue from an increased frequency of take-off and landing cycles and a higher probability of impacts from bird strikes, also pose different failure risks as compared to commercial long-haul aircraft and thus require a change in structural health monitoring philosophy. This presentation will review the state of the art in structural health monitoring with an eye toward applications for vertical lift systems operated in the urban environment. Structural health monitoring methods including eddy current, fiber optic, ultrasonic plate wave, surface acoustic wave and electrical impedance tomography will be explored for use in on-board monitoring of impact and overstrain events as well as damage detection and characterization. Infusion of the data into an early warning system to help ensure damage will not propagate to failure during flight will also be discussed.

Russell A Wincheski↗

DOE OSTI2016

Smart patch integration development of compression connector structural health monitoring in overhead transmission lines

Integration of smart patches into full-tension splice connectors in overhead power transmission lines was investigated. Lead zirconate titanate (PZT) -5A was used as a smart material and an aluminum beam was used as a host structure. Negative electrode termination was examined by using copper adhesive tape and direct bonding methods. Various commercial adhesives were studied for PZT integration onto the host structure. Aluminum beam specimens with integrated PZT smart patches were tested under thermal cycling at a temperature of 125 C, which is the higher-end temperature experienced by in-service aluminum conductor steel-reinforced cables. Electromechanical impedance (EMI) measurements were conducted at room temperature, and the root mean square deviation (RMSD) of the conductance signals was used to analyze the EMI data. It has been shown that the negative electrode method has an important effect on the performance of the integrated PZT. The PZT displayed more susceptibility to cracking when copper tape was used than when direct bonding was used. The reliability of PZT in direct bonding depended on the adhesives used in bonding layers. Although a hard alumina based adhesive can lead to cracking of the PZT, a high-temperature epoxy with adequate flexibility, such as Duralco 4538D, can provide the desired performance under target thermal cycling conditions. The RMSD parameter can characterize conductance signatures effectively. It also was demonstrated that RMSD can be used to quantify the fatigue of the PZT integration system, although RMSD is used primarily as a damage index in monitoring structural health.

compression connector↗

DOE OSTI2021

Performance Evaluation of Comparative Vacuum Monitoring and Piezoelectric Sensors for Structural Health Monitoring of Rotorcraft Components

The costs associated with the increasing maintenance and surveillance needs of aging structures are rising at an unexpected rate. Multi-site fatigue damage, hidden cracks in hard-to-reach locations, disbonded joints, erosion, impact, and corrosion are among the major flaws encountered in today’s extensive fleet of aging aircraft and space vehicles. Aircraft maintenance and repairs represent about a quarter of a commercial fleet’s operating costs. The application of Structural Health Monitoring (SHM) systems using distributed sensor networks can reduce these costs by facilitating rapid and global assessments of structural integrity. The use of in-situ sensors for real-time health monitoring can overcome inspection impediments stemming from accessibility limitations, complex geometries, and the location and depth of hidden damage. Reliable, structural health monitoring systems can automatically process data, assess structural condition, and signal the need for human intervention. The ease of monitoring an entire on-board network of distributed sensors means that structural health assessments can occur more often, allowing operators to be even more vigilant with respect to flaw onset. SHM systems also allow for condition-based maintenance practices to be substituted for the current time-based or cycle-based maintenance approach thus optimizing maintenance labor. The Federal Aviation Administration has conducted a series of SHM validation and certification programs intended to comprehensively support the evolution and adoption of SHM practices into routine aircraft maintenance practices. This report presents one of those programs involving a Sandia Labs-aviation industry effort to move SHM into routine use for aircraft maintenance. The Airworthiness Assurance NDI Validation Center (AANC) at Sandia Labs, in conjunction with Sikorsky, Structural Monitoring Systems Ltd., Anodyne Electronics Manufacturing Corp., Acellent Technologies Inc., and the Federal Aviation Administration (FAA) carried out a trial validation and certification program to evaluate Comparative Vacuum Monitoring (CVM) and Piezoelectric Transducers (PZT) as a structural health monitoring solution to specific rotorcraft applications. Validation tasks were designed to address the SHM equipment, the health monitoring task, the resolution required, the sensor interrogation procedures, the conditions under which the monitoring will occur, the potential inspector population, adoption of CVM and PZT systems into rotorcraft maintenance programs and the document revisions necessary to allow for their routine use as an alternate means of performing periodic structural inspections. This program addressed formal SHM technology validation and certification issues so that the full spectrum of concerns, including design, deployment, performance and certification were appropriately considered. Sandia Labs designed, implemented, and analyzed the results from a focused and statistically relevant experimental effort to quantify the reliability of a CVM system applied to Sikorsky S-92 fuselage frame application and a PZT system applied to an S-92 main gearbox mount beam application. The applications included both local and global damage detection assessments. All factors that affect SHM sensitivity were included in this program: flaw size, shape, orientation and location relative to the sensors, as well as operational and environmental variables. Statistical methods were applied to performance data to derive Probability of Detection (POD) values for SHM sensors in a manner that agrees with current nondestructive inspection (NDI) validation requirements and is acceptable to both the aviation industry and regulatory bodies. The validation work completed in this program demonstrated the ability of both CVM and PZT SHM systems to detect cracks in rotorcraft components. It proved the ability to use final system response parameters to provide a Green Light/Red Light (“GO” – “NO GO”) decision on the presence of damage. In additional to quantifying the performance of each SHM system for the trial applications on the S-92 platform, this study also identified specific methods that can be used to optimize damage detection, guidance on deployment scenarios that can affect performance and considerations that must be made to properly apply CVM and PZT sensors. These results support the main goal of safely integrating SHM sensors into rotorcraft maintenance programs. Additional benefits from deploying rotorcraft Health and Usage Monitoring Systems (HUMS) may be realized when structural assessment data, collected by an SHM system, is also used to detect structural damage to compliment the operational environment monitoring. The use of in-situ sensors for health monitoring of rotorcraft structures can be a viable option for both flaw detection and maintenance planning activities. This formal SHM validation will allow aircraft manufacturers and airlines to confidently make informed decisions about the proper utilization of CVM and PZT technology. It will also streamline future regulatory actions and formal certification measures needed to assure the safe application of SHM solutions.

42 ENGINEERING↗

NASA NTRSDate not supplied

Applicability of Loads Estimation Techniques Using Sparse Acceleration Sensor Data to Spacecraft Structural Health Monitoring

The use of structural health monitoring systems on spacecraft structures can play a crucial role in ensuring the safety, reliability, and longevity of the structure by gathering and analyzing onboard sensor data. Of specific importance is monitoring for excessive loading at critical interfaces as any off-nominal structural excitations experienced by spacecraft structures can cause early unpredicted high structural life consumption or damage. The availability and cost of flight-certified sensors along with the size of spacecraft structures and allowable payload mass drives the need for a method to estimate loads using sparsely-located sensors. Numerous approaches such as physics-based, statistical learning, and physics-enhanced statistical learning algorithms have gained popularity among structural prognostics applications. However, developing noise-robust prediction models to assess loads and structural life predictions from a sparse multi-sensor data acquisition system can be a challenging task. This paper discusses the evaluation of physics-based versus machine-learning algorithms for predicting loads and structural life at mission critical locations on the spacecraft structure using a finite element loads analysis with the application of simulated noise and noise reduction techniques. To estimate the loads from accelerations, the physics-based algorithm leverages a loads transformation matrix from a Craig-Bampton reduced finite element model. A System Equivalent Reduction Expansion Process (SEREP) and a pseudo-inverse approach are considered to expand from the onboard sensor degrees of freedom to the Craig-Bampton model degrees of freedom. The machine learning algorithm provides a data driven solution/mapping of the sensor accelerations to the loads at the mission critical locations using a high dimensionality analysis. Although these strategies produce comparable loads prediction without noise, the limitations of these strategies with incorporating simulated noise and noise reduction techniques with low signal to noise ratio signals are evaluated. The study demonstrates the immense potential of statistical learning algorithms for sparse structural prognostic models and enhancing signal denoising techniques. These findings also highlight the need for noise-resilient prognostic models and low-noise data acquisition systems onboard spacecraft structures.

Spacecraft Structural Health Monitoring↗

NASA NTRS1994

Structural Health Monitoring of Large Structures

This paper describes a damage detection and health monitoring method that was developed for large space structures using on-orbit modal identification. After evaluating several existing model refinement and model reduction/expansion techniques, a new approach was developed to identify the location and extent of structural damage with a limited number of measurements. A general area of structural damage is first identified and, subsequently, a specific damaged structural component is located. This approach takes advantage of two different model refinement methods (optimal-update and design sensitivity) and two different model size matching methods (model reduction and eigenvector expansion). Performance of the proposed damage detection approach was demonstrated with test data from two different laboratory truss structures. This space technology can also be applied to structural inspection of aircraft, offshore platforms, oil tankers, ridges, and buildings. In addition, its applications to model refinement will improve the design of structural systems such as automobiles and electronic packaging.

Kim, Hyoung M.↗

NASA NTRS2014

Structural Health Monitoring on Turbine Engines Using Microwave Blade Tip Clearance Sensors

The ability to monitor the structural health of the rotating components, especially in the hot sections of turbine engines, is of major interest to aero community in improving engine safety and reliability. The use of instrumentation for these applications remains very challenging. It requires sensors and techniques that are highly accurate, are able to operate in a high temperature environment, and can detect minute changes and hidden flaws before catastrophic events occur. The National Aeronautics and Space Administration (NASA) has taken a lead role in the investigation of new sensor technologies and techniques for the in situ structural health monitoring of gas turbine engines. As part of this effort, microwave sensor technology has been investigated as a means of making high temperature non-contact blade tip clearance, blade tip timing, and blade vibration measurements for use in gas turbine engines. This paper presents a summary of key results and findings obtained from the evaluation of two different types of microwave sensors that have been investigated for use possible in structural health monitoring applications. The first is a microwave blade tip clearance sensor that has been evaluated on a large scale Axial Vane Fan, a subscale Turbofan, and more recently on sub-scale turbine engine like disks. The second is a novel microwave based blade vibration sensor that was also used in parallel with the microwave blade tip clearance sensors on the experiments with the sub-scale turbine engine disks.

Gas Turbine Engines↗

NASA NTRS1990

On-orbit structural health monitoring

On-orbit structural health monitoring aboard space platforms requires the development of sensor systems for assessing impact damage from particles and debris, the effects of atomic oxygen erosion, and the integrity of power systems, storage tanks, pressure vessels, and major structural elements. The task of implementing such a smart structure diagnostic system during the initial phase of the NASA Space Station Freedom is evaluated, with a view to more complete smart structures implementation in the course of station evolution. The data processing/cataloguing task may ultimately require AI and neural networks.

Rogowski, Robert S.↗

NASA NTRS2013

Structural health monitoring system/method using electroactive polymer fibers

A method for monitoring the structural health of a structure of interest by coupling one or more electroactive polymer fibers to the structure and monitoring the electroactive responses of the polymer fiber(s). Load changes that are experienced by the structure cause changes in the baseline responses of the polymer fiber(s). A system for monitoring the structural health of the structure is also provided.

Scott-Carnell, Lisa A.↗

DOE OSTI2015

A Simple Demonstration of Concrete Structural Health Monitoring Framework

Assessment and management of aging concrete structures in nuclear power plants require a more systematic approach than simple reliance on existing code margins of safety. Structural health monitoring of concrete structures aims to understand the current health condition of a structure based on heterogeneous measurements to produce high confidence actionable information regarding structural integrity that supports operational and maintenance decisions. This ongoing research project is seeking to develop a probabilistic framework for health diagnosis and prognosis of aging concrete structures in a nuclear power plant subjected to physical, chemical, environment, and mechanical degradation. The proposed framework consists of four elements—damage modeling, monitoring, data analytics, and uncertainty quantification. This report describes a proof-of-concept example on a small concrete slab subjected to a freeze-thaw experiment that explores techniques in each of the four elements of the framework and their integration. An experimental set-up at Vanderbilt University’s Laboratory for Systems Integrity and Reliability is used to research effective combination of full-field techniques that include infrared thermography, digital image correlation, and ultrasonic measurement. The measured data are linked to the probabilistic framework: the thermography, digital image correlation data, and ultrasonic measurement data are used for Bayesian calibration of model parameters, for diagnosis of damage, and for prognosis of future damage. The proof-of-concept demonstration presented in this report highlights the significance of each element of the framework and their integration.

36 MATERIALS SCIENCE↗