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.
Structural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring
Reliable structural health monitoring (SHM) systems can automatically process data, assess structural condition and signal the need for human intervention. There is a significant need for formal SHM technology validation and quantitative performance assessment processes to uniformly and comprehensively support the evolution and adoption of SHM systems. In recent years, the SHM community has made significant advances in its efforts to evolve statistical methods for analyzing data from in-situ sensors. Several statistical approaches have been demonstrated using real data from multiple SHM technologies to produce Probability of Detection (POD) performance measures. Furthermore, limited comparisons of these methods - utilizing different simplification assumptions and data types - have shown them to produce similar POD values. Given these encouraging results, it is important to understand the circumstances under which the data was acquired. Thus far, the statistical analyses have assumed the viability of the data outright and focused on the performance quantification process once acceptable data has been compiled. This paper will address the array of parameters that must be considered when conducting tests to acquire representative SHM data. For some SHM applications, it may not be possible to simulate all environments in one single test. All relevant parameters must be identified and considered by properly merging results from multiple tests. Laboratory tests, for example, may have separate fatigue and environmental response components. Flight tests, which will likely not include statistically-relevant damage detection opportunities, will still play an important role in assessing overall SHM system performance under an aircraft operator's control. One statistical method, the One-Sided Tolerance Interval (OSTI) approach, will be discussed along with the test methods used to acquire the data. Finally, prospects for streamlining the deployment of SHM solutions will be considered by comparing SHM data needs during what is now an introductory phase of SHM usage with future data needs after a substantial database of SHM data and usage history has been compiled.
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. The use of in-situ sensors for real-time health monitoring of aircraft structures, coupled with remote interrogation, provides 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 (SHM) 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 can detect incipient damage before catastrophic failures occurs. 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 paper presents the results from successful SHM technology validation efforts that established the performance of sensor systems for aircraft fatigue crack detection. 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, and the potential inspector population. All factors that affect SHM sensitivity were included in this program including flaw size, shape, orientation and location relative to the sensors, operational and environmental variables and issues related to the presence of multiple flaws within a sensor network. This paper will also present the formal certification tasks including formal adoption of SHM systems into aircraft manuals and the release of an Alternate Means of Compliance and a modified Service Bulletin to allow for routine use of SHM sensors on commercial aircraft. This program also established a regulatory approval process that includes FAR Part 25 (Transport Category Aircraft) and shows compliance with 25.571 (fatigue) and 25.1529 (Instructions for Continued Airworthiness).
Wind turbine blades pose a unique set of inspection challenges that span from very thick and attentive spar cap structures to porous bond lines, varying core material and a multitude of manufacturing defects of interest. The need for viable, accurate nondestructive inspection (NDI) technology becomes more important as the cost per blade, and lost revenue from downtime, grows. NDI methods must not only be able to contend with the challenges associated with inspecting extremely thick composite laminates and subsurface bond lines, but must also address new inspection requirements stemming from the growing understanding of blade structural aging phenomena. Under its Blade Reliability Collaborative program, Sandia Labs quantitatively assessed the performance of a wide range of NDI methods that are candidates for wind blade inspections. Custom wind turbine blade test specimens, containing engineered defects, were used to determine critical aspects of NDI performance including sensitivity, accuracy, repeatability, speed of inspection coverage, and ease of equipment deployment. The detection of fabrication defects helps enhance plant reliability and increase blade life while improved inspection of operating blades can result in efficient blade maintenance, facilitate repairs before critical damage levels are reached and minimize turbine downtime. The Sandia Wind Blade Flaw Detection Experiment was completed to evaluate different NDI methods that have demonstrated promise for interrogating wind blades for manufacturing flaws or in-service damage. These tests provided the Probability of Detection information needed to generate industry-wide performance curves that quantify: 1) how well current inspection techniques are able to reliably find flaws in wind turbine blades (industry baseline) and 2) the degree of improvements possible through integrating more advanced NDI techniques and procedures. _____________ S a n d i a N a t i o n a l L a b o r a t o r i e s i s a m u l t i m i s s i o n l a b o r a t o r y m a n a g e d a n d o p e r a t e d b y N a t i o n a l T e c h n o l o g y a n d E n g i n e e r i n g S o l u t i o n s o f S a n d i a , L L C , a w h o l l y o w n e d s u b s i d i a r y o f H o n e y w e l l I n t e r n a t i o n a l , I n c . , f o r t h e U . S . D e p a r t m e n t o f E n e r g y ' s N a t i o n a l N u c l e a r S e c u r i t y A d m i n i s t r a t i o n u n d e r c o n t r a c t D E - N A 0 0 0 3 5 2 5 .
Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance - Proceedings of the 11th International Workshop on Structural Health Monitoring, IWSHM 2017
The use of in-situ sensors for real-time health monitoring of a wide array of civil structures can be a viable option to overcome inspection impediments stemming from accessibility limitations, complex geometries, and the location and depth of hidden damage. The maturity of Structural Health Monitoring (SHM) sensors has evolved to the point where many networks have demonstrated sensitivities that meet or exceed current damage detection requirements. As a result, there is a growing need for well-defined methods to statistically quantify the performance of sensors and sensor networks. Statistical methods can be applied to laboratory and flight test data to derive Probability of Detection (POD) values for SHM sensors in a fashion that agrees with current nondestructive inspection (NDI) validation requirements. However, while there are many agreed-upon procedures for quantifying the performance of NDI techniques, there are no guidelines for assessing SHM systems. While the intended function of the SHM and NDI systems may be very similar, there are distinct differences in the parameters that affect their performance and differences in their implementation that require special consideration. Factors that affect SHM sensitivity include flaw size, shape, orientation and location relative to the sensors, operational and environmental variables and issues related to the presence of multiple flaws within a sensor network. The FAA Airworthiness Assurance NDI Validation Center (AANC) at Sandia Labs, in conjunction with the FAA WJH Technical Center, has conducted a series of SHM validation and certification programs aimed at establishing the overall viability of SHM systems and producing appropriate precedents and guidelines for the safe adoption of SHM solutions for aircraft maintenance. This paper will present 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 discuss how they can converge to produce a confident quantification of SHM performance. Comparisons of hit-miss, a versus ?, and One Sided Tolerance Intervals will provide valuable insights into how the characteristics of the collected SHM data affect the formulation of that system's POD curve. Similarities between NDI and SHM assessments will be highlighted in order to provide a foundation in traditional flaw detection performance measures. In addition, considerations of the controlling factors to be considered when collecting SHM response data will be discussed.
Composite structures are increasing in prevalence throughout the aerospace, wind, defense, and transportation industries, but the many advantages of these materials come with unique challenges, particularly in inspecting and repairing these structures. Because composites of- ten undergo sub-surface damage mechanisms which compromise the structure without a clear visual indication, inspection of these components is critical to safely deploying composite re- placements to traditionally metallic structures. Impact damage to composites presents one of the most signi fi cant challenges because the area which is vulnerable to impact damage is generally large and sometimes very dif fi cult to access. This work seeks to further evolve iden- ti fi cation technology by developing a system which can detect the impact load location and magnitude in real time, while giving an assessment of the con fi dence in that estimate. Fur- thermore, we identify ways by which impact damage could be more effectively identi fi ed by leveraging impact load identi fi cation information to better characterize damage. The impact load identi fi cation algorithm was applied to a commercial scale wind turbine blade, and results show the capability to detect impact magnitude and location using a single accelerometer, re- gardless of sensor location. A technique for better evaluating the uncertainty of the impact estimates was developed by quantifying how well the impact force estimate meets the assump- tions underlying the force estimation technique. This uncertainty quanti fi cation technique was found to reduce the 95% con fi dence interval by more than a factor of two for impact force estimates showing the least uncertainty, and widening the 95% con fi dence interval by a fac- tor of two for the most uncertain force estimates, avoiding the possibility of understating the uncertainty associated with these estimates. Linear vibration based damage detection tech- niques were investigated in the context of structural stiffness reductions and impact damage. A method by which the sensitivity to damage could be increased for simple structures was presented, and the challenges of applying that technique to a more complex structure were identi fi ed. The structural dynamic changes in a weak adhesive bond were investigated, and the results showed promise for identifying weak bonds that show little or no static reduction in stiffness. To address these challenges in identifying highly localized impact damage, the possi- bility of detecting damage through nonlinear dynamic characteristics was also identi fi ed, with a proposed technique which would leverage impact location estimates to enable the detection of impact damage. This nonlinear damage identi fi cation concept was evaluated on a composite panel with a substructure disbond, and the results showed that the nonlinear dynamics at the damage site could be observed without a baseline healthy reference. By further developing impact load identi fi cation technology and combining load and damage estimation techniques into an integrated solution, the challenges associated with impact detection in composite struc- tures can be effectively solved, thereby reducing costs, improving safety, and enhancing the operational readiness and availability of high value assets.
Recent structural failures such as the I-35W Mississippi River Bridge in Minnesota have underscored the urgent need for improved methods and procedures for evaluating our aging transportation infrastructure. This research seeks to develop a basis for a Structural Health Monitoring (SHM) system to provide quantitative information related to the structural integrity of metallic structures to make appropriate management decisions and ensuring public safety. This research employs advanced structural analysis and nondestructive testing (NDT) methods for an accurate fatigue analysis. Metal railroad bridges in New Mexico will be the focus since many of these structures are over 100 years old and classified as fracture-critical. The term fracture-critical indicates that failure of a single component may result in complete collapse of the structure such as the one experienced by the I-35W Bridge. Failure may originate from sources such as loss of section due to corrosion or cracking caused by fatigue loading. Because standard inspection practice is primarily visual, these types of defects can go undetected due to oversight, lack of access to critical areas, or, in riveted members, hidden defects that are beneath fasteners or connection angles. Another issue is that it is difficult to determine the fatigue damage that a structure has experienced and the rate at which damage is accumulating due to uncertain history and load distribution in supporting members. A SHM system has several advantages that can overcome these limitations. SHM allows critical areas of the structure to be monitored more quantitatively under actual loading. The research needed to apply SHM to metallic structures was performed and a case study was carried out to show the potential of SHM-driven fatigue evaluation to assess the condition of critical transportation infrastructure and to guide inspectors to potential problem areas. This project combines the expertise in transportation infrastructure at New Mexico State University with the expertise at Sandia National Laboratories in the emerging field of SHM.
Airworthiness Assurance NDI Validation Center (AANC) objectives are: (1) Enhance aircraft safety and reliability; (2) Aid developing advanced aircraft designs and maintenance techniques; (3) Provide our customers with comprehensive, independent, and quantitative/qualitative evaluations of new and enhanced inspection, maintenance, and repair techniques; (4) Facilitate transferring effective technologies into the aviation industry; (5) Support FAA rulemaking process by providing guidance on content & necessary tools to meet requirements or recommendations of FARs, ADs, ACs, SBs, SSIDs, CPCP, and WFD; and (6) Coordinate with and respond to Airworthiness Assurance Working Group (AAWG) in support of FAA Aviation Rulemaking Advisory Committee (ARAC).
Goal: to detect the subtle changes in laminate composite structures brought about by thermal, chemical, ultraviolet, and moisture exposure. Compare sensitivity of an array of NDI methods, including Fourier Transform Infrared Spectroscopy (FTIR), to detect subtle differences in composite materials due to deterioration. Inspection methods applied: ultrasonic pulse echo, through transmission ultrasonics, thermography, resonance testing, mechanical impedance analysis, eddy current, low frequency bond testing & FTIR. Comparisons between the NDI methods are being used to establish the potential of FTIR to provide the necessary sensitivity to non-visible, yet significant, damage in the resin and fiber matrix of composite structures. Comparison of NDI results with short beam shear tests are being used to relate NDI sensitivity to reduction in structural performance. Chemical analyses technique, which measures the infrared intensity versus wavelength of light reflected on the surface of a structure (chemical and physical information via this signature). Advances in instrumentation have resulted in hand-held portable devices that allow for field use (few seconds per scan). Shows promise for production quality assurance and in-service applications on composite aircraft structures (scarfed repairs). Statistical analysis on frequency spectrums produced by FTIR interrogations are being used to produce an NDI technique for assessing material integrity. Conclusions are: (1) Use of NDI to assess loss of composite laminate integrity brought about by thermal, chemical, ultraviolet, and moisture exposure. (2) Degradation trends between SBS strength and exposure levels (temperature and time) have been established for different materials. (3) Various NDI methods have been applied to evaluate damage and relate this to loss of integrity - PE UT shows greatest sensitivity. (4) FTIR shows promise for damage detection and calibration to predict structural integrity (short beam shear). (5) Detection of damage for medium exposure levels (possibly resin matrix degradation only) is more difficult and requires additional study. (6) These are initial results only - program is continuing with additional heat, UV, chemical and water exposure test specimens.
The goal is to create a systematic method and structure to compile, organize, and summarize SHM related data to identify the level of maturity and rate of evolution and have a quick and ongoing evaluation of the current state of SHM among research institutions and industry. Hundreds of technical publication and conference proceedings were read and analyzed to compile the database. Microsoft Excel was used to create a useable interface that could be filtered to compare any of the entered data fields.