Thomas M. Rice

Implementation of Structural Health Monitoring (SHM) into an Airline Maintenance Program

Delta Air Lines has partnered with Sandia National Labs, FAA, Boeing, Anodyne Electronics Manufacturing Corp. (AEM), and Structural Measurement Systems (SMS) on a novel SHM program using Comparative Vacuum Monitoring (CVM) sensors. The goal is to produce regulatory guidance that will enable widespread adoption of SHM across the commercial aviation industry. This “blueprint” is required since current regulations do not define SHM, nor validation and certification of SHM required for implementation. doi: 10.12783/SHM2015/338

Shape control of solar collectors using torsional shape memory alloy actuators

Solar collectors that are focused on a central receiver are designed with a mechanism for defocusing the collector or disabling it by turning it out of the path of the suns rays. This is required to avoid damaging the receiver during periods of inoperability. In either of these two cases a fail-safe operation is very desirable where during power outages the collector passively goes to its defocused or deactivated state. This paper will be principally concerned with focusing and defocusing the collector in a fail-safe manner using shape memory alloy actuators. Shape memory alloys are well suited to this application in that once calibrated the actuators can be operated in an on/off mode using a small amount of electric power. Also, in contrast to other smart materials that were investigated for this application, shape memory alloys are capable of providing enough stroke at the appropriate force levels to focus the collector. In order to accommodate the large, nonlinear deformations required in the solar collector plate to obtain desired focal lengths, a torsional shape memory alloy actuator was developed that produces a stroke of 0.5 inches. Design and analysis details presented, along with comparisons to test data taken from an actual prototype, demonstrate that the collector can be repeatedly focused and defocused within accuracies required by typical solar energy systems.

Development and Assessment of Advanced Inspection Methods for Wind Turbine Blades Using a Focused WINDIE Experiment.

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 Sandia Wind NDI Experiment (WINDIE) was completed to evaluate fifteen different NDI methods that have demonstrated promise for interrogating wind blades for manufacturing flaws or in-service damage. These tests provided the information needed to identify the applicability and limitations of advanced inspection methods for wind turbine blades. Ultimately, the proper combination of several inspections methods may be required to produce the best inspection sensitivity and reliability for both near-surface and deep, subsurface damage. Based on these results, phased array ultrasonics was selected for further development and introduction at blade manufacturing facilities. Hardware was developed and customized to optimize UT sensitivity and deployment to address blade inspection needs. Inspection procedures were produced and beta tested at blade production facilities. This study has identified one optimum overall NDI method while determining complimentary NDI methods that can be applied to produce a comprehensive blade inspection system. 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.

Convergence of Multiple Statistical Methods for Calculating the Probability of Detection from SHM Sensor Networks

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 ȃ, 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

Establishing the Reliability of SHM Systems Through the Extrapolation of NDI Probability of Detection Principles

Extensive Structural Health Monitoring (SHM) studies have highlighted the ability of various sensors to detect common flaws found in composite and metal structures with sensitivities that meet or exceed current damage detection requirements. Reliable SHM systems can automatically process data, assess structural condition, and signal the need for human intervention. While ad-hoc efforts to introduce SHM into routine aircraft maintenance practices are valuable in leading the way for more widespread SHM use, there is a significant need for formal SHM certification efforts to exercise and define the process of producing routine use of SHM solutions. SHM certification must address the full spectrum of issues ranging from design to performance and deployment to continued airworthiness. Currently, there are no guidelines for SHM system designers or agreed-upon procedures for quantifying the performance of SHM systems. The FAA Airworthiness Assurance Center (AANC) at Sandia Labs, in conjunction with Boeing, Delta Air Lines, Structural Monitoring Systems and Anodyne Electronic Manufacturing, is conducting a study to develop and carry out a certification process for SHM. By conducting a focused assessment of a particular aircraft application, all aspects of SHM integration are being addressed. While it is important to recognize the unique validation and verification tasks that arise from distinct differences between SHM and nondestructive inspection (NDI) deployment and flaw detection, it should be recognized that some portions of the methodology needed to determine NDI performance can be adapted to the validation of SHM systems. In this study, statistical methods were applied to laboratory and flight test data to derive Probability of Detection (POD) values for SHM sensors in a fashion that agrees with current NDI requirements. doi: 10.12783/SHM2015/330

Use of nondestructive inspection and fiber optic sensing for damage characterization in carbon fiber fuselage structure

To investigate a variety of nondestructive inspection technologies and assess impact damage characteristics in carbon fiber aircraft structure, the FAA Airworthiness Assurance Center, operated by Sandia National Labs, fabricated and impact tested two full-scale composite fuselage sections. The panels are representative of structure seen on advanced composite transport category aircraft and measured approximately 56”x76”. The structural components consisted of a 16 ply skin, co-cured hat-section stringers, fastened shear ties and frames. The material used to fabricate the panels was T800 unidirectional pre-preg (BMS 8-276) and was processed in an autoclave. Simulated hail impact testing was conducted on the panels using a high velocity gas gun with 2.4” diameter ice balls in collaboration with the University of California San Diego (UCSD). Damage was mapped onto the surface of the panels using conventional, hand deployed ultrasonic inspection techniques, as well as more advanced ultrasonic and resonance scanning techniques. In addition to the simulated hail impact testing performed on the panels, 2” diameter steel tip impacts were used to produce representative impact damage which can occur during ground maintenance operations. The extent of impact damage ranges from less than 1 in2 to 55 in2 of interply delamination in the 16 ply skin. Substructure damage on the panels includes shear tie cracking and stringer flange disbonding. It was demonstrated that the fiber optic distributed strain sensing system is capable of detecting impact damage when bonded to the backside of the fuselage.