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New structural health monitoring technologies can detect aircraft damage in real time and even predict failures

All kinds of engineering infrastructures undergo aging, and damage appears as a consequence of the loads applied to them, so inspection and maintenance actions are required to predict and lengthen their lifetime thus avoiding catastrophic failures. Due to the harsh conditions suffered by aircraft structures, periodic and scheduled inspection and maintenance tasks are essential for safe and efficient operation. The cost for the personnel needed to carry out these procedures is high, but the cost due to aircraft downtime during these time-consuming inspections is significantly greater.


Aircraft components and the composites they’re built from need to be as light as possible (while still able to carry out their role). Composite materials are defined as non-metallic non-homogeneous combinations of fibers and resins. It is mixture of two or more than two materials (reinforcement, fillers and binder) which considerably differ in physical and chemical properties, that when combined, make a material with appearances different from the individual components.


The virtues of composite structure typically include reduced weight, increased performance, and fuel economy.These components often carry high loads, and their lightweight nature mean that even small flaws can lead to failure. Failure of the structural component can have catastrophic consequences with the resultant loss of life and the aircraft. Cost and risk, especially when human life is involved, have impeded the use of advanced composites in commercial and military aircraft; however, these barriers are being overcome as both positive outcomes and user experiences increase. In general, failures occur when a component or structure is no longer able to withstand the stresses imposed on it during operation.


Michael Hoke, president of Abaris Training, a Reno, Nev.-based school for advanced composites fabrication, says delamination is a common problem in composites–like cracking is in metal–and isn’t necessarily serious.  The Federal Aviation Administration (FAA) has ordered the visual inspection of all Airbus A-300-600 and A-310 aircraft–both among the first planes to incorporate composite tails. FAA says possible warning signs include edge delamination, cracked paint, surface distortions, and other surface damage. Hoke points out that more sophisticated techniques including ultrasonic, X-ray, and thermal-imaging methods do a better job of detecting delamination than visual inspection does.


Testing for flaws is essential, but needs to be carried out in a non-destructive way, which limits the testing options. As a result, the military actively seeks new ways to carry out non-destructive testing (NDT). Researchers from the National University of Science and Technology MISiS (NUST MISiS) have recently come up with a revolutionary non-contact method for stress monitoring in polymer composites, which provides a way to not only identify but to predict the emergence of defects.


One of the most promising new methods uses smart materials. A three-ply “skin” that can sense damage and report it to operators in real time before the damage causes a problem has been developed. Conversely, it can also report when it’s still in operational condition and doesn’t need to be replaced.


University of Queensland alumnus Dr Nigel Greenwood from Evolving Machine Intelligence (EMI) developed the technology and worked with others from UQ to build real-world applications. Dr Greenwood called upon the expertise of UQ mechanical engineer Dr Ingo Jahn and his research team to apply the same artificial intelligence to aviation turbine engines and their related systems. “We’re able to use EMI’s breakthrough AI technology to predict aviation engine component degradation and plan services to improve performance,” Dr Jahn said. “It allows us to evolve computational models of aviation engines as if they were organisms and the AI can explain explicitly what it thinks is happening inside the engine.”

Structural Health Monitoring (SHM)

Hence, automation of the inspection process is a point of capital importance to reduce inspection efforts. In this context, a structural health monitoring (SHM) system can be defined as a set of devices that provides information that allows us to locate, evaluate and predict the loading and damage conditions of a structure. SHM of aircraft structures can perform real time inspection, reducing costs and improving the reliability and performance of these structures


A large number of aircraft remain in service beyond their actual operational life. Aging aircraft are subject to cracks because of fatigue and corrosive environment. With the help of structural health monitoring, it is easy to determine if any structural damage has occurred, the timing of occurrence, and the place of damage. On the basis of such critical data, decisions regarding the structures are made.


The successful application of SHM to aircraft requires two conditions: it must provide reliable and accurate information about the condition of the structure, increasing the security of critical components and avoiding disasters, and it must be a profitable process for the airline operators by reducing economic losses caused by unproductive downtimes. Therefore, there is a great interest from industry and academia in developing SHM systems that meet both conditions.


The monitoring system, which is equipped with various sensors, provides a detailed picture of the condition of an aircraft. Monitoring systems monitor and analyze the integrity of structures and capture aircraft component positioning feedback through continuously monitoring various parameters such as strain, temperature, stress, and loads.


A wide range of potential SHM technologies is being developed to fulfill these conditions, and the most promising options are: electrical strain gauges and crack wires, acoustic emission methods, optical-based technologies, comparative vacuum monitoring and MEMS. Their intrinsic capabilities, such as insensitivity to electromagnetic radiation, light weight, small size, great sensitivity and resolution, and, above all, their suitability to be embedded into structures, make optical fiber sensors (OFSs) very appropriate to perform SHM.


There are three possible approaches in order to deploy a SHM system based on optical sensors . The first one uses single-point sensors, which is the way in which most of the pressure or temperature sensors operate. The second one employs distributed sensing, where the measurand can be obtained at any point of an optical fiber. Finally, there are quasi-distributed systems that use a number of single-point sensors, allowing the sensing of large structures


Russian Researchers Find Way to Predict Plane Failures

Composites are used in many transport vehicles today. To evaluate the quality and durability of a material, the value of the internal tensile stresses of the structure — during both manufacturing and in use must be identified. In some composites, the value of internal tensile stresses after manufacturing can reach up to 95 percent of the ultimate tensile strength, which means, a slight increase in pressure will result in failure.


Carbon fiber composites, fiberglass and hybrid composites do not have this level of internal tensile stresses after manufacturing, but structural stress can build up due to working loads, the environment and the weather. This results in the deformation of the material and a decrease in load-bearing capacity.


The method developed by researchers from NUST MISiS includes monitoring the stresses using amorphous ferromagnetic microwires which are embedded between layers of carbon fiber composite to form a mesh that will be sensitive to applied stresses.


The tensile stresses in the composite material surrounding the microwires affect the way the wire material reacts to an external magnetic field. This means stress levels can be measured without direct contact, without a sensitive element: it requires no physical contact because it was embedded in the material at the required depth during manufacturing.


Other methods of stress monitoring in composite structures are often inconvenient,” explained Andrei Stepashkin, senior researcher at the NUST MISiS Center for Composite Materials.


“Non-contact methods (such as ultrasonic and acoustic testing), for example, allow us to detect existing defects only. They provide no indication of internal stresses in a material or stress distribution throughout a structure. Traditional methods for stress monitoring are contact-based, requiring physical tag attachment to a material. It turns out there are no non-contact methods for testing a material before a defect occurs, which is why we saw a need for this application.”


The authors also point out that the new method requires a single sensor — unlike other popular stress testing methods that require placing sensors on both sides of a part to be monitored. Thus, this technology makes the process of stress monitoring of composite materials much easier, faster and more efficient, allowing it to not only detect, but also predict the emergence of defects without direct contact.


Researchers have tested this technology in various modes, as well as the process for embedding the wires into a composite material and have found no negative effect on the properties of the material.


Army Sensors Can Now Detect Aircraft Damage as It Happens

For the first time ever, a team of researchers successfully developed and tested networked acoustic emission sensors that can detect airframe damage on conceptual composite UH-60 Black Hawk rotorcraft.


Researchers with the U.S. Army Research Laboratory and the U.S Army Aviation and Missile Research, Development and Engineering Center said their discovery opens up possibilities for new onboard features that could immediately alert the flight crew the state of structural damage like matrix cracking and delamination as they occur, giving the crew greater opportunity to take corrective actions before catastrophic failure.


ARL has been studying several possible alternatives to rotorcraft airframe health monitoring. This effort, which began almost two years ago, makes a strong case for integrated real-time damage sensing methodologies on future airframe structures. The sensing method can be used to reliably detect and locate the initiation and growth of damage that may occur during service.


“Future Army airframe structures are required to be lighter, safer and ultra-reliable,” said Dr. Mulugeta Haile, research aerospace engineer. “To achieve these the Army must adopt a combined strategy of implementing advanced structural design methods, improved structural materials and integrated damage sensing and risk prediction capabilities.”


He said the team turned to acoustic emission tests because other methods such as ultrasonic and radiography require an external energy source in the form of a directed wave.


“The external energy has the undesirable effect of interfering with other systems of the aircraft. In addition, other methods are not as good as AE in detecting early damage,” he said.


Acoustic emission sensors used in the distributed network are lightweight broadband piezoelectric crystals.

Acoustic emission sensing is a passive non-destructive technique for detection of damage in the very early stage and long before the structure experiences catastrophic failure. Unlike other methods, acoustic emission detects damage in real-time (or at the instant the damage is happening). The fact that AE is passive means that it does not require an external energy to detect damage. It relies on the energy that is initiated within the structure, Haile explained.


“The novelty of the current work is that we introduced several new concepts on wave acquisition control and signal processing to recover damage related information in networked acoustic emission sensors,” Haile said. “The Eureka moment was when the sensing network consistently identified and located the initiation and progression of damage during a prolonged fatigue test that lasted over 200,000 cycles. A feat that has never been achieved before.”


Currently, the Army sustains its fleet using phase maintenance paradigm, which is a periodic calendar based practice that requires inspection and maintenance at fixed time intervals. The process is highly inefficient, costly and entails extended downtime. The newly developed sensing network will enable condition based maintenance or maintenance on demand. It has the potential to drastically cut the life cycle cost of Army vehicles. The work also supports the Army’s long term vision of maintenance-free aircrafts.


Vacuum Monitoring Sensors for Aircraft

Sandia and Structural Monitoring Systems, which has a significant presence in North America, worked together with Delta Air Lines Inc. (Atlanta, Georgia, USA) and the FAA to get their team’s Comparative Vacuum Monitoring (CVM†) sensors industry certified for crack detection on commercial aircraft.


The sensors are made of thin, flexible Teflon† and have rows of little channels, called galleries. Those can be stuck onto critical joints or welds, or placed near other places where cracks are likely to form. When the metal is whole, the pump can remove the air out of the galleries, forming a vacuum. When a tiny crack forms in the metal underneath the sensor, it can no longer form a vacuum, similar to how a vacuum cleaner stops working when the hose has a leak, the researchers explain. These sensors can detect cracks smaller than the thickness of a dime.


The sensors can be produced in many different shapes, depending on the region that needs to be monitored, such as across a long weld or around a series of bolts. They can even be placed in a series in front of a tiny crack, to see whether it grows and if so, how fast. Each sensor has numerous control galleries and monitoring hardware, allowing analysts to tell if there is something wrong with the sensor or connecting tubes. Because of these control galleries, the sensors are practically foolproof, the researchers say.


Machine Learning For Stronger Military Vehicles

Levi McClenny, a doctoral candidate in the Department of Electrical and Computer Engineering at Texas A&M University, is working with Dr. Ulisses Braga-Neto on a research project using state-of-the-art machine learning tools to gain a better overall picture of what happens at the microstructure level in materials. Moreover, he is pursuing a full understanding of the fracturing process in order to predict when breakage or deterioration would occur in military vehicles and other structures and ultimately prevent this from happening in the first place.


A vehicle is comprised of many components, all of which are at individual states in their individual lifecycles,” McClenny said. “If we can get an overall system state from these component states, we can report to the driver or the pilot the overall state of his or her vehicle or aircraft in real time. The idea here is to engineer vehicles that can begin to detect their own deterioration.”


McClenny and his collaborative team are seeking to discover how certain microstructure properties relate to material properties by using images from a microscope lens to observe distortions and other inconsistencies within a material. These images could hold a wealth of information on how the materials function in the presence of some sort of stress.


The team is hoping to reverse engineer these observations, essentially trying to generate images from data, with the original images as a “roadmap.” However, these images would have specific desirable properties that the researchers can control.


“If we can generate images with the desired properties then we can potentially determine the processing parameters to generate those materials in real life,” McClenny said. “With this approach, we could generate a material with the exact specifications we desire, such as tensile strength, ductility, conductivity and more.“McClenny is utilizing machine learning and artificial intelligence to research the factors that cause materials to fracture, cracks to propagate and eventually break.


“We want to understand these microstructure interactions, modeled using machine learning approaches, to better leverage their properties for more efficient materials,” McClenny said. “Once an understanding is gained, there are numerous applications, such as ‘smart’ vehicle technology and many others.”


Smart Material Developed That ‘Feels Pain’ for U.S. Army Research Lab

Clemson University associate professor Oliver J. Myers and graduate assistant Brandon Williams have developed one in a three-ply “skin” that can sense damage and report it to operators in real time before the damage causes a problem. (Conversely, it can also report when it’s still in operational condition and doesn’t need to be replaced.)


The research could lead to composites that not only “feel pain” but can show operators where it “hurts” in the same way a human’s nerves tell the brain where damage to the body has occurred. Used in composite materials on aircraft, the potential for the material is extraordinary.


The U.S. Army Research Lab in Maryland is interested in the skin. Indeed, it has provided Myers and Williams with a nearly $1 million grant to apply the material to military aircraft components. The research could help the Army save money on rotorcraft maintenance, said Asha Hall, the lead co-principal investigator and Prognostics and Diagnostics acting team lead in the Mechanics Division of the Vehicle Technology Directorate at the U.S. Army Research Laboratory.


The skin is a thin layer of magnetostrictive film sandwiched between two sheets of carbon fiber reinforced polymer, or CFRPs. (Magnetorestrictive materials, in this case Terfenol-D, an alloy comprised of terbium, dysprosium and iron, are those that change their dimensions and shape when they undergo magnetization.) Essentially, the material “feels” physical stress by sensing changes in the magnetic field, and relays this information to operators, who can then evaluate the structural integrity of the composite materials.


“We’re trying to extend that maintenance-free operating period,” she said. “The big, big impact is to reduce sustainment costs for the Army.”


“The embedded magnetostrictive material is sensing the problems or damage in the composite structure, whether it is matrix cracking, fiber breakage, or delamination,” Professor Myers told Design News. “This would be useful for military applications as various composite systems are being utilized for only a specified period of time and disposed without performance testing.”


The smart structures would be manufactured using the layered composite as one unit rather than as a retrofitted part. The composite material is lightweight and requires no power. As a bonus, it’s also able to operate in harsh environments.


Monitoring the health of structures with real-time sensors isn’t new to the military, but current systems require the sensors to be retrofitted after manufacturing, which presents practical limitations. While the military is the first in line for the smart skin, there could ultimately be applications for consumer vehicles, as well. It’s a way to move away from the current process of “destructive evaluation” to attain a state of non-destructive real-time structural health monitoring of aircraft. Think of it like a human patient wearing a heart and brain monitor.


“The magnetostrictive material has actuation (shape changing) and energy harvesting capabilities when excited by a magnetic field or high vibration environment,” Professor Myers told Design News. “However, much research and variational approaches would be required for that transition.” Continued research into the viability of the technology would be necessary to bring the costs to more affordable levels (the magnetorestrictive material currently costs about $20 per gram).


USAF Looks to Cloud-Based App to Help Maintain Propulsion Systems

The U.S. Air Force (USAF) is seeking information on Reliability Centered Maintenance (RCM) cloud-based application development for its propulsion systems. In a request for information (RFI) posted on Beta.Sam.gov, the USAF said the Propulsion Integration Office (PIC) located at Tinker Air Force Base, Okla., seeks to gather information from the private sector to shape a future RCM contract that will support multiple engine platforms. USAF is looking to pursue RCM, a maintenance planning model that helps ensure USAF’s propulsion systems continue to perform in their present operating context, to achieve an increase in cost-effectiveness, reliability, machine uptime, and a better understanding of the USAF’s level of risk.


For its eventual contract, the PIC is looking for vendors who have the technical expertise and capability needed to integrate cloud-based apps for engine type-model series. The RFI said that the apps must utilize machine learning to enable RCM, including the ability to identify required maintenance actions to optimize reliability and cost-effectiveness. The eventual app must include a deployment readiness tool, EShop Optimization, CShop Optimization, a reliability predictor tool, data set monitoring, maintenance triage, kitting, and a workscope cost optimization tool, and need to be based on original prototype data and analytical models for engines within the Propulsion Directorate engine portfolio.


The USAF is asking for respondents to provide information on their experience with both RCM and military aircraft propulsion and maintenance activity, as well as their experience with cloud migration and machine learning, natural language processing, and domain ontologies. The RFI also provides additional questions regarding the app capabilities the PIC is seeking.


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