A survey of outlier detection methodologies

Outlier detection has been used for centuries to detect and, where appropriate, remove anomalous observations from data. Outliers arise due to mechanical faults, changes in system behaviour, fraudulent behaviour, human error, instrument error or simply through natural deviations in populations. Their detection can identify system faults and fraud before they escalate with potentially catastrophic consequences. It can identify errors and remove their contaminating effect on the data set and as such to purify the data for processing. The original outlier detection methods were arbitrary but now, principled and systematic techniques are used, drawn from the full gamut of Computer Science and Statistics. In this paper, we introduce a survey of contemporary techniques for outlier detection. We identify their respective motivations and distinguish their advantages and disadvantages in a comparative review

Perturbation Analysis for Robust Damage Detection with Application to Multifunctional Aircraft Structures

The most widely known form of multifunctional aircraft structure is smart structures for structural health monitoring (SHM). The aim is to provide automated systems whose purposes are to identify and to characterize possible damage within structures by using a network of actuators and sensors. Unfortunately, environmental and operational variability render many of the proposed damage detection methods difficult to successfully be applied. In this paper, an original robust damage detection approach using output-only vibration data is proposed. It is based on independent component analysis and matrix perturbation analysis, where an analytical threshold is proposed to get rid of statistical assumptions usually performed in damage detection approach. The effectiveness of the proposed SHM method is demonstrated numerically using finite element simulations and experimentally through a conformal load-bearing antenna structure and composite plates instrumented with piezoelectric ceramic materials.FUI MSIE (Pole Astech

Routines, learning by using and networks: the case of aircraft maintenance

The purpose of this paper is to explore the notion of routines and its connection to the evolution of “learning-by-using” in a complex network setting, aircraft maintenance. Despite continued theoretical interest, there has been a dearth of empirical studies in how routines emerge and develop in the field. In addition, few studies have considered how routines intersect and interact across conventional organisational boundaries. Aircraft maintenance stands at the junctions of a number of relationships that define and constrain how maintenance operations are to be performed, namely airframe manufacturer-maintenance station and maintenance station-aircraft operator. In addition, aircraft maintenance is governed by a highly formalised set of rules involving formal institutions and regulatory bodies (e.g. industry associations, civil aviation authorities). A system governed by tight routines might be expected to learn only gradually and slowly. The paper discusses how the combination of routines with the accumulation and rapid diffusion of “learning-by-using” mechanisms at different levels of the network of actors directly and indirectly involved in aircraft maintenanceinfo:eu-repo/semantics/publishedVersio

NASA patent abstracts bibliography: A continuing bibliography. Section 1: Abstracts (supplement 38)

Abstracts are provided for 132 patents and patent applications entered into the NASA scientific and technical information system during the period July 1990 through December 1990. Each entry consists of a citation, an abstract, and in most cases, a key illustration selected from the patent or patent application

Emerging Needs for Pervasive Passive Wireless Sensor Networks on Aerospace Vehicles

NASA is investigating passive wireless sensor technology to reduce instrumentation mass and volume in ground testing, air flight, and space exploration applications. Vehicle health monitoring systems (VHMS) are desired on all aerospace programs to ensure the safety of the crew and the vehicles. Pervasive passive wireless sensor networks facilitate VHMS on aerospace vehicles. Future wireless sensor networks on board aerospace vehicles will be heterogeneous and will require active and passive network systems. Since much has been published on active wireless sensor networks, this work will focus on the need for passive wireless sensor networks on aerospace vehicles. Several passive wireless technologies such as microelectromechanical systems MEMS, SAW, backscatter, and chipless RFID techniques, have all shown potential to meet the pervasive sensing needs for aerospace VHMS applications. A SAW VHMS application will be presented. In addition, application areas including ground testing, hypersonic aircraft and spacecraft will be explored along with some of the harsh environments found in aerospace applications

Investigating Forward Flight Multirotor Wind Tunnel Testing in a 3-by 4-foot Wind Tunnel

Investigation of complex multirotor aerodynamic phenomena via wind tunnel experimentation is becoming extremely important with the rapid progress in advanced distributed propulsion VTOL concepts. Much of this experimentation is being performed in large, highly advanced tunnels. However, the proliferation of this class of vehicles extends to small aircraft used by small businesses, universities, and hobbyists without ready access to this level of test facility. Therefore, there is a need to investigate whether multirotor vehicles can be adequately tested in smaller wind tunnel facilities. A test rig for a 2.82-pound quadcopter was developed to perform powered testing in the Cal Poly Aerospace Department’s Low Speed Wind Tunnel, equipped with a 3-foot tall by 4-foot wide test section. The results were compared to data from similar tests performed in the U.S. Army 7-by 10-ft Wind Tunnel at NASA Ames. The two data sets did not show close agreement in absolute terms but demonstrated similar trends. Due to measurement uncertainties, the contribution of wind tunnel interference effects to this discrepancy in measurements was not able to be properly quantified, but is likely a major contributor. Flow visualization results demonstrated that tunnel interference effects can likely be minimized by testing at high tunnel speeds with the vehicle pitched 10-degrees or more downward. Suggestions towards avoiding the pitfalls inherent to multirotor wind tunnel testing are provided. Additionally, a modified form of the conventional lift-to-drag ratio is presented as a metric of electric multirotor aerodynamic efficiency

Prediction of landing gear loads using machine learning techniques

This article investigates the feasibility of using machine learning algorithms to predict the loads experienced by a landing gear during landing. For this purpose, the results on drop test data and flight test data will be examined. This article will focus on the use of Gaussian process regression for the prediction of loads on the components of a landing gear. For the learning task, comprehensive measurement data from drop tests are available. These include measurements of strains at key locations, such as on the side-stay and torque link, as well as acceleration measurements of the drop carriage and the gear itself, measurements of shock absorber travel, tyre closure, shock absorber pressure and wheel speed. Ground-to-tyre loads are also available through measurements made with a drop test ground reaction platform. The aim is to train the Gaussian process to predict load at a particular location from other available measurements, such as accelerations, or measurements of the shock absorber. If models can be successfully trained, then future load patterns may be predicted using only these measurements. The ultimate aim is to produce an accurate model that can predict the load at a number of locations across the landing gear using measurements that are readily available or may be measured more easily than directly measuring strain on the gear itself (for example, these may be measurements already available on the aircraft, or from a small number of sensors attached to the gear). The drop test data models provide a positive feasibility test which is the basis for moving on to the critical task of prediction on flight test data. For this, a wide range of available flight test measurements are considered for potential model inputs (excluding strain measurements themselves), before attempting to refine the model or use a smaller number of measurements for the prediction

An Integrated Procedure to Assess the Stability of Coastal Rocky Cliffs: From UAV Close-Range Photogrammetry to Geomechanical Finite Element Modeling

The present paper explores the combination of unmanned aerial vehicle (UAV) photogrammetry and three-dimensional geomechanical modeling in the investigation of instability processes of long sectors of coastal rocky cliffs. The need of a reliable and detailed reconstruction of the geometry of the cliff surfaces, beside the geomechanical characterization of the rock materials, could represent a very challenging requirement for sub-vertical coastal cliffs overlooking the sea. Very often, no information could be acquired by alternative surveying methodologies, due to the absence of vantage points, and the fieldwork could pose a risk for personnel. The case study is represented by a 600 m long sea cliff located at Sant\u2019Andrea (Melendugno, Apulia, Italy). The cliff is characterized by a very complex geometrical setting, with a suggestive alternation of 10 to 20 m high vertical walls, with frequent caves, arches and rock-stacks. Initially, the rocky cliff surface was reconstructed at very fine spatial resolution from the combination of nadir and oblique images acquired by unmanned aerial vehicles. Successively, a limited area has been selected for further investigation. In particular, data refinement/decimation procedure has been assessed to find a convenient three-dimensional model to be used in the finite element geomechanical modeling without loss of information on the surface complexity. Finally, to test integrated procedure, the potential modes of failure of such sector of the investigated cliff were achieved. Results indicate that the most likely failure mechanism along the sea cliff examined is represented by the possible propagation of shear fractures or tensile failures along concave cliff portions or over-hanging due to previous collapses or erosion of the underlying rock volumes. The proposed approach to the investigation of coastal cliff stability has proven to be a possible and flexible tool in the rapid and highly-automated investigation of hazards to slope failure in coastal areas