Predictive Models of an Electro-mechanical Driving System for Failure Testing of Strain Gauges

Strain gauges are bonded at high stress locations on the surface of critical structural components such as turbine blades to measure fatigue characteristics and detect early warning signs of high cycle fatigue. However, strain gauges do not always report expected measurements. The usual response by maintenance technicians to these failing signals is to investigate the component for weakness, check the placement of the gauges on the component, or examine the instrumentation for failure or damage. However, little research has been conducted to show when the failing signals are the fault of the strain gauge. Such failure modes of strain gauges include improper gauge installation, over-straining, operating outside the temperature limits, physical damage and environmental wear, and improper gauge selection. Failure Modes and Effects Analysis, FMEA, is a methodology for monitoring failure modes and their potential effects, causes, and solutions. This research consisted of the introductory steps in developing and analyzing a laboratory setup for FMEA strain gauge testing and analysis. The primary goal of this research was to develop predictive models for strain gauge responses under controlled laboratory conditions. A testing station was developed that generated a mechanical motion on a beam, subjecting strain gauges to a sinusoidally-varying strain. Predictive models of the testing station were developed and experimentally analyzed. Models were also developed for two particular failure modes, debonding and wire lead termination, and experimental analysis was conducted. In general, the models adequately describe the operation of a strain gauge operating under normal conditions and in the studied failure mode. Predicted and experimental data are presented that show the characteristic signals in terms of time domain, histogram, and frequency domain analysis

Structural health monitoring of offshore wind turbines: A review through the Statistical Pattern Recognition Paradigm

Offshore Wind has become the most profitable renewable energy source due to the remarkable development it has experienced in Europe over the last decade. In this paper, a review of Structural Health Monitoring Systems (SHMS) for offshore wind turbines (OWT) has been carried out considering the topic as a Statistical Pattern Recognition problem. Therefore, each one of the stages of this paradigm has been reviewed focusing on OWT application. These stages are: Operational Evaluation; Data Acquisition, Normalization and Cleansing; Feature Extraction and Information Condensation; and Statistical Model Development. It is expected that optimizing each stage, SHMS can contribute to the development of efficient Condition-Based Maintenance Strategies. Optimizing this strategy will help reduce labor costs of OWTs׳ inspection, avoid unnecessary maintenance, identify design weaknesses before failure, improve the availability of power production while preventing wind turbines׳ overloading, therefore, maximizing the investments׳ return. In the forthcoming years, a growing interest in SHM technologies for OWT is expected, enhancing the potential of offshore wind farm deployments further offshore. Increasing efficiency in operational management will contribute towards achieving UK׳s 2020 and 2050 targets, through ultimately reducing the Levelised Cost of Energy (LCOE)

Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0

Instrumentation and Modal Modeling of a Commercial Wind Turbine

With commercial wind power generation coming of age, the majority of research and development has gone into the design of turbine blades and the components within the nacelle, leaving the turbine mast largely ignored. The author proposes a system for the instrumentation and monitoring the modal properties of a commercial wind turbine, as well as the design and creation of a model suitable for use in wind tunnel tests. This is accomplished via a combination of experimental and theoretical methods. A system for structural monitoring of the turbine will allow for early warning and preventive maintenance of masts in the field. The model will focus on conditions where failure of the mast is most likely to occur, such as severe weather events. These tools will prove valuable in the design of masts as well as siting for wind farms

SSME lifetime prediction and verification, integrating environments, structures, materials: The challenge

The planned missions for the space shuttle dictated a unique and technology-extending rocket engine. The high specific impulse requirements in conjunction with a 55-mission lifetime, plus volume and weight constraints, produced unique structural design, manufacturing, and verification requirements. Operations from Earth to orbit produce severe dynamic environments, which couple with the extreme pressure and thermal environments associated with the high performance, creating large low cycle loads and high alternating stresses above endurance limit which result in high sensitivity to alternating stresses. Combining all of these effects resulted in the requirements for exotic materials, which are more susceptible to manufacturing problems, and the use of an all-welded structure. The challenge of integrating environments, dynamics, structures, and materials into a verified SSME structure is discussed. The verification program and developmental flight results are included. The first six shuttle flights had engine performance as predicted with no failures. The engine system has met the basic design challenges

Total Hip Joint Replacement Biotelemetry System

The development of a biotelemetry system that is hermetically sealed within a total hip replacement implant is reported. The telemetry system transmits six channels of stress data to reconstruct the major forces acting on the neck of the prosthesis and uses an induction power coupling technique to eliminate the need for internal batteries. The activities associated with the telemetry microminiaturization, data recovery console, hardware fabrications, power induction systems, electrical and mechanical testing and hermetic sealing test results are discussed

A progressive collapse evaluation of steel structures in high temperature environment with optical fiber sensors

In the process of a progressive failure of steel structures in a post-earthquake fire, real-time assessment and prediction of structural behaviors are of paramount significance to an emergency evacuation and rescue effort. However, existing measurement technologies cannot provide the needed critical data such as large strains at high temperature. To bridge this gap, a novel optical fiber sensor network and an adaptive multi-scale finite element model (FEM) are proposed and developed in this study. The sensor network consists of long period fiber gratings (LPFG) sensors and extrinsic Fabry-Perot interferometer (EFPI) sensors or their integration. Each sensor is designed with a three-tier structure for an accurate and reliable measurement of large strains and for ease of installation. To maintain a balance between the total cost of computation and instrumentation and the accuracy in numerical simulation, a structure is divided into representative/critical components instrumented densely and the remaining components simulated computationally. The critical components and the remaining were modeled in different scales with fiber elements and beam/plate elements, respectively, so that the material behavior and load information measured from the critical components are representative to the remaining components and can be used to update the temperature distribution of the structure in real time. Sensitivity studies on the number of sensors and the initial selection of an updating temperature parameter were conducted. Both the sensor network and the FEM were validated with laboratory tests of a single-bay, one-story steel frame under simulated post-earthquake fire conditions. The validated FEM was applied to a two-bay, four-story steel building under the 1995 Kobe earthquake excitations. Based on extensive tests and analyses, the proposed sensor can measure a strain of 12% at as high as 800⁰C (1472⁰F) in temperature. Within the application range, the LPFG wavelength and the EFPI gap change linearly with the applied strain and temperature. The proposed updating criterion and algorithm in the adaptive FEM are proven to be effective. The number of sensors is sufficient in engineering applications as long as the sensors can adequately represent the material behavior of the instrumented components. The predicted structural behavior is unaffected by any change in a low temperature range and thus insensitive to the initial selection of the updating parameter --Abstract, page iii

Marshall Space Flight Center Research and Technology Report 2019

Today, our calling to explore is greater than ever before, and here at Marshall Space Flight Centerwe make human deep space exploration possible. A key goal for Artemis is demonstrating and perfecting capabilities on the Moon for technologies needed for humans to get to Mars. This years report features 10 of the Agencys 16 Technology Areas, and I am proud of Marshalls role in creating solutions for so many of these daunting technical challenges. Many of these projects will lead to sustainable in-space architecture for human space exploration that will allow us to travel to the Moon, on to Mars, and beyond. Others are developing new scientific instruments capable of providing an unprecedented glimpse into our universe. NASA has led the charge in space exploration for more than six decades, and through the Artemis program we will help build on our work in low Earth orbit and pave the way to the Moon and Mars. At Marshall, we leverage the skills and interest of the international community to conduct scientific research, develop and demonstrate technology, and train international crews to operate further from Earth for longer periods of time than ever before first at the lunar surface, then on to our next giant leap, human exploration of Mars. While each project in this report seeks to advance new technology and challenge conventions, it is important to recognize the diversity of activities and people supporting our mission. This report not only showcases the Centers capabilities and our partnerships, it also highlights the progress our people have achieved in the past year. These scientists, researchers and innovators are why Marshall and NASA will continue to be a leader in innovation, exploration, and discovery for years to come

Characterizing the Load Environment of Ferry Landings for Washington State Ferries and the Alaska Marine Highway System

INE/AUTC 13.0