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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Investigation of Current Methods to Identify Helicopter Gear Health

This paper provides an overview of current vibration methods used to identify the health of helicopter transmission gears. The gears are critical to the transmission system that provides propulsion, lift and maneuvering of the helicopter. This paper reviews techniques used to process vibration data to calculate conditions indicators (CI s), guidelines used by the government aviation authorities in developing and certifying the Health and Usage Monitoring System (HUMS), condition and health indicators used in commercial HUMS, and different methods used to set thresholds to detect damage. Initial assessment of a method to set thresholds for vibration based condition indicators applied to flight and test rig data by evaluating differences in distributions between comparable transmissions are also discussed. Gear condition indicator FM4 values are compared on an OH58 helicopter during 14 maneuvers and an OH58 transmission test stand during crack propagation tests. Preliminary results show the distributions between healthy helicopter and rig data are comparable and distributions between healthy and damaged gears show significant differences.

Dempsey, Paula J.↗
NASA NTRS2007

Investigation of Current Methods to Identify Helicopter Gear Health

This paper provides an overview of current vibration methods used to identify the health of helicopter transmission gears. The gears are critical to the transmission system that provides propulsion, lift and maneuvering of the helicopter. This paper reviews techniques used to process vibration data to calculate conditions indicators (CI's), guidelines used by the government aviation authorities in developing and certifying the Health and Usage Monitoring System (HUMS), condition and health indicators used in commercial HUMS, and different methods used to set thresholds to detect damage. Initial assessment of a method to set thresholds for vibration based condition indicators applied to flight and test rig data by evaluating differences in distributions between comparable transmissions are also discussed. Gear condition indicator FM4 values are compared on an OH58 helicopter during 14 maneuvers and an OH58 transmission test stand during crack propagation tests. Preliminary results show the distributions between healthy helicopter and rig data are comparable and distributions between healthy and damaged gears show significant differences.

Dempsey, Paula J.↗
NASA NTRS2001

The Application of Time-Frequency Methods to HUMS

This paper reports the study of four time-frequency transforms applied to vibration signals and presents a new metric for comparing them for fault detection. The four methods to be described and compared are the Short Time Frequency Transform (STFT), the Choi-Williams Distribution (WV-CW), the Continuous Wavelet Transform (CWT) and the Discrete Wavelet Transform (DWT). Vibration data of bevel gear tooth fatigue cracks, under a variety of operating load levels, are analyzed using these methods. The new metric for automatic fault detection is developed and can be produced from any systematic numerical representation of the vibration signals. This new metric reveals indications of gear damage with all of the methods on this data set. Analysis with the CWT detects mechanical problems with the test rig not found with the other transforms. The WV-CW and CWT use considerably more resources than the STFT and the DWT. More testing of the new metric is needed to determine its value for automatic fault detection and to develop methods of setting the threshold for the metric.

Pryor, Anna H.↗
NASA NTRS2015

Evaluation of MEMS-Based Wireless Accelerometer Sensors in Detecting Gear Tooth Faults in Helicopter Transmissions

The diagnostics capability of micro-electro-mechanical systems (MEMS) based rotating accelerometer sensors in detecting gear tooth crack failures in helicopter main-rotor transmissions was evaluated. MEMS sensors were installed on a pre-notched OH-58C spiral-bevel pinion gear. Endurance tests were performed and the gear was run to tooth fracture failure. Results from the MEMS sensor were compared to conventional accelerometers mounted on the transmission housing. Most of the four stationary accelerometers mounted on the gear box housing and most of the CI's used gave indications of failure at the end of the test. The MEMS system performed well and lasted the entire test. All MEMS accelerometers gave an indication of failure at the end of the test. The MEMS systems performed as well, if not better, than the stationary accelerometers mounted on the gear box housing with regards to gear tooth fault detection. For both the MEMS sensors and stationary sensors, the fault detection time was not much sooner than the actual tooth fracture time. The MEMS sensor spectrum data showed large first order shaft frequency sidebands due to the measurement rotating frame of reference. The method of constructing a pseudo tach signal from periodic characteristics of the vibration data was successful in deriving a TSA signal without an actual tach and proved as an effective way to improve fault detection for the MEMS.

gears↗
DOE OSTI2021

Machine Learning and Economic Models to Enable Risk-Informed Condition Based Maintenance of a Nuclear Plant Asset

The primary objective of this research is to address challenges in the implementation of risk-informed, condition-based predictive maintenance (PdM), which reduces operating costs while still maintaining the safety and reliability of commercial nuclear power plants (NPPs). To achieve the objective, risk models are being developed by taking advantage of advancements in data analytics, deep learning, machine learning (ML), and artificial intelligence (AI). The notable outcomes presented in the report include ? Development of a ML models using heterogeneous plant process and vibration data collected at different spatial and temporal resolutions from the Salem?s CWS to diagnose a circulating water pump (CWP) failure based on salient fault signatures. The developed diagnostic models are extendable to other faults associated with CWPs and CWP motors given associated fault signatures. ? Development of a natural language processing (NLP) technique to automatically classify the WO data into different categories. The developed NLP technique was validated on independent WO data. This automates the tedious and time-consuming activity of mining and classifying WOs by subject matter experts. ? Estimation of mean time between downtime (i.e., time duration between time instances when 1 or more CWPs are not available) and developed an approach to establish reliability of CWS components using unstructured WO data along with CWS plant process data. ? Formulation of economic model based on Markov chain models. The parameters of associated with the transition rate between different states of Markov chain models were estimated using WO data. The economic model formulation and discussion captures both time-independent and time-dependent parameter variation, leading to risk-informed decision-making.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1990

Monitoring techniques for the X-29A aircraft's high-speed rotating power takeoff shaft

The experimental X-29A forward swept-wing aircraft has many unique and critical systems that require constant monitoring during ground or flight operation. One such system is the power takeoff shaft, which is the mechanical link between the engine and the aircraft-mounted accessory drive. The X-29A power takeoff shaft opertes in a range between 0 and 16,810 rpm, is longer than most jet engine power takeoff shafts, and is made of graphite epoxy material. Since the X-29A aircraft operates on a single engine, failure of the shaft during flight could lead to loss of the aircraft. The monitoring techniques and test methods used during power takeoff shaft ground and flight operations are discussed. Test data are presented in two case studies where monitoring and testing of the shaft dynamics proved instrumental in discovering and isolating X-29A power takeoff shaft problems. The first study concerns the installation of an unbalanced shaft. The effect of the unbalance on the shaft vibration data and the procedure used to correct the problem are discussed. The second study deals with the shaft exceeding the established vibration limits during flight. This case study found that the vibration of connected rotating machinery unbalances contributed to the excessive vibration level of the shaft. The procedures used to identify the contributions of other rotating machinery unbalances to the power takeoff shaft unbalance are discussed.

Voracek, David F.↗
NASA NTRS1993

Pattern classifier for health monitoring of helicopter gearboxes

The application of a newly developed diagnostic method to a helicopter gearbox is demonstrated. This method is a pattern classifier which uses a multi-valued influence matrix (MVIM) as its diagnostic model. The method benefits from a fast learning algorithm, based on error feedback, that enables it to estimate gearbox health from a small set of measurement-fault data. The MVIM method can also assess the diagnosability of the system and variability of the fault signatures as the basis to improve fault signatures. This method was tested on vibration signals reflecting various faults in an OH-58A main rotor transmission gearbox. The vibration signals were then digitized and processed by a vibration signal analyzer to enhance and extract various features of the vibration data. The parameters obtained from this analyzer were utilized to train and test the performance of the MVIM method in both detection and diagnosis. The results indicate that the MVIM method provided excellent detection results when the full range of faults effects on the measurements were included in training, and it had a correct diagnostic rate of 95 percent when the faults were included in training.

Chin, Hsinyung↗
NASA NTRS2003

Detailed Vibration Analysis of Pinion Gear with Time-Frequency Methods

In this paper, the authors show a detailed analysis of the vibration signal from the destructive testing of a spiral bevel gear and pinion pair containing seeded faults. The vibration signal is analyzed in the time domain, frequency domain and with four time-frequency transforms: the Short Time Frequency Transform (STFT), the Wigner-Ville Distribution with the Choi-Williams kernel (WV-CW), the Continuous Wavelet' Transform (CWT) and the Discrete Wavelet Transform (DWT). Vibration data of bevel gear tooth fatigue cracks, under a variety of operating load levels and damage conditions, are analyzed using these methods. A new metric for automatic anomaly detection is developed and can be produced from any systematic numerical representation of the vibration signals. This new metric reveals indications of gear damage with all of the time-frequency transforms, as well as time and frequency representations, on this data set. Analysis with the CWT detects changes in the signal at low torque levels not found with the other transforms. The WV-CW and CWT use considerably more resources than the STFT and the DWT. More testing of the new metric is needed to determine its value for automatic anomaly detection and to develop fault detection methods for the metric.

Mosher, Marianne↗
NASA NTRS1993

Identification and interpretation of patterns in rocket engine data

A prototype software system was constructed to detect anomalous Space Shuttle Main Engine (SSME) behavior in the early stages of fault development significantly earlier than the indication provided by either redline detection mechanism or human expert analysis. The major task of the research project is to analyze ground test data, to identify patterns associated with the anomalous engine behavior, and to develop a pattern identification and detection system on the basis of this analysis. A prototype expert system which was developed on both PC and Symbolics 3670 lisp machine for detecting anomalies in turbopump vibration data was checked with data from ground tests 902-473, 902-501, 902-519, and 904-097 of the Space Shuttle Main Engine. The neural networks method was also applied to supplement the statistical method utilized in the prototype system to investigate the feasibility in detecting anomalies in turbopump vibration of SSME. In most cases the anomalies detected by the expert system agree with those reported by NASA. On the neural networks approach, the results are given the successful detection rate higher than 95 percent to identify either normal or abnormal running condition based on the experimental data as well as numerical simulation.

Lo, C. F.↗
NASA NTRS1982

Analysis of a turbine rotor containing a transverse crack at Oak Creek Unit 17

Transient increases in one, two and three per revolution vibration characteristics of a low pressure steam turbine were observed during steam temperature reduction operations. Vibration and fracture mechanics analyses suggested the presence of a transverse shaft crack which was eventually identified by ultrasonic inspection and confirmed by destructive sectioning. Signature analyses of vibration data recorded over a two-year period prior to crack identification are correlated with fatigue crack growth, which occurred intermittently during transient temperature decreases. The apparent increased response of the rotor to vibration is due to asymmetric stiffness changes introduced by the growing transverse crack. The vibration response is predicted to increase with increasing crack depths in excess of 10% of the shaft diameter. Fracture mechanics analyses predict that fatigue crack growth occurred during periods of steam temperature decrease, when high surface tensile stresses are present. These same transient thermal stresses are shown to have retarded and prevented subsequent fatigue crack growth during steady operation.

Rogers, G. W.↗
NASA NTRS1975

Experimental studies for determining human discomfort response to vertical sinusoidal vibration

A study was conducted to investigate several problems related to methodology and design of experiments to obtain human comfort response to vertical sinusoidal vibration. Specifically, the studies were directed to the determination of (1) the adequacy of frequency averaging of vibration data to obtain discomfort predictors, (2) the effect of practice on subject ratings, (3) the effect of the demographic factors of age, sex, and weight, and (4) the relative importance of seat and floor vibrations in the determination of measurement and criteria specification location. Results indicate that accurate prediction of discomfort requires knowledge of both the acceleration level and frequency content of the vibration stimuli. More importantly, the prediction of discomfort was shown to be equally good based upon either floor accelerations or seat accelerations. Furthermore, it was demonstrated that the discomfort levels in different seats resulting from similar vibratory imputs were equal. Therefore, it was recommended that criteria specifications and acceleration measurements be made at the floor location. The results also indicated that practice did not systematically influence discomfort responses nor did the demographic factors of age, weight, and sex contribute to the discomfort response variation.

Dempsey, T. K.↗
NASA NTRS1998

Experimental flight test vibration measurements and nondestructive inspection on a USCG HC-130H aircraft

This paper presents results of experimental flight test vibration measurements and structural inspections performed by the Federal Aviation Administration's Airworthiness Assurance NDI Validation Center (AANC) at Sandia National Laboratories and the US Coast Guard Aircraft Repair and Supply Center (ARSC). Structural and aerodynamic changes induced by mounting a Forward Looking Infrared (FLIR) system on a USCG HC-130H aircraft are described. The FLIR adversely affected the air flow characteristics and structural vibration on the external skin of the aircraft's right main wheel well fairing. Upon initial discovery of skin cracking and visual observation of skin vibration in flight by the FLIR, a baseline flight without the FLIR was conducted and compared to other measurements with the FLIR installed. Nondestructive inspection procedures were developed to detect cracks in the skin and supporting structural elements and document the initial structural condition of the aircraft. Inspection results and flight test vibration data revealed that the FLIR created higher than expected flight loading and was the possible source of the skin cracking. The Coast Guard performed significant structural repair and enhancement on this aircraft, and additional in-flight vibration measurements were collected on the strengthened area both with and without the FLIR installed. After three months of further operational FLIR usage, the new aircraft skin with the enhanced structural modification was reinspected and found to be free of flaws. Additional US Coast Guard HC-130H aircraft are now being similarly modified to accommodate this FLIR system. Measurements of in- flight vibration levels with and without the FLIR installed, and both before and after the structural enhancement and repair were conducted on the skin and supporting structure in the aircraft's right main wheel fairing. Inspection results and techniques developed to verify the aircraft's structural integrity are discussed.

US COAST GUARD↗
NASA NTRS1976

Practical aspects of a maximum likelihood estimation method to extract stability and control derivatives from flight data

A maximum likelihood estimation method was applied to flight data and procedures to facilitate the routine analysis of a large amount of flight data were described. Techniques that can be used to obtain stability and control derivatives from aircraft maneuvers that are less than ideal for this purpose are described. The techniques involve detecting and correcting the effects of dependent or nearly dependent variables, structural vibration, data drift, inadequate instrumentation, and difficulties with the data acquisition system and the mathematical model. The use of uncertainty levels and multiple maneuver analysis also proved to be useful in improving the quality of the estimated coefficients. The procedures used for editing the data and for overall analysis are also discussed.

Iliff, K. W.↗
DOE OSTI2021

Vibrational spectroscopy of uranium tetrafluoride hydrates

Uranium tetrafluoride (UF 4 ) is an important intermediate in the production of UF6 and nuclear fuel. Historical characterization of UF 4 with Raman spectroscopy was plagued with ambiguity until the first accurate Raman spectrum was published by our group in 2016. Although generally considered to be relatively stable, UF 4 can hydrolyze to form numerous UF 4 hydrates that may play a role in future uranium waste forms. In contrast to anhydrous UF 4 , the hydrates, with their OH stretch and HOH bending modes, can be spectroscopically characterized by the type and degree of water bonding in the crystal lattice, which can yield additional information about their crystal structure. Herein, vibrational spectroscopy (Raman and infrared) was used to characterize three different UF 4 hydrates: UF 4 (H 2 O) 0.33 , U 3 F 12 (H 2 O), and UF 4 (H 2 O) 2.5 . Spectra show the different hydrates vary in the number of observed bands, full-width half-maximum of the bands, and band intensity. These differences are due to varying interactions between the OH stretch and HOH bending modes with UF 4 and the polymeric UF 4 structure in the crystal lattice. These vibrational data, in combination with spectral fitting and crystallographic structures measured with powder X-ray diffraction and single crystal X-ray diffraction, provide unique details on the location of water molecules in the crystal lattice of hydrated UF 4 , and provide an interesting contrast to the vibrational spectra of anhydrous UF 4 .

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2000

Advanced Engine Health Management Applications of the SSME Real-Time Vibration Monitoring System

The Real Time Vibration Monitoring System (RTVMS) is a 32-channel high speed vibration data acquisition and processing system developed at Marshall Space Flight Center (MSFC). It Delivers sample rates as high as 51,200 samples/second per channel and performs Fast Fourier Transform (FFT) processing via on-board digital signal processing (DSP) chips in a real-time format. Advanced engine health assessment is achieved by utilizing the vibration spectra to provide accurate sensor validation and enhanced engine vibration redlines. Discrete spectral signatures (such as synchronous) that are indicators of imminent failure can be assessed and utilized to mitigate catastrophic engine failures- a first in rocket engine health assessment. This paper is presented in viewgraph form.

Fiorucci, Tony R.↗
NASA NTRS1992

Acoustic fatigue characterization of carbon/carbon panels

Data from a sonic fatigue test of a blade-stiffened carbon/carbon panel is analyzed to determine the progression of damage to failure. The reduction in stiffness, as observed from acceleration measurements taken during the test, is correlated with the physical damage. Damage was measured through visual inspection, thermographic measurements, and through the novel use of vibration data collected using a scanning laser vibrometer.

Rizzi, S. A.↗
NASA NTRS1975

Computer analysis of railcar vibrations

Computer models and techniques for calculating railcar vibrations are discussed along with criteria for vehicle ride optimization. The effect on vibration of car body structural dynamics, suspension system parameters, vehicle geometry, and wheel and rail excitation are presented. Ride quality vibration data collected on the state-of-the-art car and standard light rail vehicle is compared to computer predictions. The results show that computer analysis of the vehicle can be performed for relatively low cost in short periods of time. The analysis permits optimization of the design as it progresses and minimizes the possibility of excessive vibration on production vehicles.

Vlaminck, R. R.↗
NASA NTRS2003

Maneuver Classification for Aircraft Fault Detection

Automated fault detection is an increasingly important problem in aircraft maintenance and operation. Standard methods of fault detection assume the availability of either data produced during all possible faulty operation modes or a clearly-defined means to determine whether the data provide a reasonable match to known examples of proper operation. In the domain of fault detection in aircraft, identifying all possible faulty and proper operating modes is clearly impossible. We envision a system for online fault detection in aircraft, one part of which is a classifier that predicts the maneuver being performed by the aircraft as a function of vibration data and other available data. To develop such a system, we use flight data collected under a controlled test environment, subject to many sources of variability. We explain where our classifier fits into the envisioned fault detection system as well as experiments showing the promise of this classification subsystem.

Oza, Nikunj C.↗